University of Southern California Dissertations and Theses

Multi-modality intravascular imaging by combined use of ultrasonic and opticial techniques

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Multi-modality intravascular imaging by combined use of ultrasonic and opticial techniques

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MULTI-MODALITY INTRAVASCULAR IMAGING
BY COMBINED USE OF ULTRASONIC AND OPTICIAL TECHNIQUES

by

Teng Ma

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BIOMEDICAL ENGINEERING)

August 2015

Portion of chapter 2 and chapter 3 © 2014 IEEE and 2014 SPIE
Chapter 4 © 2015 IEEE, chapter 5 © 2015 NPG, and chapter 6 © 2014 AIP
All other materials © 2015 Teng Ma

Dedication

To my beloved

Parents
Lirong Feng and Shudong Ma

i

Acknowledgements
I still remember the morning of December 2010 5:00 AM Pacific Time, during which I
sent the first email to my current advisor Dr. K. Kirk Shung to express my interests of joining his
research group. I’ll never forget the time when I received his positive reply immediately. It was
5:30 AM. That was one of the most surprised and excited moments in my life. Three months later,
I got a chance to visit the campus of University of Southern California (USC) as a Ph.D. applicant.
As soon as I stepped onto the beautiful campus and visited NIH Resource Center on Medical
Transducer Technology (UTRC), I found myself belonging to this place and made up my mind of
pursing a Ph.D. degree at USC, specifically under the guidance of Dr. Shung. From that time
onward, I started to realize that I needed to build up my soul as a Trojan with the slogan of “Fight
on”, and the wolverine’s “Go blue” at University of Michigan had to become a wonderful memory
for me. How time flies! The four years’ time at USC slipped in my fingers, to realize my dream of
becoming a biomedical engineering researcher, I swayed with the laughter and tears of youth, felt
the joy and pain of growing up, without any regrets. There are no words to express everything I
feel at this moment, but I want to take this opportunity to thank all the people who offered me help
and support during my four years Ph.D. study in the Department of Biomedical Engineering of
USC.
Back to the beginning of this journey. I would like to thank my advisor Dr. K. Kirk Shung,
for his mentorship and guidance that leads me to explore in the field of biomedical imaging. Your
warm smile and endless support always made me move forward, from the first time that I entered
into the laboratory of UTRC with little knowledge about ultrasound, to the present day that I’m
able to independently design and fabricate ultrasonic transducer, and acquire ultrasonic images.
More importantly, your mentorship is not only limited to my research development, your kindness
ii

and generosity have taught me how to professionalize as a young student. As the director of one
of the most prestigious and established ultrasound research laboratory in the world, you have also
shown me your leadership and collaborative spirit to work with people from different backgrounds.
I am equally indebted to my co-advisor, Dr. Qifa Zhou. I always think that I am very
fortunate to learn from you about ultrasonic imaging, to discuss with you about our research
projects, to vent my frustrations with you about failed experiments, and to share the joy with you
when we published new papers. Whenever I met with difficulties in making progresses of projects,
you were always patient to help me resolve the problems by using all the resources you have and
encourage me never give up. Whenever I achieved a little success, you never cherished words of
praise to make me feel more and more confident. I sincerely appreciate the freedom you gave me
to pursue my own ideas and interests. Your support on me is not limited to just research. As times
went by, I realized that it has become a habit of me to have a short talk with you on every morning
about life just as much as research. Sometimes, when I unintentionally released my personal
pressures to you, you always said “You are just like my son who need more experiences!” On the
other hand, you always cared about my health and safety just like my father. Without your guidance,
patience, encouragement and trust, I would not be able to make this dissertation possible and I
would not be where I am today. Thank you so much, Dr. Zhou.
I am also sincerely thankful to Dr. Zhongping Chen from University of California, Irvine
(UCI), who also provided me persistent support during my Ph.D. study. Thank you for providing
me access to all resources in your lab. It was a great honor and privilege for me to work with you,
and your talented, hard-working research group. Without your supervision, this dissertation would
not be possible. Without your inspirations, I would not be so clear on which direction I would go
after graduation.
iii

I would also like to express my sincere gratitude to other committee members of my
dissertation, Dr. Jesse Yen, Dr. Andrea Armani, and Dr. Megan McCain for their insightful
feedback and valuable time.
I thank my collaborators at UCI including Ms. Jiawen Li, Dr. Wenjuan Qi, Dr. Rui Li, Dr.
Jiang Zhu, Mr. Zhonglie Piao, and Ms. Rachel Qu. It has been a real pleasure working with you
all. I must specially thank Ms. Jiawen Li, who worked the most closely with me in the last four
years. I cannot remember how many times we worked together from early morning to late night to
make intravascular catheter, conduct experiments, solve technical problems, and consult with
clinicians. Without trust between us, we could not make so much progress on this collaborative
project. Although we cannot work together as before after graduation, I'm sure that we will
continue our friendship forever. I hope that you will enjoy your future life in Australia.
I thank Dr. Ji-xin Cheng as well as Dr. Pu Wang, Mr. Jie Hui at Purdue University. Without
your expertise in Ramen Laser development, we would not be able to make high-speed IVPA
imaging possible.
I thank Dr. Pranav Patel for his guidance and consultancies from interventional
cardiological perspective. I also thank Dr. Andrea Correa for interpreting histology sections from
pathological perspective.
I am greatly thankful to all my colleagues and friends at UTRC USC, especially graduate
students or postdoctoral fellows Dr. Ruimin Chen, Dr. Xiang Li, Dr. Yuling Chen, Ms. Mingyue
Yu, Mr. Xuejun Qian, Mr. Chi-Tat Chiu, Mr. Zeyu Chen, Dr. Ying Li, Mr. Yang Li, Mr. Chunlong
Fei, Mr. Thomas Cummins, Mr. Nestor Cabrera, and Mr. Payam Eliahoo, our lab manager Mr. Jay
Williams and our retired budget analyst Peter Lee. Special acknowledgement to Ruimin: thank
you for teaching me how to fabricate the tiny ultrasonic transducer/array hand by hand and step by
iv

step. Whenever I struggled in catching up the experiment deadlines, you were always there
available for help. To Xiang Li: thank you for your symmetrical training for me on the IVUS
technology which helped me tremendously to complete this thesis. To Yuling: my close friend and
companion, thank you for your time to listen attentively to my personal story and offer me sincere
advices. More importantly, whenever I had questions about ultrasound theory, you could always
help me find an answer. The countless lunch breaks with you were part of my fantastic memories
at USC. To Mingyue and Xuejun: thank you for joining my team and working together with me.
Your desires for leaning and hardworking spirits had made me share what I have known with you
unreservedly. With your effort and time, we have solved many problems which I was struggling
with during my research. I think highly of both of you, and I’m sure that you will achieve much
more than I can in continuing our projects.
Last but not the least, I would like to give my appreciations to my loved parents, Ms. Lirong
Feng and Mr. Shudong Ma, who started to fulfill their responsibility toward me by giving
themselves to me in unconditional love since the day when I was born. I want to thank you for
raising me up and shaping who I am today. Your incredible support and faith in me made it possible
for me to study abroad and realize my dream. When facing my 8 years’ study in the U.S., 6000
miles away from home, and 12 hours’ time difference, we were even closer. Thank you for
bringing me to the world, and I was, am and will be your son who makes you proud forever.

v

Table of Contents

Dedication ....................................................................................................................................... i
Acknowledgements ....................................................................................................................... ii
List of Tables ................................................................................................................................ ix
List of Figures ................................................................................................................................ x
Abstract ..................................................................................................................................... xviii
Chapter 1 Introduction................................................................................................................. 1
1.1 Clinical Background ............................................................................................................. 1
1.1.1 Atherosclerosis ............................................................................................................... 2
1.1.2 Thin-cap Fibroatheroma (TCFA) ................................................................................... 4
1.2 Intravascular Imaging Techniques ........................................................................................ 6
1.2.1 Intravascular Ultrasound (IVUS) ................................................................................... 7
1.2.2 Intravascular Optical Coherence Tomography (IV-OCT) ........................................... 13
1.2.3 Intravascular Photoacoustic (IVPA) ............................................................................ 15
1.2.4 Other Intravascular Imaging Techniques ..................................................................... 18
1.3 Scopes of the Dissertation ................................................................................................... 20
Chapter 2 Ultra-high Speed Fully Integrated IVUS and OCT Imaging System .................. 24
2.1 Motivation of Combined Use IVUS and OCT ................................................................... 24
2.2 Development of Hybrid IVUS-OCT Catheter .................................................................... 26
2.2.1 Previous Generations of Catheter Design .................................................................... 26
2.2.2 Optimized Back-to-back IVUS-OCT Catheter Design................................................ 28
2.3 Integrated IVUS-OCT System Setup and Signal Processing ............................................. 32
2.4 Imaging Results and Discussion ......................................................................................... 36
2.4.1 Coronary Artery Imaging by Using Back-to-back IVUS-OCT catheter ..................... 36
2.4.2 High Speed IVUS-OCT Imaging at 72 fps .................................................................. 39
Chapter 3 Diagnostic Accuracy and Diagnostic Criteria of Integrated IVUS-OCT System 47
3.1 Background and Literature Review .................................................................................... 47
3.2 Statistical Experiment Design ............................................................................................. 49
3.2.1 Specimen Preparation .................................................................................................. 49
3.2.2 Histology Analysis ....................................................................................................... 50
3.2.3 Imaging-based Diagnosis Analysis and Diagnostic Criteria ....................................... 50
3.2.4 Statistical Study ........................................................................................................... 52
3.3 Diagnostic Accuracy of Integrated IVUS-OCT System ..................................................... 53
3.3.1 Intraobserver Variability .............................................................................................. 53
3.3.2 Histological Diagnosis vs Imaging-based Diagnosis ................................................... 54
3.3.3 Sensitivity and Specificity Quantification ................................................................... 56
3.4 Characterization of Calcified, Fibrous and Lipid-rich Plaques .......................................... 57
3.5 Study Limitation and Future Improvement......................................................................... 62

vi

Chapter 4 Multi-frequency Intravascular Ultrasound (IVUS) Imaging ............................... 64
4.1 Introduction ......................................................................................................................... 65
4.2 Method and Material ........................................................................................................... 68
4.2.1 Catheter Design and Fabrication .................................................................................. 68
4.2.2 Phantom Preparation and Experimental Set-up ........................................................... 74
4.3 Transducer Characterization ............................................................................................... 75
4.4 Tissue Mimicking Phantom Imaging Results ..................................................................... 78
4.5 In vitro Human Cadaver Coronary Artery Imaging ............................................................ 81
4.6 Discussions and Conclusion ............................................................................................... 83
Chapter 5 High-speed Intravascular Photoacoustic Imaging ................................................. 86
5.1 Background ......................................................................................................................... 86
5.2 IVPA System Setup ............................................................................................................ 88
5.2.1 Ramen Laser ................................................................................................................ 88
5.2.2 3D Pull-back Rotary Scanning System ........................................................................ 89
5.3 Catheter Design ................................................................................................................... 91
5.3.1 Coaxial Design ............................................................................................................. 91
5.3.2 Sequential Design ........................................................................................................ 93
5.4 High Speed IVPA Imaging Results .................................................................................... 94
5.4.1 High Speed PA Imaging of Lipid-mimicking Phantom by the Coaxial Catheter........ 94
5.4.2 High Speed PA Imaging of Lipid-laden artery by the Coaxial Catheter ..................... 95
5.4.3 High Speed PA Imaging of Lipid-laden artery by the Sequential Catheter ................. 95
5.5 Discussion ........................................................................................................................... 96
Chapter 6 Confocal Acoustic Radiation Force Optical Coherence Elastography (ARF-
OCE)..............................................................................................................................................99
6.1 Development of ARF-OCE................................................................................................. 99
6.1.1 Overview of Elastography Technology ....................................................................... 99
6.1.2 Acoustic Radiation Force (ARF) Excitation Method ................................................ 103
6.1.3 Concept of ARF-OCE ................................................................................................ 106
6.2 Resonant Frequency ARF-OCE ........................................................................................ 109
6.2.1 Principle of Resonant Frequency ............................................................................... 110
6.2.2 Imaging Results and Discussion ................................................................................ 114
6.3 Confocal ARF-OCE by Using Single Ring Transducer ................................................... 117
6.3.1 Limitation of Previous ARF-OCE System ................................................................ 118
6.3.2 Confocal ARF-OCE and Ring Transducer Characterization ..................................... 118
6.3.3 Imaging Results and Discussion ................................................................................ 124
6.4 Confocal ARF-OCE by Using a Dual-ring Transducer .................................................... 129
6.4.1 Dual-ring Transducer Characterization ...................................................................... 130
6.4.2 Imaging Results and Discussion ................................................................................ 133

vii

Chapter 7 High Resolution Acoustic Radiation Force Based Ultrasonic Elastography .... 136
7.1 Background and Literature Review .................................................................................. 137
7.2 Methods and Materials ...................................................................................................... 140
7.2.1 Ultrasonic Transducer Design and Experimental Setup ............................................ 140
7.2.2 Phantom Preparation .................................................................................................. 142
7.3 Results and Discussion ..................................................................................................... 143
7.3.1 Transducer Alignment and Acoustic Field Characterization ..................................... 143
7.3.2 Phantom Imaging Results .......................................................................................... 146
7.3.3 Ex vivo Human Coronary Artery Image .................................................................... 151
7.4 Conclusions ....................................................................................................................... 152
Chapter 8 Summary and Perspectives .................................................................................... 154
8.1 Summary of the Thesis ..................................................................................................... 154
8.2 Perspectives of Multi-modality Intravascular Imaging ..................................................... 158
Bibliography .............................................................................................................................. 167

viii

List of Tables
Table 1-1: Design Parameters of a 45 MHz PMN-PT IVUS transducer. .................................... 10
Table 2-1: Summary of design parameters of three generations of IVUS-OCT probe design
(the highlighted parameter indicates the major limitation of design for dual-modality
intravascular catheter design). ..................................................................................................... 27
Table 3-1: Comparison of diagnostic criteria of atherosclerotic plaque components, adapted
from (Kawasaki, Bouma et al. 2006). .......................................................................................... 47
Table 3-2: Previous reported diagnostic accuracy (sensitivity/specificity) of IVUS-only and
OCT-only based diagnosis by Rieber’s (Rieber 2006), Kume’s (Kume T 2006), and
Kawasaki‘s (Kawasaki M 2006). ................................................................................................. 48
Table 3-3: The advantages and disadvantages of OCT and IVUS in classifying each type of
atherosclerotic plaque. ................................................................................................................. 48
Table 3-4: Interobserver variability of each imaging diagnosis. ................................................. 54
Table 3-5: Overall agreement between the imaging based diagnosis and histological diagnosis.
...................................................................................................................................................... 55
Table 3-6: Diagnostic accuracy (sensitivity and specificity) of IVUS-OCT, OCT-only and
IVUS-only imaging diagnosis for characterizing calcified, fibrous and lipid-rich plaques. Data
are percentages with 95% confidence intervals. .......................................................................... 57
Table 4-1: Piezoelectric properties of materials for IVUS imaging application. ........................ 69
Table 4-2: Properties of the materials used in IVUS transducer fabrication (Cannata, Ritter et
al. 2003) ....................................................................................................................................... 73
Table 4-3. Measured center frequencies, bandwidths and resolutions of the representative
transducers used in this study. ..................................................................................................... 76
Table 6-1: Comparison of different elasticity measurement and imaging methods, adapted
from (Sarvazyan, Hall et al. 2011). ............................................................................................ 102
Table 6-2: Acoustic output parameters (Hydrophone test). ....................................................... 122
Table 7-1: Design parameters and measured properties of transducers .................................... 141

ix

List of Figures
Figure 1-1: Anatomy of human coronary arteries. (Adapted from Patrick J. Lynch, medical
illustrator, http://commons.wikimedia.org/wiki/File%3ACoronary_arteries.png) ......................... 2
Figure 1-2: The formation of Atherosclerosis. (Adapted from www.medmovie.com) .................. 3
Figure 1-3: Procedures of Percutaneous Coronary Intervention (PCI): coronary artery stenting
(adapted from http://www.summitmedicalgroup.com/library/adult_care/pci_tx/). ........................ 4
Figure 1-4: (a) Schematic drawing of the morphologic features of a TCFA (Stolzmann,
Subramanian et al. 2011). (b) Histology image of TCFA (NC: necrotic core, Arrow: thin
fibrous cap) (Tavora, Cresswell et al. 2010). .................................................................................. 6
Figure 1-5: Imaging processing procedures of IVUS. .................................................................... 8
Figure 1-6: Fabrication process flow of 45 MHz side-viewing miniaturized IVUS transducers.
....................................................................................................................................................... 11
Figure 1-7: Prototype IVUS transducers: needle type (a); and flexible type (b). ......................... 12
Figure 1-8: Illustration of photoacoustic effect. ........................................................................... 15
Figure 1-9: (a) Photograph of integrated IVUS-NIRS imaging system (TVC imaging
systemTM, Infraredx, Inc) including a TVC Imaging SystemTM console, a TVC NexusTM
Controller, and a TVC InsightTM Catheter. (b) Multi-modality TVC Insight Catheter core
assembly. (c) TVC Composite™ View of co-registered near infrared spectroscopy lipid core
plaque with intravascular ultrasound. (d) chemogram of the near-infrared spectroscopic
(NIRS) image. The yellow-red color-coded map illustrates the probability of the presence of
a lipid core (yellow corresponds to high probability and red to low probability). (e) Co-
registration of IVUS and NIRS data. Adapted from website of Infraredx, Inc
(http://www.infraredx.com/). ........................................................................................................ 20
Figure 2-1: (a) Schematic of first generation of IVUS-OCT probe(Yin, Yang et al. 2010) (b)
Schematic and photography of second generation of IVUS-OCT probe (Li, Yin et al. 2010).(c)
Schematic and photography of third generation of IVUS-OCT probe (Yin, Li et al. 2011). ....... 27
Figure 2-2: A finished integrated IVUS-OCT catheter is inside a 3.6 Fr sheath. ......................... 28
Figure 2-3: Schematic of back-to-back OCT-IVUS probe, c) Photo of back-to-back probe,
showing the transducer. Insert: photo showing the OCT sub-probe, d) Schematic of
cardiovascular system. .................................................................................................................. 31
Figure 2-4: Ellipsoid-shape ball lens design to minimize astigmatism caused by toroidal
sheath, (a) 190µm-radius in X-direction and (c) 150µm-radius in Y-direction. Point Spread
Function of exiting beam at (b) X-direction and (d) Y-direction. ................................................ 32
x

Figure 2-5: Schematic of IVUS-OCT imaging system. The blue blocks represent signal flow;
the orange blocks represent the mechanical joints; the green blocks represent synchronizing
triggers. ......................................................................................................................................... 33
Figure 2-6: A rotary joint device connects the rotational and pull-back motor; and couples
electrical and optical signals from the rotational part to the stationary part. ................................ 34
Figure 2-7: Flow chart of signal acquisition and imaging processing of GPU based IVUS-
OCT system. ................................................................................................................................. 35
Figure 2-8: Time domain pulse-echo waveform and frequency spectrum of the IVUS probe
with a 1mm-long coaxial cable connecting to a slip ring. ............................................................ 37
Figure 2-9: Top row: Images of calcified plaques. (Ia) OCT, (Ib) IVUS and (Ic) merged OCT-
IVUS cross-sectional images of a human coronary artery with calcified plaque; (Id)
corresponding H&E histology. Second row: Images of coronary artery with deep calcification,
indicating that OCT lacks the capability to clearly visualize deep calcification. (IIa) OCT, (IIb)
IVUS and (IIc) merged OCT-IVUS cross-sectional images of human coronary artery with a
calcified plaque; (IId) corresponding H&E histology. Third row: Images of necrotic plaque
and fibrous plaque. (IIIa) OCT (IIIb) IVUS and (IIIc) merged OCT-IVUS cross-sectional
images of human coronary artery with necrotic plaque and fibrous plaque; (IIId)
corresponding histology. Arrow: necrotic plaque. Arrow head: fibrous plaque. Top inset:
highly magnified image of the top box region, trichrome stain. Inset image confirms the
existence of fibrous plaque. Bottom inset: highly magnified image of the bottom box region,
CD 68 stain. Inset image confirms the existence of macrophages. Bottom row: Images of FH
swine coronary artery with intimal hyperplasia. Still frame from 35:00 second of movie 1.
(IVa) OCT (IVb) IVUS and (IVc) merged OCT-IVUS of FH swine coronary artery with
intimal hyperplasia; (IVd) corresponding H&E histology. Inset: highly magnified image of
Elastic stain. Scale bar: 1mm. ....................................................................................................... 38
Figure 2-10: (a) IVUS image with a large lipid-rich necrotic core indicated by the “half-moon”
shape. (b) OCT image with a thin fibrous cap indicated by the “star”. (c) Histology image
corresponding to (a) and (b) showing the indicators of TCFA. (d) Longitudinal cross-sectional
pull-back IVUS image with 6.5s pull-back time and 8.125 cm pull-back length. (e) The
corresponding longitudinal cross-sectional pull-back OCT image to (d). (f) IVUS image with
a calcified plaque indicatd by the double star and a region of lipid-deposition indicated by the
arrow. (g) The corresponding OCT to (f). (h) Histology image corresponding to (f) and (g)
showing the complex atherosclerotic coronary artery. (i) and (j): The 3D reconstruction of
IVUS image and OCT image, respectively................................................................................... 42
Figure 2-11: Ultrafast imaging of a rabbit abdominal aorta in vivo. (I) Three-dimensional cut-
away rendering of the volumetric data set acquired with an intravascular catheter in abdominal
aorta of a live rabbit. The volume comprises 288 frames of images acquired in 4 s during the
injection of iohexol at a rate of 3 ml/s. Red, artery wall; semi-transparent white, lipid. Circular
cross-section IVUS (IIa) (IIIa) (IVa) OCT (IIb) (IIIb) (IVb) fused IVUS-OCT (IIc) (IIIc) (IVc)
image pairs and the corresponding H&E histology photos (IId) (IIId) (IVd) at locations 1, 2
and 3 denoted in (I). Arrows point at lipid-rich plaque regions. Scale bar: 0.5mm. The shape
xi

of this artery changed between in vivo imaging and histology due to the reduced intra-lumen
pressure after this artery was harvested. ....................................................................................... 45
Figure 3-1: Flow chart for objective diagnostic criteria of IVUS-OCT. Solid arrow with
rectangular block represent main determinant path, dashed arrow with elliptic block represent
secondary supportive evidence path. By combined use the complementary information of
both IVUS and OCT, three loops diagnostic criteria are formed to characterize calcified (loop
1), fibrous (loop 2) and lipid-rich (loop 3) plaques. ..................................................................... 52
Figure 3-2: Histograms of sensitivity and specificity of imaging-based diagnosis. *Data
statistically different when comparing IVUS-OCT diagnosis to IVUS-only or OCT-only
diagnosis. ...................................................................................................................................... 56
Figure 3-3: Example of deep calcified plaque detection. (A) OCT image: due to limited
imaging depth, a deep calcified plaque (within the elliptic ROI) was misdiagnosed to be
fibrous plaque by OCT-only diagnosis. (B) IVUS image: a calcified plaque were diagnosis
with clear future of bright echo signal followed with acoustic shadow. (C) Histology image
(H&E stain) confirmed a deep calcified plaque. ........................................................................... 58
Figure 3-4: Example of superficial calcified plaque characterization. (A) OCT image: within
the ROI, clear boundary and precise location of a large calcified plaque as well as a small
calcified plaque (pointed by arrow) were characterized by OCT diagnosis. (B) IVUS image:
due to the poor resolution and acoustic shadowing artifacts, the size and shape of the calcified
plaques could not be detail characterized. (C) Histology image (H&E stain) confirmed a large
calcified plaque and a small calcified plaque within the ROI. ..................................................... 59
Figure 3-5: Example of discrepancy between the OCT and IVUS on lipid-rich plaque
diagnosis. (A) OCT image: a lipid rich plaque was detected by OCT as a diffused boarded,
signal-poor regions with overlying signal-rich bands. (B) IVUS image: a false negative case
of same lipid-rich plaque by IVUS-only diagnose to be fibrous plaque. Referenced by OCT
image, a corresponding region of signal-poor characteristic was interpolated to be the
supportive evidence in IVUS-OCT diagnosis. (C) Histology images: Top image (H&E stain)
and bottom image (highly magnified image of CD68 stain). ....................................................... 60
Figure 3-6: Example of a false-negative diagnosis of lipid-rich plaque by OCT-only diagnosis.
(A) OCT image: a lipid-rich plaque was misdiagnosed as fibrous plaque by OCT-only
diagnosis. (B) IVUS image: a region homogenous low echo-density region was shown
(pointed by the arrow), but the lipid-rich plaque still could not be clearly discriminated
without using OCT as a reference. (C) Histology image (CD 68 Stain). ..................................... 61
Figure 3-7: Example of false-negative IVUS-OCT diagnosis of fibrous plaque within overall
intimal thickening. (A) OCT image: ROI was misdiagnosed as lipid-rich plaque by OCT-only,
and IVUS-OCT diagnosis since OCT served as the major diagnostic factor. (B) IVUS image:
whole three-layer structure with overall intimal thickening were visualized by IVUS image.
(C) Histology image (H&E stain). ................................................................................................ 62
Figure 4-1: Illustrations of design schemes of multi-frequency IVUS catheter. (a) Left-and-
right configuration. (b) Fore-and-aft configuration. (c) Back-to-back configuration. .................. 71
xii

Figure 4-2: (a) Diagram of back-to-back multi-frequency IVUS catheter. Middle: 3D drawing.
Left-bottom: sectional drawing. (b) Photograph of a multi-frequency IVUS catheter prototype.
Enlarged photograph: side view (top) and front view (bottom) of catheter tip. ........................... 73
Figure 4-3: Illustration of agar-based tissue mimicking phantom. (a) 3D drawing. (b)
Sectional drawing.......................................................................................................................... 74
Figure 4-4: A diagram of the multi-frequency IVUS imaging system. ........................................ 75
Figure 4-5: Pulse-echo measurement results. Time-domain echo signals and frequency
responses of a representative (a) 35 MHz transducer, (b) 90 MHz transducer, (c) 120 MHz
transducer and (d) 150 MHz transducer. ....................................................................................... 76
Figure 4-6: Tissue mimicking phantom images without presence of blood at (a) 35 MHz, (b)
90 MHz, (c) 120 MHz and (d) 150 MHz. Dynamic Range: 45 dB. Scale bar: 1 mm. ................. 79
Figure 4-7: Fused tissue mimicking phantom images captured by (a) 35/90 MHz multi-
frequency IVUS catheter and (b) 35/120 MHz multi-frequency IVUS catheter. White color:
35 MHz ultrasound image. Orange color: 90 MHz ultrasound image. Green color: 120 MHz
ultrasound image. Dynamic range: 45 dB. Scale bar: 1 mm. ....................................................... 80
Figure 4-8: Tissue mimicking phantom images in presence of blood at (a) 35 MHz, (b) 90
MHz, (c) 120 MHz and (d) 150 MHz. Dynamic Range: 45 dB. Scale bar: 1 mm. ...................... 81
Figure 4-9: IVUS images of human coronary artery at (a) 35 MHz, (b) 90 MHz and (c) 120
MHz. Dynamic Range: 50 dB. Scale bar: 1 mm. .......................................................................... 82
Figure 4-10: Fused IVUS images of human coronary artery captured by (a) 35/90 MHz multi-
frequency IVUS catheter and (b) 35/120 MHz multi-frequency IVUS catheter. White color:
35 MHz IVUS image. Orange color: 90 MHz IVUS image. Green color: 120 MHz IVUS
image. Dynamic range: 50 dB. Scale bar: 1 mm. ......................................................................... 82
Figure 4-11: Summaries of IVUS transducers’ performances at different center frequencies in
this study, including imaging depth, imaging contrast, and imaging resolution. Red dot: OCT.
Dashed blue dot: 1-3 composite IVUS transducer. ....................................................................... 85
Figure 5-1: Principles and schematics of the Raman laser system. (a) The principle of the Ba
(NO3)2 crystals-based Raman Laser. (b) The Schematics of the Raman shifter: M1-M7: 45°
1064 nm reflective mirror; PBS: polarizing beam splitter; HWP: half wave plate; M8:
resonator end mirror; M9: output coupler; M10: silver mirror. (c) The schematics of the MOPA
system: Amp: amplifier; PH: pin hole; QR: quartz rotator; OI: optical isolator; FA: fiber
amplifier; DL: Diode laser; AOM: acousto-optical modulator..................................................... 89
Figure 5-2: (a) Block diagram showing the data acquisition system. FC: fiber coupler; DAQ:
data acquisition. (b) The photograph of the scanning assembly. (c) The explosive view of the
schematic of the rotary joint. ........................................................................................................ 91
xiii

Figure 5-3: Design of coaxial IVPA catheter. (a) Schematic of coaxial IVPA probe. (b)
Photograph of the coaxial IVPA probe. ........................................................................................ 92
Figure 5-4: Design of sequential IVPA catheter. (a) Schematic of sequential IVPA probe. (b)
Photograph of the sequential IVPA probe. ................................................................................... 93
Figure 5-5: High-speed imaging of lipid-mimicking phantom. (a) Photoacoustic image, (b)
ultrasound image, (c) the merged image of PE tube. (d) The photoacoustic spectrum of PE
tube. ............................................................................................................................................... 94
Figure 5-6: High speed PA Imaging of Lipid-laden artery acquired by coaxial catheter. (a) PA
imaging of the artery. (b) US image of the artery. (c) Merged PA & US image. ......................... 95
Figure 5-7: High speed PA Imaging of Lipid-laden artery acquired by a sequential catheter.
(a) PA imaging of the artery. (b) US image of the artery. (c) Merged PA & US image. ............. 96
Figure 6-1: Four critical steps to construct elastography imaging. ............................................. 100
Figure 6-2: Three major ARF excitation method: (a) quasi-static excitation method, (b)
transient excitation method, and (d) harmonic excitation method. ............................................. 105
Figure 6-3: Development of concept of ARF-OCE. ................................................................... 106
Figure 6-4: Schematic diagram of spectral-domain ARF-OCE system. SLD: superluminescent
diode, CCD: charge-coupled device, US: ultrasonic transducer, FG: function generator. ......... 109
Figure 6-5: Displacement at varying frequencies of two silicon phantoms. The resonant
frequency is defined as the frequency where the peak displacement located. ............................ 113
Figure 6-6: Displacement at varying frequencies of two silicon phantoms. The resonant
frequency is defined as the frequency where the peak displacement located. ............................ 114
Figure 6-7: Linear dependency curve of resonant frequencies on varying Young's Moduli of
silicone tissue phantoms. ............................................................................................................ 114
Figure 6-8: (a) Frequency response spectrogram of agar and metal ball. M-mode vibration
phase amplitude was recorded while the targeting point was stimulated by amplitude
modulated acoustic radiation force. The modulation frequency was swept over a range of 50
Hz to 1600 Hz, covering the resonant frequency of both materials. The resonant frequency of
agar and metal ball were 60 Hz and 1080 Hz, respectively. (b) 3D OCE image. (c) The sample
image. The area within the red-dash box was the imaging area. ................................................ 115
Figure 6-9: Frequency response of human coronary artery. (a)OCT morphological image of
the coronary artery segment in the dotted area in (e), (b) (c) resonant-ARF-OCE images
showing frequency response at 500 Hz and 800 Hz. A higher vibration amplitude is measured
on the left and right side of the resonant-ARF-OCE image (b) at 500 Hz, corresponding to the
thin loose fibrous cap. High vibration is detected at 800 Hz at the center of the NCFA (c)
corresponding to a thicker and denser portion of the fibrous cap. (d) and (e) Histological
xiv

sections showing a necrotic core fibroatheroma (NCFA) with a fibrous cap (arrow) overlying
a large necrotic lipid core (NC). (d) Close-up view of the scanned area of plaque (dotted area
in (e)). .......................................................................................................................................... 117
Figure 6-10: (a) Schematic of the confocal ARF-OCE system, including a SD-OCT system
and a customized focused ring transducer (4 MHz) transducer with a 30mm aperture and a
5mm inner hole. .......................................................................................................................... 120
Figure 6-11: Ring transducer design: (a) photograph of the ring transducer with 30mm
diameter and 10mm height and a 5 mm hole, and (b) 2D intensity profile from Field II
simulation. ................................................................................................................................... 121
Figure 6-12: Acoustic output wave (a) and spectrum of the output wave (b) at the focal point.
..................................................................................................................................................... 122
Figure 6-13: Relative acoustic output amplitude (left) and relative pulse intensity integral
(right) along axial direction. The x-axis in this plot is axial direction z = 0 refers to the focal
depth (axial position of 5cm away from the surface of transducer). .......................................... 123
Figure 6-14: Acoustic output amplitude (left) and relative pulse intensity integral (right) along
lateral direction at different axial position (z=2cm, z=3cm, z=4cm, z=5cm and z=6cm). ......... 123
Figure 6-15: Scanning area validation on a homogeneous silicone phantom with 1.5 mm
lateral scan. (a) OCT intensity image and (b) phase map induced by 800 Hz ARF excitation
on the phantom. ........................................................................................................................... 125
Figure 6-16: Axial displacements of silicone phantoms with different stiffness. R: ratio of the
silicone to the related activator. .................................................................................................. 126
Figure 6-17: 2D and 3D ARF-OCE (a~b) and the sample image of agar phantom (c) with a
stainless steel sphere embedded inside stimulated at a fixed frequency of 1050 Hz. The surface
of the metal ball shows distinctive vibration amplitude due to its resonance. The agar phantom,
however, vibrates much less since the driving frequency is far away from its resonant
frequency..................................................................................................................................... 127
Figure 6-18: (a) 3D OCT image (b) 3D ARF-OCE phase image of a human cadaver coronary
artery (c) fused OCT and ARF-OCE images (d) 2D OCT (e) 2D ARF-OCE (f) sample image
(g) the histological image (h) the close up view of the atherosclerotic lesion. FC: fibrous cap.
NC: necrotic core. ....................................................................................................................... 129
Figure 6-19: (a) Schematic diagram and photography of dual-ring transducer. A center hole
is available for OCT beam delivery. (b) Illustration of beat pattern generation. The two
elements of the transducer are driven with frequencies with a Δω difference and are focused
at the same location on the sample(Fatemi and Greenleaf 1998). (c) Modified ARF-OCE
imaging system set-up................................................................................................................. 131
Figure 6-20: (a-c) Lateral beam profile of inner ring transducer. (d-f) Lateral beam profile of
outer ring transducer. (g) Axial beam profile of inner ring and outer ring transducer. ............. 132
xv

Figure 6-21: Comparison of displacement of tissue when using single ring vs. dual ring
excitation. Resonance frequency of phantom is 2000Hz. ........................................................... 134
Figure 6-22: OCE image using dual ring vibro-acoustography approach showing
displacement shift of dual-layered silicone phantom at resonance frequency excitation of
2000Hz. Red box represents focal zone. ..................................................................................... 135
Figure 7-1: (a) Schematic of experimental setup. (b) Photograph of arrangement of ultrasonic
transducers. ................................................................................................................................. 142
Figure 7-2: Geometry and composition illustration of (a) left-and-right phantom, (b) up-and-
down phantom, and (c) inclusion phantom. ................................................................................ 143
Figure 7-3: (a) 2D beam profile of 4 MHz ring transducer at focal plane without needle
transducer insertion. (b) 2D beam profile of 4 MHz ring transducer at focal plane with needle
transducer insertion. (c) 2D pressure profile of 40 MHz needle transducer. (d) 1D beam profile
along the axial direction of 40 MHz needle transducer, and the 1D beam profile along the
axial direction of 4 MHz ring transducer with and without needle transducer insertion. ........... 144
Figure 7-4: Illustration of confocal alignment procedures of transducers and the FOV
determination HMI system. (a) Excitation zone of ring transducer. (b) Detection zone of
needle transducer. (c). FOV of HMI system: the overlapped region of excitation zone and
detection zone. ............................................................................................................................ 146
Figure 7-5: (a) Dynamic displacement curves within 20 ms imaging window of 0.5% agar
phantom and 1.5% agar phantom at the axial depth of 1.7, 2.1, 2.5 and 2.9 mm. (b) Average
amplitudes of harmonic motion of the 0.5% agar phantom and 1.5% agar phantom along the
axial direction.............................................................................................................................. 147
Figure 7-6: B-mode image (a) and its corresponding high resolution HMI image (b) of left-
and-right phantom. B-mode image (c) and its corresponding high resolution HMI image (d)
of up-and-down phantom. B-mode image (e) and its corresponding high resolution HMI
image (f) of left-and-right phantom. The red dashed lines in the B-mode image represent the
boundary estimated from the corresponding HMI image. S: soft 0.5%-agar phantom, H: hard
1.5%-agar phantom. .................................................................................................................... 149
Figure 7-7: (a) Displacement curves of left-and-right along the lateral direction at the axial
location of 2.8, 2.31, 2.54, 2.77 and 3.00 mm. (b) Displacement curves of up-and-down
phantom along the axial direction at the axial location of 0.75, 1.75, 2.00, 2.75 and 3.50 mm.
(c) Averaged displacement curves of left-and-right along the lateral direction with fitting
curve. (d) Averaged displacement curves of up-and-down phantom along the axial direction
with fitting curve. ........................................................................................................................ 150
Figure 7-8: B-mode image (a) and its corresponding high resolution HMI image of a section
of human atherosclerosis coronary artery. I: intima layer, M: media layer, A: adventitia layer
and surrounding tissue, C: calcified plaque. ............................................................................... 152
xvi

Figure 8-1: (a) Schematic of the tri-modalities integrated system and the probe. OCT and
fluorescence systems were combined with a wavelength division multiplexer. Ultrasound
signal was synchronized with optical signal by the trigger from swept source laser. (b)
Structure of the tri-modality endoscopic probe: the optical probe and ultrasound transducer
were placed side-by-side. (c) Photograph of the tri-modality catheter. The rigid portion of the
probe is 7 mm and the diameter is 1.2 mm. The scale is in centimeters. Ex vivo images from
human coronary artery (d) combined OCT and fluorescence image, (e) combined ultrasound
and fluorescence image, and (f) combined tri-modality image. Adapted from Liang et al
(Liang, Ma et al. 2014). .............................................................................................................. 160
Figure 8-2: (a) Integrated IVUS/OCT/ARF-OCE probe with coaxial arrangement design.
Inserted image: different view showing the mirror at the tip of the probe. GRIN lens: gradient-
index lens. US: ultrasonic transducer. (b) First prototype of ring transducer for intravascular
ARF-OCE probe. ........................................................................................................................ 164
Figure 8-3: (a) Schematic of dual-element IV-ARFI transducer. (b) Photo of the dual-element
IV-ARFI transducer prototype. (c) Pulse-echo results of ring shape excitation transducer (8.5
MHz). (d) Pulse-echo results of square detection transducer (35 MHz). (e) B-mode Image of
side-by-side gelatin phantom (50dB dynamic range, estimated Young’s Modulus: left-13kPa,
right-45kPa). (f) ARFI image of side-by-side gelatin phantom (unit: µm). ............................... 165

xvii

Abstract
Thin-capped fibroatheroma (TCFA) is considered to be the phenotype of vulnerable
atherosclerotic plaque based on the pathological studies, whose sudden rupture is frequently
responsible for acute coronary syndrome (ACS). Early detection and prognosis of TCFA will not
only guide the therapeutic strategy to benefit the patients, but also contribute to the study of natural
history of vulnerable plaque that is still elusive. To date, various imaging modalities employing
ultrasonic scattering contrast with radio frequency analysis, optical scattering contrast, optical
absorption mechanism, spectroscopic analysis and targeted-molecular imaging method, provide
diverse visualizations of coronary arteries both in clinic and research. However, none of these
imaging modalities has been symmetrically validated to precisely detect TCFA in vivo, since any
single imaging modality exhibit natural limitations when characterizing the elusive TCFA.
Therefore, integration of theses imaging modalities into a single catheter is hypothesized to be the
optimal method to enable the early detection of TCFA by combing best features of these techniques
while compensating their respective weakness.
In this thesis, several multi-modality intravascular imaging systems by combined use of
ultrasonic and optical techniques were developed in three aspects to access the morphological
information, functional components, and elasticity of coronary arteries. Aim to fully obtain the
morphological information real time in vivo, an ultra-high speed integrated intravascular
ultrasound (IVUS) and optical coherence tomography (OCT) system has been optimized and
prototyped. Statistical validation study and IVUS-OCT diagnostic criteria development has
demonstrated that the integrated IVUS-OCT system has an overall higher diagnostic accuracy of
atherosclerotic plaques, especially for lipid-rich plaques. From the cost-effective perspectives, a
multi-frequency IVUS imaging system was developed to improve the trade-off between resolution
xviii

and depth of penetration of IVUS. Aiming to measure the thin fibrous cap, an ultra-high frequency
IVUS transducer was incorporated into the conventional IVUS catheter to provide higher special
resolution image of the coronary artery, which makes the multi-frequency IVUS imaging system
an alternative of integrated IVUS-OCT system. Moreover, the development of a high speed
integrated IVUS and intravascular photoacoustic (IVPA) system make it possible to quantify a key
parameter of diagnosing TCFA-- the size of lipid deposition inside coronary artery. In vitro
imaging of lipid-laden artery was performed by using current IVUS-IVPA system with 2 orders
of magnitude improvement of imaging speed, which bridged the gap of translating the IVUS-IVPA
technology to clinical study. In order to characterized the biomechanical properties of plaque
components, acoustic radiation force (ARF) optical coherence elastography (OCE) is further
developed featured by the confocal alignment of OCT detection region with acoustic excitation
field. Based on the concept of mechanical resonant frequency of tissue in response to external
force, the development of resonant OCE system adds an additional contrast to the current ARF-
OCE system by sweeping the acoustic excitation frequency. Finally, an ultrasonic-only high
resolution elastography technique harmonic motion imaging (HMI) was developed to provide
microstructural level mechanical property characterization by using low frequency excitation and
high frequency detection method. This research have supported the hypothesis that multi-
modality intravascular imaging by using ultrasonic and optical techniques serves as a reliable
method to facilitate the early diagnosis of vulnerable atherosclerotic plaque and enhance the study
of natural history of vulnerable plaque.
xix

Chapter 1 Introduction
1.1 Clinical Background
The heart muscle needs oxygen-rich blood to ensure the perpetual transportation of blood
within circulatory system to tissues of other parts in the body, and oxygen-depleted blood must be
carried away (Haeger 1959). The coronary arteries are the vessels that deliver oxygen-rich blood
to the heart muscle (myocardium). The coronary arteries run along the outer surface of the heart
and have small branches dive into the heart muscle. The represented human coronary artery
anatomy is shown in Figure 1-1. Left and right coronary arteries are the two main coronary arteries
originating from the beginning of the aorta. The left coronary artery is branched off into the left
anterior descending artery and circumflex artery to supply blood to left ventricle and left atrium.
The right coronary artery divides into the right posterior descending and acute marginal arteries,
and delivers blood to the right ventricle, right atrium, sinoatrial node, and atrioventricular node to
regulate the heart rhythm.
Coronary artery disease (CAD), or ischemic heart disease (IHD), is the most common type
of heart disease that has serious implication due to the reduction of the flow of oxygen and nutrients
to heart muscle, and thus leads to symptom of sudden heart attack or even final arises. It is a
common term that plaques are built up in the arteries, which causes narrowing and blockage of
coronary arteries. Each year, more than 20 million patients worldwide with CAD experience acute
coronary syndrome (ACS), and 34% of these individuals die from CAD complications (Roger, Go
et al. 2012).

1

Figure 1-1: Anatomy of human coronary arteries. (Adapted from Patrick J. Lynch, medical
illustrator, http://commons.wikimedia.org/wiki/File%3ACoronary_arteries.png)

1.1.1 Atherosclerosis
Atherosclerosis is characterized by the thickening of arterial vessel wall due to building up
of athermanous plaque on inner lining of arteries. Formation of atherosclerosis is illustrated in
Figure 1-2. A normal artery is composed of three layers: intima, media and adventitia (Figure
1-2(a)). As a fatty streak develops inside the intima (Figure 1-2(b)), thin fibrous plaque with a fatty
core will be formed gradually (Figure 1-2(c)). The fibrous plaque can be vulnerable to rupture if
it contains thin caps (Figure 1-2(d)). Consequently, the rupture causes narrowing or even
occlusion of entire arterial lumen (Figure 1-2(e), (Ross 1999).

2

Figure 1-2: The formation of Atherosclerosis. (Adapted from www.medmovie.com)

Percutaneous Coronary Intervention (PCI), also known as coronary angioplasty, is a non-
surgical procedure to treat blockage of coronary arteries cause by atherosclerosis. During PCI
(detailed description is shown in Figure 1-3 ), interventional cardiologists insert a balloon catheter
from femoral or radial artery to the narrowed site of coronary artery under guidance of X-ray. The
balloon is then inflated to stretch the plaque tissue and open up the artery lumen to improve blood
flow. A stent may be inserted at this moment to open the coronary artery permanently. The catheter
is removed at last. There are two major types of coronary stents, bare-metal stent (BMS) and drug-
eluting stent (DES). The DES, designed in 1990s, is coated with special drugs to present the
restenosis and reduce the need for repeat interventions. The newly developed bio-absorbable DES
would overcome the predisposition to late stent thrombosis of regular DES.
3

Figure 1-3: Procedures of Percutaneous Coronary Intervention (PCI): coronary artery stenting
(adapted from http://www.summitmedicalgroup.com/library/adult_care/pci_tx/).

1.1.2 Thin-cap Fibroatheroma (TCFA)
The sudden rupture of vulnerable atherosclerotic plaque is widely recognized to be main
mechanism underlying ACS (Finn, Nakano et al. 2010, Moreno 2010). Although the understanding
4

of vulnerable plaques remains to be elucidated, histological studies have demonstrated that thin-
cap fibroatheroma (TCFA) is the most common phenotype of vulnerable plaques (shown in Fig.1).
TCFA is composed of a lipid-rich necrotic core with an overlying thin-cap rich in macrophages
(white blood cells that attack foreign substances) (Libby 1995). Quantitatively, TCFA is further
defined as an atherosclerotic plaque with a fibrous cap < 65 μm in thickness associated with
macrophage infiltration (>25 cells per 0.3 mm diameter field) and a large lipid-rich necrotic core
occupying nearly 35% of plaque volume (Virmani, Burke et al. 2003). Therefore, both the
thickness of TCFA and the size of the lipid-rich necrotic core are considered to be the major
predictors of ACS. As a corollary, the presence of the inflammatory molecules and cells, such as
increased macrophages, are useful in both identifying and staging the vulnerable plaques.
Additional markers of TCFA are micro-calcifications and proliferation of the vasa vasorum
(vessels that supply the walls of large arteries). To precisely identify intravascular TCFA in vivo,
the imaging techniques employed must recognize key morphological structures as well as
biological features of the TCFA. Thus, early detection and staging of TCFA will not only guide
the interventional or pharmacological strategy to prevent plaque rupture, but also contribute to the
study of epidemiology of vulnerable plaques.
5

Figure 1-4: (a) Schematic drawing of the morphologic features of a TCFA (Stolzmann,
Subramanian et al. 2011). (b) Histology image of TCFA (NC: necrotic core, Arrow: thin fibrous
cap) (Tavora, Cresswell et al. 2010).

1.2 Intravascular Imaging Techniques
An optimal intravascular imaging technology for plaque characterization, especially for the
identification of vulnerable plaque with TCFA, should meet the following requirements: (1)
visualizing the endoluminal structure in details and scaling the degree of stenosis; (2) quantifying
the entire plaque volume and plaque burden; (3) identifying plaque components such as
calcification, lipid-rich necrotic core, fibrous tissue and inflammatory markers; (4) providing
adequate spatial resolution to measure the thickness of thin fibrous cap; (5) monitor plaque rupture
and thrombus formation. Each intravascular imaging technology possesses unique features that
yield valuable information while exhibiting inherent limitations that can be difficult to overcome;
therefore, an integration of multiple imaging modalities seems a synergistic solution (Garcia-
6

Garcia, Gonzalo et al. 2008, Honda and Fitzgerald 2008, Maehara, Mintz et al. 2009, Puri,
Worthley et al. 2011, Bourantas, Garcia-Garcia et al. 2013, Bourantas and Serruys 2014).
1.2.1 Intravascular Ultrasound (IVUS)
Ultrasound is the sound with frequency higher than the upper limit of human hearing range
(~20 kHz). It is a compressional wave that can only propagate inside a medium. Sound velocity in
water is approximately 1484 m/s. It’s much lower than the speed of electromagnetic wave, which
allows pulse-echo recording by measuring time-of-flight for ultrasound imaging. The contrast
mechanism in ultrasound imaging is based on acoustic impedance variation between different
materials. When the transmitting ultrasonic waves hit an interface of two media, where acoustic
impedances of the two media mismatch, portion of the ultrasonic waves will be bounced back and
received by the same transducer. The rest of ultrasonic waves continue propagate until hit other
interfaces. The position of each interface can be timely resolved by recording corresponding time
delay of echo signals. The echo signals received along one transmitting/receiving route is named
one A-line. The ultrasonic transducer is mechanically scanned linearly or rotationally to form a 2-
D image by incorporating multiple A-lines. The echo signal amplitude is converted to gray scale
which is the representation of the brightness in the image.
In IVUS imaging, a single element transducer is rotated 360˚ to scan cross section of vessel
wall and form a radial format image. The IVUS imaging processing steps are illustrated in Figure
1-5. First, the raw radiofrequency (RF) data is digitally filtered within the effective bandwidth to
remove unwanted noises that are out of the bandwidth. After filtering, envelop detection and
logarithm compression are applied on the RF data. The compressed data is then digitally converted
into radial format for display. Multiple averaging methods could be applied to the RF data or
7

compressed data to reduce background noise level. However, in the case that require high frame
rate, less A-lines are acquired, thus averaging may not be feasible.

Figure 1-5: Imaging processing procedures of IVUS.

High-frequency ultrasound generally refers to ultrasound with frequency higher than 10
MHz. Spatial resolutions of an image are determined by working frequency both in lateral (Rlateral)
and axial (Raxial) directions (equations 1-1 and 1-2).

𝑅𝑅 𝑙𝑙𝑙𝑙𝑙𝑙 𝑙𝑙 𝑙𝑙 𝑙𝑙𝑙𝑙
=
𝐶𝐶 𝑓𝑓 0
∙ 𝐹𝐹 #
(Equation 1-1)
𝑅𝑅 𝑙𝑙 𝑎𝑎𝑎𝑎 𝑙𝑙𝑙𝑙
=
𝐶𝐶 2 ∙ 𝐵𝐵𝐵𝐵
− 6 𝑑𝑑𝑑𝑑
(Equation 1-2)

where 𝑐𝑐 is the sound velocity, 𝑓𝑓 0
is the operational center frequency of transducer, f-number ( 𝐹𝐹 #
)
is the ratio of focal distance to aperture diameter of transducer, and 𝐵𝐵𝐵𝐵
− 6𝑑𝑑 𝐵𝐵 represents the -6 dB
fractional bandwidth of a transducer. It is obvious that both axial and lateral resolutions can be
improved by increasing center frequency. Transducer can be focused either by attaching an
acoustic lens or by deforming transducer aperture into curved shape by ball bearing hot pressing
(Cannata, Ritter et al. 2003). For an unfocused single element transducer with flat aperture, the
8

focal distance can be considered equal to the near field size, or the natural focus, which is described
as below in equation 1-3,

𝐹𝐹 0
=
𝑙𝑙 2
𝜆𝜆
(Equation 1-3)

where 𝐹𝐹 0
is the natural focus, 𝑎𝑎 is the radius of the transducer aperture, 𝜆𝜆 is the wavelength at the
transducer’s center frequency. Acoustic beam width is around 𝑎𝑎 to 2 𝑎𝑎 within natural focusing
zone and it starts to diverge beyond the zone.
The most critical component of designing an ultrasonic transducer is the selection of the
piezoelectric material that converts the acoustic energy to an electrical signal. Possessing good
piezoelectric properties, Pb(Zr,Ti)O3 or PZT is the most popular polycrystalline ferroelectric
ceramic material for fabricating ultrasonic transducers, especially for IVUS application (Haertling
1999, Cheung, Zhou et al. 2011). Besides polycrystalline ceramics, single crystals, such as LiNbO3
(Cannata, Ritter et al. 2003, Lam, Hsu et al. 2013) and Pb(Mg1/3Nb2/3)O3-PbTiO3 (PMN-PT) (Lau,
Lam et al. 2004, Zhou, Xu et al. 2007, Lam, Chen et al. 2012) are also used for ultrasonic
transducers due to their outstanding dielectric and electromechanical properties. Different from
the polycrystalline ceramics, single crystals do not suffer from grain size and porosity issues when
fabricating very thin piezoelectric layers, thus are more desirable for high frequency transducers
without scaling limitations (Park and Shrout 1997). Both LiNbO3 and PMN-PT have satisfactory
electromechanical coupling coefficient kt (e.g., LiNbO3 ~ 0.39, PMN-PT ~ 0.58), which is
favorable for high sensitivity transducers. However, PMN-PT exhibits a much higher clamped
dielectric permittivity ε
s
/ε0

than LiNbO3 (e.g., LiNbO3 ~ 39, PMN-PT ~ 800), which is selected for
9

designing smaller aperture transducers. Requiring a small aperture and high sensitivity, currently
PMN-PT should be the first choice for IVUS imaging system.
In this thesis, most of the IVUS transducers that have been designed and fabricated is made
of PMN-PT single crystal with a center frequency ranging from 30-50 MHz. The design
parameters of a 45 MHz side-looking IVUS transducer based on the PiezoCAD (Sonic Concepts,
Inc. Bothell, WA) simulation were summarized in Table 1-1. The transducer has an aperture size
of 0.4 mm in square shape.

Table 1-1: Design Parameters of a 45 MHz PMN-PT IVUS transducer.
Material Thickness
Piezoelectric layer PMN-PT 42 µm
1
st
matching layer 2-3 µm Silver epoxy 10 µm
2
nd
matching layer Parylene 10 µm
Backing layer E-Solder 3022 0.3 mm

The general fabrication process flow of 40 MHz side-viewing miniaturized IVUS
transducers is illustrated in Figure 1-6, which has been described by Cannata et al previously
(Cannata, Ritter et al. 2003). A first matching layer was laid over to the negative electrode (front
site) of PMN-PT material to facilitate the efficient acoustic energy transfer between the PMN-PT
element with high acoustic impedance and the water medium. The matching layer had a thickness
of λ/4 (λ is the wavelength in the material of the matching layer) and was made of a mixture of
three parts 2-3 μm silver particles (Adrich Chem. Co., Milwaukee, WI) and 1.25 parts Insulcast
501 epoxy (American Safety Technologies, Roseland, NJ). A conductive backing material (E-
SOLDER 3022, Von Roll Isola Inc., New Haven, CT) was cured separately over the back of the
10

PMN-PT element to damp the energy radiation from the back site of the element and provide
structural support. Before assembling the functional element into the steel needle housing, an
electrical connector was fixed into the backing material. Finally, parylene was vapor deposited on
the whole transducer as a second matching layer and protective coating. To enhance the
piezoelectric activity of the PMN-PT single crystal, the finished transducer was poled in a DC
electric field of 20 KV/cm for 5 minutes under room temperature. The prototype needle IVUS
transducer is shown in Figure 1-7 (a). Another flexible version is fabricated with 1.5 m long double
wound flexible torque coil with an outer diameter of 0.65 mm, as shown in Figure 1-7 (b). The
torque coil allows for smooth torque translation to the distal end throughout the whole catheter.

Figure 1-6: Fabrication process flow of 45 MHz side-viewing miniaturized IVUS transducers.

11

Figure 1-7: Prototype IVUS transducers: needle type (a); and flexible type (b).

Catheter-based intravascular ultrasound (IVUS) has been used clinically for over the last
two decades to image coronary arteries for atherosclerotic lesions, to evaluate the lumen and
plaque dimensions, and to guide intervention and stent deployment. The mechanically scanning
IVUS transducer (20~40 MHz) or the radial array transducer (10~20 MHz), utilizing the theory of
echogenicity of high frequency ultrasonic waves, are capable of providing detailed cross-sectional
visualization of coronary artery wall with 70-200 μm axial resolution, 200-400 μm lateral
resolution, and 5-10 mm imaging depth (Elliott and Thrush 1996, Brezinski, Tearney et al. 1997).
In the late 1990s, Bernard Sigel et al. first demonstrated the feasibility of using ultrasonic spectrum
analysis to characterize vulnerable plaques of carotid arteries (Noritomi, Sigel et al. 1997,
Noritomi, Sigel et al. 1997, Lee, Sigel et al. 1998). Later on, the newly developed radiofrequency
backscatter spectrum analysis algorithm was implemented in two commercial intracoronary artery
imaging systems: Virtual Histology (VH-IVUS, Volcano Therapeutics, CA, USA) and iMap
12

(Boston Scientific, CA, USA) (Nair, Kuban et al. 2002, Nasu, Tsuchikane et al. 2006, Nair,
Margolis et al. 2007, Shin, Garcia-Garcia et al. 2011). The IVUS-based elastography technique,
intravascular palpography, is able to assess local mechanical properties during arterial deformation
caused by the intraluminal pressure, which can be used to perform high-risk plaque assessment
(Schaar, de Korte et al. 2003, Schaar, van der Steen et al. 2006, Deleaval, Bouvier et al. 2013).
However, based on clinical studies in patients with ACS, the reliability of using ultrasonic
spectrum analysis and intravascular palpography to detect vulnerable plaque was subpar
(Brugaletta, Garcia-Garcia et al. 2012). This was caused by the insufficient resolution of IVUS to
reliably characterize different tissue types and to precisely detect TCFA at such small scales.
Nevertheless, IVUS remains an important tool for assessing plaque burden and monitoring artery
remodeling (Maresca, Adams et al. 2014).
1.2.2 Intravascular Optical Coherence Tomography (IV-OCT)
Optical coherence tomography (OCT), considered as the optical analogue of ultrasound,
utilizes back-scattered infrared light to achieve high spatial resolution (10-30 μm) and high-speed
microstructural coronary artery images (>100 frames per second, 20-40 mm/s pull back speed)
(Brezinski, Tearney et al. 1996, Regar, Schaar et al. 2003). Due to the improved localization of
back-scattered light, OCT offers significant higher spatial resolution (10~30 μm), and higher speed
cross-sectional real-time imaging than ultrasound (Huang, Swanson et al. 1991, Patwari,
Weissman et al. 2000). However, similar to other optical imaging techniques, the imaging depth
of OCT is limited to only 0.5 mm to 1.5 mm range. OCT is based on a Michelson interferometer
and can be implemented in either a time-domain OCT (TD-OCT) or a spectral domain OCT (FD-
OCT) configuration, where collimated beam from a light source is split into a reference and a
13

sample arm. In TD-OCT, the interference of the light beam from the reference arm and sample
arm is measured by using autocorrelation method with a single photoreceiver, and depth imaging
capability is achieved by mechanically scanning the reference arm. Instead of sweeping the
reference reflector, FD-OCT calculates the autocorrelation based on the Fourier transform of
power spectral signal acquired by the high-speed camera to achieve higher speed and higher signal-
to-noise ratio image quality compared with TD-OCT system (Prati, Regar et al. 2010, Prati,
Guagliumi et al. 2012). Similar to the IVUS, the catheter-based intravascular OCT probe
generated a broad bandwidth infrared light, that is then irradiated into the tissue at different angular
positions. 2D cross-sectional image can then be reconstructed based on the echo time delay and
the intensity of the detected optical echo from tissue. 3D volumetric data can be acquired by
mechanically pulling back the entire catheter during rotational scan. In 2004, Light Lab (Light
Lab Imaging, USA), acquired by St Jude Medical Inc recently, was the first company to
commercialize catheter-based intravascular TDOCT imaging system (Prati, Regar et al. 2010). In
2011, the intravascular FDOCT system together with single mode optical fiber catheter
(Dragonfly
TM
; St Jude Medical, USA) was approved by FDA with the advantages of higher frame
rate (100 fps), improved axial resolution (lateral resolution remained the same), and reduced
motion artifacts, which bring this non-occlusive into clinical practice by reducing procedural time
and increased safety (Prati, Guagliumi et al. 2012).
Under rapid development in scientific research and proliferation in medical device industry,
intravascular OCT has gained wide recognition in clinical practice and has become the top
contender to challenge the status of IVUS in the intravascular imaging field. However, OCT has
several limitations: imaging limitation in penetration depth (1-2 mm), requiring temporal clearance
14

of luminal blood during the imaging procedure, and lacking the reliability of tissue characterization
as compared to IVUS.
1.2.3 Intravascular Photoacoustic (IVPA)
The photoacoustic (PA) effect, first discovered by Alexander Graham Bell in 1880, is the
formation of acoustic waves following light absorption in sample. The primary mechanism of PA
effect, illustrated in Figure 1-8, is called photo-thermal effect. When the sample is illuminated with
pulsed or periodical light, it absorbs the energy from light. The absorbed energy converts into
localized temporal temperature rise which results in volume expansion. Due to thermal expansion,
the pressure rise during heating generates a broadband acoustic waves propagating to the
surrounding medium. The acoustic waves can be detected by an ultrasonic transducer and then
used to form images. Photoacoustic imaging can provide both deep ultrasonic penetration depth
and high optical contrast due to optical absorption(Wang and Hu 2012).

Figure 1-8: Illustration of photoacoustic effect.
15

The principle of IVPA is based on the detection of acoustic waves generated by vascular
tissue components when irradiated by a pulsed laser light at the tip of the IVPA catheter. The
unique optical absorption of different tissues when excited at a specific wavelength opens a new
frontier for atherosclerotic plaque characterization. However, contrast based on electronic
absorption, as in case of hemoglobin, can hardly be applied for intravascular imaging due to the
lack of tissue specificity inside the arterial wall (Yang, Favazza et al. 2012). Lipid components
within coronary arteries have a distinct absorption spectrum in the near infrared wavelength range;
specifically, several groups have demonstrated that the enhanced overtone absorption of C-H
bounds excited at the wavelength range of 1.2 and 1.7 µm can be used for imaging and mapping
lipids in an atherosclerotic plaque(Wang, Su et al. 2010, Jansen, van der Steen et al. 2011, Wang,
Karpiouk et al. 2012, Wang, Wang et al. 2012). Moreover, spectroscopic IVPA imaging was also
investigated as a tool for providing additional information to further differentiate lipid components
of atherosclerotic plaques (Sethuraman, Amirian et al. 2008, Jansen, van der Steen et al. 2014,
Jansen, Wu et al. 2014). The beauty of IVPA is that it not only quantifies the size of lipid
components, a key indicator of vulnerable plaque, but also automatically incorporates the IVUS
image to clarify ambiguity such as photoacoustic signals generated by calcification (Jansen, van
der Steen et al. 2014). Since IVPA originated from the combination of optical illumination and
ultrasonic detection, the quality of laser source and ultrasonic transducers are the two key
determining factors for this new promising technology.
There is a formidable barrier that blocks the transition of IVPA system from bench top to
bedside - the slow imaging speed. The current IVPA system employed a Nd:YAG-pumped optical
parametric oscillator (OPO) system with 10 Hz repetition rate to generate the excitation at 1.7 µm
and 1.2 µm wavelength for lipid visualization (Jansen, van der Steen et al. 2011, Wang, Karpiouk
16

et al. 2012, Bai, Gong et al. 2014). This laser repetition rate translates to a cross-sectional imaging
speed of 50fps if 500 a-lines per image is acquired. Such speed is hardly applicable for future
clinical application, in which real-time frame rate is usually required. Therefore, to break the
barrier of development of high-speed IVPA system, a nanosecond laser source with few kilo Hertz
which can still provide optimal wavelengths at 1.2 or 1.7 μm for lipid imaging is demanded. The
additional challenge in choosing the laser system for IVPA is to obtain an optimal laser pulse
duration. The optimal frequency responds of small transducers used in IVPA is in tens of MHz
range. The tissue acoustic frequency depends on optical pulse duration, therefore the control over
pulse duration is important for overall IVPA performance. Unfortunately, most of commercially
available kHz-rate pump lasers are Q-switch lasers with fixed pulse duration.
Meanwhile, the safety of IVPA will garner increased attention as advancement in IVPA
imaging speed matches that of current commercial IVUS systems. To alleviate concerns over the
safety of IVPA systems, modifications of the hybrid IVUS-IVPA catheter are required to increase
the sensitivity of ultrasonic transducer and to improve the overlap of optical illumination and
ultrasonic detection pathways in order to reduce the optical illumination power. Most commonly
used miniature IVPA catheter designs have either a lateral or a longitudinal offset between the
optical illumination path and the ultrasonic detection path. This not only creates inaccuracy in the
IVUS-IVPA images co-registration, but also limits the FOV of IVPA along the axial direction
(Wang, Su et al. 2010, Jansen, van der Steen et al. 2011, Wei, Li et al. 2011). An alternative is a
confocal IVUS-IVPA catheter by using a miniaturized ring-shaped transducer in the high-speed
IVPA system to enable an enlarged FOV with increased sensitivity. Other innovations on the
horizon to further miniaturize the size of ring-shaped transducers are to switch to high-performance
17

piezoelectric material for ultrasonic transducer fabrication, using laser dicing method and focused
light illumination.
1.2.4 Other Intravascular Imaging Techniques
Recently, using molecular specificity for tissue characterization has further increased the
feasibility of assessing the metabolic state of vulnerable plaques. Different tissue compositions
have different optical absorption and scattering effect on near-infrared (NIR) light (400 to 2400
nm). Near-infrared spectroscopic (NIRS) is the first intravascular imaging technique to achieve
lipid content characterization within plaques by analyzing absorbance of emitted NIR light at
different wavelengths (Moreno, Lodder et al. 2002, Waxman, Dixon et al. 2009). NIRS has been
validated for its capability to characterize the lipid composition of plaque by analyzing the spectral
response from the scattering and absorption of near infrared light by the cholesterol (Waxman,
Dixon et al. 2009). The TVC Imaging System (InfraReDx, Burlington, MA, USA) is the first
commercial multimodal intravascular imaging system to fully assemble an IVUS transducer and
an optical NIRS fiber into a single catheter to provide simultaneously co-registered IVUS-NIRS
image (Fig.5). In this way, the presence of the lipid content from the chemogram of NIRS image
can be mapped on to the coronary artery structural information captured by the IVUS transducer,
allowing for a more accurate detection of vulnerable plaque. The integrated IVUS and NIRS
system has been evaluated in over 90 hospitals across 10 countries, and extensive clinical data and
case reports have validated its ability to identify lipid core plaque with improved accuracy(Schultz,
Serruys et al. 2010, Goldstein, Maini et al. 2011, Madder, Steinberg et al. 2013, Brugaletta and
Sabate 2014, Dohi, Maehara et al. 2014). However, the integrated IVUS-NIRS system also has
several limitations: the NIRS can only display the lipid distribution along the lateral or transversal
18

direction, which has poor resolution, and it does not contain axial resolution to determine the
location and to quantify the size of the lipid-rich core. Moreover, it is still uncertain that if the
penetration depth of NIRS is able to cover the entire field-of-view (FOV) of an IVUS image,
especially to predict the lipid presence at a location relatively further away from the catheter tip.
Therefore, to determine the treatment strategy for patients diagnosed with vulnerable plaques by
the integrated IVUS-NIRS system, a prospective multi-center observational study of patients
undergoing NIRS via TVC imaging system (COLOR Registry) is needed(Brugaletta and Sabate
2014).
Other emerging optical imaging techniques such as near-infrared fluorescence (NIRF)
imaging (Yoo, Kim et al. 2011), Raman spectroscopy (Buschman, Marple et al. 2000, van de Poll,
Romer et al. 2002), and fluorescence spectroscopic imaging (Stephens, Park et al. 2009, Sun,
Chaudhari et al. 2011) are advancing the field of catheter-based technology by providing the
contrast that involves molecular specificity, which can be used to identify tissue composition.
However, these optical image techniques lack the capability to perform cross-sectional mapping
for tissue structure; thus, IVUS and OCT remain essential.

19

Figure 1-9: (a) Photograph of integrated IVUS-NIRS imaging system (TVC imaging systemTM,
Infraredx, Inc) including a TVC Imaging SystemTM console, a TVC NexusTM Controller, and a
TVC InsightTM Catheter. (b) Multi-modality TVC Insight Catheter core assembly. (c) TVC
Composite™ View of co-registered near infrared spectroscopy lipid core plaque with intravascular
ultrasound. (d) chemogram of the near-infrared spectroscopic (NIRS) image. The yellow-red
color-coded map illustrates the probability of the presence of a lipid core (yellow corresponds to
high probability and red to low probability). (e) Co-registration of IVUS and NIRS data. Adapted
from website of Infraredx, Inc (http://www.infraredx.com/).

1.3 Scopes of the Dissertation
In this dissertation, several multi-modality intravascular imaging systems were developed
to acquire morphological information, functional components, and elasticity of the coronary
20

arteries. The objective of this research is not only to provide clinical benefits by early diagnosis
and assessment of vulnerable plaques, but also to contribute to the development of the natural
history of atherosclerosis. This research is composed of three major parts, including (1) the
optimization of IVUS-OCT system and development of multi-frequency IVUS system for
coronary structural imaging, (2) the improvement of IVUS-IVPA for in vivo studies, and (3) the
validation of ARF-OCE system and high-resolution ultrasonic elastography for catheter-based
intravascular studies. They represent the three targeting aspects to improve the characterization of
atherosclerotic plaques respectively.
In chapter 2, the technical details of the integrated IVUS-OCT system are symmetrically
reported to fulfill the clinical requirements for intravascular imaging studies. The miniaturized
hybrid IVUS-OCT catheter design is optimized and featured with the back-to-back arrangement
of the IVUS transducer and the OCT ball lens, which facilitate the real-time online fusion function.
A serious of in vitro images of human cadaver samples, containing calcified plaques, fibrous
plaques or lipid-rich plaques, demonstrated the feasibility and superiority of the integrated IVUS-
OCT system to offer the complementary morphological description of human coronary arteries.
In chapter 3, a pilot study on the diagnostic accuracy of atherosclerosis using the integrated
IVUS-OCT system is reported. The results have demonstrated that the diagnostic accuracy of
atherosclerosis by using IVUS-OCT system was improved with statistical significance. More
importantly, based on the existing diagnostic criteria, the objective diagnostic criteria of IVUS-
OCT with a three-loop structure is firstly developed and reported, through closely working with
experienced interventional cardiologists and pathologists. This objective criteria makes the
integrated IVUS-OCT system a promising intravascular imaging technique that can be translated
to clinical studies in the near future.
21

In chapter 4, we have successfully developed and prototyped multi-frequency IVUS
imaging system catheters with three different frequency. The multi-frequency IVUS catheter, with
a clinical compatible size of 0.95 mm in diameter, is featured by the back-to-back arrangement of
a conventional IVUS transducer and a high frequency IVUS transducer to achieve accurate co-
registration of two IVUS images. The in vitro human cadaver coronary artery imaging
demonstrates the capability of the multi-frequency catheter to provide more comprehensive
visualization of the vascular structure and to facilitate the assessment of the vulnerable plaque.
Compared to other multi-modality intravascular imaging techniques, the multi-frequency IVUS
imaging capitalizes the advantage of cost-effectiveness because only a moderate modification of
the current commercial IVUS system is needed.
In chapter 5, a new IVUS-IVPA system is developed to overcome the limitations of the
previous IVPA imaging systems. Two types of flexibly rotary IVPA catheter were designed,
fabricated, and validated on the imaging system. The frame rate of the imaging system has been
increased from 0.04 fps to 4 fps with two order of magnitude increase. By using the strong optical
absorption contrast for the lipid component at 1197nm, the lipid core size is quantified in the in
vitro coronary artery imaging experiments. The combination of IVUS and IVPA is likely to be a
promising tool to access both the morphological and the functional information of the coronary
artery.
In chapter 6, we reported the further development of the ARF-OCE system. Based on the
mechanical resonance of tissues in response to external periodic excitations, an acoustic excitation
frequency dependent resonant ARF-OCE algorism is developed to provide additional contrast to
the previous ARF-OCE system. Moreover, the confocal arrangement of the acoustic excitation and
the optical detection by using a single ring transducer and a dual-ring transducer is established.
22

The phantom validation study and the in vitro human cadaver sample study suggest that ARF-OCE
is capable of differentiating the coronary artery component based on the biomechanical
characteristics.
In chapter 7, a high resolution ultrasonic elastography (HMI) technique is developed to
accurately distinguish imaging subjects with varying stiffness at a small scale. The high resolution
HMI takes the advantage of low frequency (4 MHz) excitation to generate enough ARF-induced
displacements and high frequency ultrasound detection to accurately characterize tissue’s
mechanical properties at a small scale. The acoustic beams of two ultrasonic transducers were
precisely aligned into confocal configuration to provide an effective FOV of 2 mm in depth. The
measured lateral and axial resolutions of HMI system were 314 and 154 μm, respectively. The
feasibility of this HMI system on differentiating materials with different stiffness was validated on
three different agar-based tissue-mimicking phantoms. These results demonstrate that the high
resolution HMI is able to accurately map the stiffness distribution onto the structural ultrasound
B-mode image. The HMI of ex-vivo human atherosclerosis coronary artery is able to determine
the layer-specific pathological structure and identify the calcified plaque based on the
biomechanical properties of the coronary artery.
Finally, chapter 8 summaries the thesis and provide the perspectives of future development
of multi-modality intravascular imaging system by combined use of ultrasonic and optical
techniques.

23

Chapter 2 Ultra-high Speed Fully Integrated IVUS and OCT
Imaging System
2.1 Motivation of Combined Use IVUS and OCT
Each year, more than 20 million patients worldwide with coronary artery disease (CAD)
experience acute coronary syndrome (ACS) and thirty-four percent of these individuals die from
CAD complications in a given year (Véronique L. Roger 2011). ACS is caused by the
accumulation of vulnerable atherosclerotic plaques within coronary artery walls. It is essential to
have high-resolution and deep-penetration imaging techniques on the scale of 2-2000 μm, which
is the length scale CAD usually occurs at, to visualize vascular plaque elements in the coronary
artery wall. Currently, only intravascular ultrasound (IVUS) and intravascular optical coherence
tomography (OCT) are able to provide cross-sectional real-time visualization of the coronary
artery wall. However, due to the intrinsic resolution of IVUS and penetration depth limitation of
OCT, neither of them alone is able to accurately assess plaque characteristics (Masanori Kawasaki
and Seemantini K. Nadkarni 2006, Takahiro Sawada, Satoshi Watanabe et al. 2008, Troels Thim
2010). Combined use of IVUS and OCT holds the potential of combining the strengths of the two
imaging modalities and improving the diagnostic accuracy of plaque vulnerability. Thus, the
fusion of these disparate medical imaging modalities is clinically important in enhancing
diagnostic accuracy.
An integrated imaging system combining OCT whose high resolution can resolve the
superficial microstructures and ultrasound whose penetration depth can cover the whole vessel
wall would be more beneficial than either one alone. Moreover, in such a system, a minimal
24

amount of flushing agent is needed for OCT since ultrasound can serve as guidance while
searching for targets in the blood vessel. The feasibility of combining information from
intravascular OCT and IVUS for detecting TCFA has been studied by several investigators.
Sawada et al (Sawada, Shite et al. 2008) accomplish the combination by acquiring ultrasound and
OCT images from separate systems. The results indicate that neither modality alone is sufficient
for detecting TCFA, while the combined use of OCT and IVUS provides much better sensitivity
and specificity for evaluating TCFA. However, using two separate catheters and systems is not
only time consuming, but also gives the patients extra suffering and possibly increases safety risks.
In addition, separately acquired IVUS and OCT images may not be fully co-registered, which
could result in inaccurate diagnosis. An integrated IVUS-OCT catheter and system is an alternative
solution to potentially overcome all the aforementioned problems.
However, the translation of such a technology into clinical practice was greatly hindered
by the large gap between IVUS and OCT imaging speeds(Räber L, Heo JH et al. 2012). A speed
of 30 fps is commonly used in a commercially available IVUS system, while commercial OCT
systems usually perform at over 100 fps(H. Zacharatos, A.E. Hassan et al. 2010, Krishnaraj S
Rathod, Stephen M Hamshere et al. 2015). An integrated IVUS-OCT system can only operate at
the lower speed, i.e. that of IVUS. With the 30 fps IVUS imaging speed, an extensive amount of
the contrast agent is needed to obtrain clear OCT images, but it would be extremely dangerous for
the patients (for example, a 15-second injection of 45 ml contrast agents will be required if a 10
cm artery is imaged). The use of contrast agents may lead to renal function disorder(McCullough
2008). Some patients may also encounter life-threatening reactions, such as cardiotoxic effects and
seizures. Low speed imaging, and thus long imaging procedure time, may also increase the chance
25

of catheter-induced spasm(Seung-Jung Park, Young-Hak Kim et al. 2007). Thus, this speed limit
became a fundamental barrier for the transition of an integrated IVUS-OCT into clinical practice.
Thus, in this chapter, we successfully addressed this challenge through the development
and in vivo application of an ultrafast integrated IVUS-OCT imaging system and back-to-back
IVUS-OCT catheter. The IVUS-OCT technique provides the complementary advantages of both
OCT and IVUS, without sacrificing the imaging speed or increasing operation risks.
2.2 Development of Hybrid IVUS-OCT Catheter
2.2.1 Previous Generations of Catheter Design
There have been three generations of integrated IVUS-OCT catheter design presented by
our group summarized in Figure 2-1 and Table 2-1. The first generation of IVUS-OCT (Figure
2-1 (a)) demonstrated the breakthrough of using dual-modality imaging probe to generate both
IVUS image and OCT images at same time; however, it suffered from the large probe size of 2.4
mm and disadvantages of offline signal processing to co-register IVUS and OCT images(Yin,
Yang et al. 2010). The unique design of second generation of IVUS-OCT probe (Figure 2-1 (b))
solves the image co-registration problem by using a miniaturized ring transducer confocally
aligned with the OCT light beam. However, the large OD and long rigid part limited the possibility
of translating this design to the intracoronary artery imaging(Li, Yin et al. 2010). Even though the
OD of third generation of IVUS-OCT (Figure 2-1 (c)) was further reduced to only 0.64 mm, the
OCT probe and ultrasonic transducer did not image the same cross-section within each imaging
frame(Yin, Li et al. 2011). The image co-registration has to be performed under 3D pull-back
26

scanning reconstruction, which potentially caused error during the interventional procedure since
the lumen size continuously changed during the cardiac cycle. Therefore, an optimized design of
IVUS-OCT is essentially needed in order to lead this promising technology into clinical validation
and study.

Figure 2-1: (a) Schematic of first generation of IVUS-OCT probe(Yin, Yang et al. 2010) (b)
Schematic and photography of second generation of IVUS-OCT probe (Li, Yin et al. 2010).(c)
Schematic and photography of third generation of IVUS-OCT probe (Yin, Li et al. 2011).

Table 2-1: Summary of design parameters of three generations of IVUS-OCT probe design (the
highlighted parameter indicates the major limitation of design for dual-modality intravascular
catheter design).
Generation 1 Generation 2 Generation 3
Outer Diameter 2.4 mm 2.5 mm 0.64 mm
Rigid Cap Length 5 mm 5 mm 3 mm
Transducer Material PZT LNO PMN-PT
Light reflection Micro-prism Glass mirror Micro-prism
Co-registration
Offline fusion
Co-planar
Online fusion
Confocal
Offline fusion
Different cross-section

27

By making this probe into a catheter, we achieved many features that are required for
clinical use. A finished integrated IVUS-OCT catheter is shown in Figure 2-2. The catheter has a
diameter of 3.6 Fr and an effective length of more than 1.6 m. There is an imaging window, about
15-20 cm long, at the distal end of the catheter, which is transparent to both ultrasound and OCT.
An X-ray opaque marker for angiography and a slot for guide wire were located at the tip of
catheter. The catheter is capable of flushing and pulling back. The flexible torque coil shaft ensured
the rotational torque can be smoothly translated through the whole catheter.

Figure 2-2: A finished integrated IVUS-OCT catheter is inside a 3.6 Fr sheath.

2.2.2 Optimized Back-to-back IVUS-OCT Catheter Design
Clinical Requirement
There have been several reports demonstrating the feasibility and potential effectiveness
of the combined use of OCT and IVUS in different clinical settings for plaque characterization and
thin-cap fibroatheroma (TCFA) recognition (Takahiro Sawada, Satoshi Watanabe et al. 2008,
28

Räber L 2012). Nevertheless, there are major limitations to previous approaches using offline
fusion of OCT and IVUS (Takahiro Sawada, Satoshi Watanabe et al. 2008, Räber L 2012): prior
to fusion, matching OCT and IVUS lesions based on manual identification of landmarks, such as
side-branches or calcification, is required. The matching procedures are not only tediously slow
but also may lead to inaccurate co-registration, because lumens constantly change shape and the
images acquired may not be identical at different points in time within each cardiac cycle. They
cannot be used for real-time display either, severely limiting clinical utility for guiding
interventions during a catheterization procedure. The ability to fully integrate OCT and IVUS
capabilities into a single imaging system for in vivo assessment of plaques (Rishi Puri 2011, Räber
L 2012) will help overcome these limitations. Fully-integrated techniques are also less time
consuming, less traumatic, provide less radiation exposure, use fewer contrast agents, and provide
more accurate imaging capabilities with the potential for a real-time fusion image display.
In preliminary research, our group first developed an integrated OCT-IVUS system and
imaging probe (Jiechen Yin 2010, Xiang Li 2010, Jiechen Yin 2011). Independently, Li et al.
(Brian H. Li 2012) designed a similar hybrid OCT-IVUS system and used it for in vitro human
cadaver imaging. Recently, we reported the safe and successful in vivo imaging of plaques in
rabbits and coronary arteries in a swine, using a miniature probe design (Jiechen Yin 2011).
However, one limitation of the previously employed miniature probe (Jiechen Yin 2011) was its
difficulty to co-register data in real-time, due to the offset between the OCT prism and IVUS
transducer. For a steady object, offline processing that shifts two images relative to the separation
of the probes may be able to fuse OCT-IVUS images of the same region of interest (ROI).
However, for in vivo imaging, constant changes in lumen geometry renders co-registering images
very difficult, given there is an offset between OCT and US probes.
29

Optimized Automatically Co-registered IVUS-OCT Catheter
We present a novel design for a miniature integrated probe that overcomes this limitation.
The new design uses back-to-back OCT-IVUS probes to facilitate imaging at the same ROI
simultaneously. This catheter enables real-time imaging and display of co-registered OCT-IVUS
images for identifying vulnerable plaques and guiding coronary intervention, which better fits
clinical needs compared to the previous probe design with an offline fusion method. In addition,
our current integrated probe design has a similar rigid-part size to the clinically-used IVUS or OCT
probe, has a clinically acceptable outer diameter (OD), and does not sacrifice image quality. The
reduction in probe size is essential to enable safer OCT-IVUS delivery for clinical applications.
We report the first demonstration of real-time 3D imaging and display of co-registered OCT-IVUS
images in polar coordinates.
With the guidance of visible light from the OCT-sub probe, a back-to-back, co-registered
OCT-IVUS probe (Fig. 1 b and c) was made by carefully aligning an OCT sub-probe with an IVUS
sub-probe, while confirming that the light beam and sound wave exit at the same axial position,
but 180 degrees apart. This integrated probe provides automatically co-registered and co-axial
fusion imaging. The combined probe was then inserted into a customized probe cap (a stainless
steel tube with two windows; OD: 0.9 mm; length: 1.5 mm). Following the probe cap, we used a
double wrapped torque coil to encompass the fiber and electrical wire, giving the probe adequate
flexibility and torque control. During experiments, the probe was inserted into a sheath to avoid
cross-contamination between probe and cadaver segments. Water was filled in the sheath to
facilitate ultrasound imaging.
30

Figure 2-3: Schematic of back-to-back OCT-IVUS probe, c) Photo of back-to-back probe, showing
the transducer. Insert: photo showing the OCT sub-probe, d) Schematic of cardiovascular system.

We used a 0.4 mm x 0.4 mm x 0.3 mm 45 MHz PMN-PT single element transducer for our
IVUS sub-probe, which is thinner than in previous designs (Jiechen Yin 2010, Jiechen Yin 2011).
The PMN-PT plate was lapped to a thickness of only 300µm before it was mechanically diced into
0.4mm*0.4mm square shape. The center core of a 46 AWB coaxial cable was connected to the
side of the backing layer (back electrode) and covered by epoxy (Epo-Tek 301, Epoxy
Technologies) to insulate from the front electrode without increasing the thickness of the
transducer. For the OCT sub-probe, we chose a ball-lens design, which enables less insertion loss
and stronger interfaces (M. Shishkov 2003, Youxin Mao 2010) than the traditional GRIN lens
design (Guillermo J. Tearney 1997, Brian H. Li 2012). Ball lenses also have the potential to be
manufactured in large quantities while maintaining constant performance. A single mode fiber
(SMF-28 Corning Incorporated; cladding OD: 0.125 mm) was fusion-spliced to a fiber spacer
(cladding OD: 0.125 mm; reflective index: 1.457; Prime Optical Fiber Corporation) using a
splicing workstation (GPX 3400 system, Vytran LLC). Then, a ball with a 560 µm-long fiber
spacer (Youxin Mao 2010) was created at the distal end of the fiber spacer using the splicing
workstation. This ball lens can generate a beam focusing at ~1 mm from the ball surface (Figure
2-4 (a) and (c)). Next, the lens was mechanically polished until the angle between the polished
31

surface and optical fiber was less than 37 degrees. The ball lens was later inserted into a sealed
polyimide tube, isolating the ball lens from the water in the sheath and maintaining an air-fiber
interface to ensure that the total internal reflection (TIR) was generated at the polished surface. To
compensate for the astigmatism caused by the toroidal sheath, the ball lens was intentionally
morphed into an ellipsoid. The toroidal sheath’s surface acts like a negative lens (R. Andrew Wall
2011), and via Zemax simulation, we found that a 150µm-radius ball with a 0.55 mm radius sheath
generates a beam similar to that produced by a 190µm-radius ball without a toroidal sheath (Figure
2-4). Thus, we specifically designed our ball lens’s fusion-splice procedures to make the ball lens
an ellipsoid shape: 190µm-radius in X-direction (Figure 2-4(a)) and 150 µm-radius in Y-direction
(Figure 2-4(c)).

Figure 2-4: Ellipsoid-shape ball lens design to minimize astigmatism caused by toroidal sheath, (a)
190µm-radius in X-direction and (c) 150µm-radius in Y-direction. Point Spread Function of
exiting beam at (b) X-direction and (d) Y-direction.
2.3 Integrated IVUS-OCT System Setup and Signal Processing
The schematic of the integrated IVUS-OCT system is shown in Figure 2-5 and a
photograph of the system is shown in Error! Reference source not found.. The system can be
32

roughly divided into four parts: IVUS subsystem, OCT subsystem, timing and motor controller,
data acquisition and processing components.

Figure 2-5: Schematic of IVUS-OCT imaging system. The blue blocks represent signal flow; the
orange blocks represent the mechanical joints; the green blocks represent synchronizing triggers.

An ultrafast IVUS-OCT imaging system was built based on a 50 kHz swept source laser
and a 50 kHz-external-triggered ultrasound pulser/receiver. A 150 MHz balance detector and a
500 Msamples/s two channel digitizer were used. OCT and ultrasound signal were acquired by the
channel 1 and 2 of the digitizer respectively. The A-line trigger of the swept laser was used as the
trigger signal for the digitizer. The AUX port of digitizer was connected to the external trigger-in
port of the US receiver for synchronizing. A pre-trigger sampling was used for the IVUS channel
in order to acquire the IVUS signal from the beginning of a pulser. The rotation was generated by
an external motor and transferred to the integrated probe by a timing belt. Transmission of optical
33

and electrical signals from the rotary part to the stationary part was achieved by an optical rotary
joint (maximal speed: 10000 RPM) and a custom designed brushed electrical slip ring (maximal
rotational speed: 5000 RPM). The rotational and pullback system was enclosed in an aluminum
box and tested for electrical safety, see Figure 2-6. The rotational and pullback speed was set at 72
rotations/s and 1.8 cm/s, respectively. A slip ring holder (with wire protection and electromagnetic
shielding) was designed to secure the slip ring at the proximal end of the catheter and connected
the bracket supporting the fiber rotary joint and motor. This connection was made possible by
magnets.

Figure 2-6: A rotary joint device connects the rotational and pull-back motor; and couples
electrical and optical signals from the rotational part to the stationary part.

All acquired frames were transferred to the onboard memory of a graphic processing unit,
which enabled enough computational speed to allow for simultaneous 72 fps processing and
displaying. All processed images with the raw data were saved in real-time in an ultrafast solid
state drive, which is illustrated in Figure 2-7. The co-registered OCT-IVUS polar domain image
34

pairs were displayed in real-time, by rotating OCT images 180 degrees to match IVUS images’
orientation and converting them from Cartesian coordinates to polar coordinates, using a
commercial graphical processing unit CUDA package. This is the first report of the capability to
display real-time OCT-IVUS imaging in polar coordinates.

Figure 2-7: Flow chart of signal acquisition and imaging processing of GPU based IVUS-OCT
system.

35

2.4 Imaging Results and Discussion
2.4.1 Coronary Artery Imaging by Using Back-to-back IVUS-OCT catheter
Human coronary arteries, which were up to 3 days postmortem and fixed with formalin,
were used for imaging. Plaques were imaged with this OCT-IVUS integrated system in phosphate
buffered saline at room temperature. After imaging, each coronary artery segment was sectioned
for histology analysis.
A typical cardiovascular system is shown in Figure 2-3 (d). The system includes several
sharp turns: from the descending aorta to ascending aorta, there is a curve of over 180 degrees.
Furthermore, the right (or left) coronary artery and ascending aorta are normally 80-90 degrees
angularly spaced. This curvy structure demands a probe with high flexibility, small diameter, and
short length of the rigid-part to provide safe access to the coronary arteries. In previously reported
probe designs, either the probe’s OD is too large or the rigid-part is too long, both of which
potentially reduce the safety of catheter interventions. The back-to-back ball-lens design probe
reported here minimizes the probe’s rigid-part to 1.5 mm-long, which is the same size as clinically-
used IVUS or OCT rigid-parts, while maintaining an OD of 0.9 mm. Using available space more
efficiently than previous designs, we further reduces probe size without reducing the size of optical
lenses, hence maintaining image quality. The optical system’s lateral resolution is ~40 µm, similar
to what the traditional 0.35mm-diameter GRIN lens can achieve. Standard pulse-echo testing (Fig.
3) was performed to evaluate the thinner (300 μm) IVUS transducer’s performance. The center
frequency of the IVUS transducer was found to be 45 MHz, exhibiting a -6dB fractional bandwidth
of 40% (Figure 2-8). Thus, the IVUS transducer demonstrated satisfactory performance compared
to those in previously published reports (Jiechen Yin 2010, Jiechen Yin 2011).
36

Figure 2-8: Time domain pulse-echo waveform and frequency spectrum of the IVUS probe with a
1mm-long coaxial cable connecting to a slip ring.

Representative OCT-IVUS image pairs of coronary artery segments with calcified plaques
and a lipid-fibrous plaque are shown in Figure 2-9(Ia-IId) and Figure 2-9(IIIa–IIId), respectively.
Sharp boundaries in OCT (Figure 2-9 Ia and IIa arrows) and acoustic shadows in IVUS (Figure
2-9 Ib and IIb arrows) demonstrate the locations of calcified plaques. The signal-high region in the
OCT image (Figure 2-9 IIIa arrowhead) demonstrates the location of a fibrous plaque. The signal-
low region overlaying diffused boundary in the OCT image (Figure 2-9 IIIa arrow) demonstrates
the location of a necrotic plaque. Histology photos validate the plaque type classification by OCT-
IVUS images.

1.8045 1.9298 2.055 2.1803 2.3055
-500
-250
0
250
500
Time ( µs)
Amplitude (mV)

25 35 45 55 65
-24
-18
-12
-6
0
Frequency (MHz)
Magnitude (dB)
Pulse-echo Response
Spectrum
37

Figure 2-9: Top row: Images of calcified plaques. (Ia) OCT, (Ib) IVUS and (Ic) merged OCT-
IVUS cross-sectional images of a human coronary artery with calcified plaque; (Id) corresponding
H&E histology. Second row: Images of coronary artery with deep calcification, indicating that
OCT lacks the capability to clearly visualize deep calcification. (IIa) OCT, (IIb) IVUS and (IIc)
merged OCT-IVUS cross-sectional images of human coronary artery with a calcified plaque; (IId)
corresponding H&E histology. Third row: Images of necrotic plaque and fibrous plaque. (IIIa)
OCT (IIIb) IVUS and (IIIc) merged OCT-IVUS cross-sectional images of human coronary artery
with necrotic plaque and fibrous plaque; (IIId) corresponding histology. Arrow: necrotic plaque.
Arrow head: fibrous plaque. Top inset: highly magnified image of the top box region, trichrome
stain. Inset image confirms the existence of fibrous plaque. Bottom inset: highly magnified image
of the bottom box region, CD 68 stain. Inset image confirms the existence of macrophages. Bottom
row: Images of FH swine coronary artery with intimal hyperplasia. Still frame from 35:00 second
of movie 1. (IVa) OCT (IVb) IVUS and (IVc) merged OCT-IVUS of FH swine coronary artery
with intimal hyperplasia; (IVd) corresponding H&E histology. Inset: highly magnified image of
Elastic stain. Scale bar: 1mm.

38

2.4.2 High Speed IVUS-OCT Imaging at 72 fps
This system can image at 72 frames per second (fps), which ensures a significantly shorter
duration of flushing and imaging procedures and greatly improves the safety and efficiency of
using an IVUS-OCT system. To show the potential of safe IVUS-OCT imaging for evaluating
plaques in vivo, we imaged the aortas of atherosclerotic rabbits, vessels which are comparable to
the caliber of human coronary arteries. Ultrafast volumetric imaging was performed safely and
successfully. 3D imaging of an abdominal aorta (72 mm in length) was acquired within a 4s
flushing of contrast agents, which is the same amount as what is used for standard clinical OCT
imaging. We also acquired IVUS-OCT images of vulnerable plaque with clear illustration of its
two crucial characteristics: the thin cap and the large necrotic core. This technology holds great
promise in detecting vulnerable plaque and optimizing treatment methods(Steve Ramcharitar,
Nieves Gonzalo et al. 2009) in the near future. With the development of this powerful imaging
tool, our ability to manage post-procedure complications and reduce repeat revascularization
procedures will also be improved.
Commercially available IVUS systems usually image at 30 fps(H. Zacharatos, A.E. Hassan
et al. 2010, Krishnaraj S Rathod, Stephen M Hamshere et al. 2015). A high imaging speed was
hypothesized to degrade IVUS image quality due to strong vibrations in the catheter, a high level
of noise generated in the coupling process, and a short detection duration for the ultrasound
transducer(Xiang Li, Jiawen Li et al. 2014). To quantitatively evaluate the imaging quality of our
ultrasound sub-system, we tested the contrast to noise ratio (CNR) of our system in a well-
controlled phantom, imaging at 25 fps, 50 fps and 72 fps. We used “wire in silicone gel” as a
phantom and used the same imaging catheter throughout the test to avoid unknown variables in
the animal experiments. The phantom tested showed the CNR of the ultrasound sub-system at 25
39

fps, 50 fps and 72 fps were 6.49 dB, 6.19 dB and 6.18 dB, respectively. There was only 0.31 dB
difference between 25 fps and 72 fps, i.e., a very subtle CNR drop. This sensitivity drop can be
compensated for by using our ultra-sensitive ultrasound transducer(Teng Ma, Mingyue Yu et al.
2015).
Over 300 ROI from 25 cadavers were imaged with the IVUS-OCT integrated system in
phosphate buffered saline. After imaging, each coronary artery was decalcified, embedded, and
sectioned to 6 μm-thick slides. Every 500 µm, two slides were collected and stained for identifying
the histological components of the ROI. One sectioned slide was stained with H&E, and the other
with immunostain CD 68. Two cardiologists read the corresponding IVUS-OCT image pairs and
classified them as TCFA or non-TCFA, blinded to each other’s diagnosis, and histological results.
They used OCT images to measure the thickness of the fibrous cap and IVUS images to evaluate
the lipid pool size.
To further strengthen the catheter design optimize data acquisition system, integrated
IVUS-OCT imaging of human cadaver coronary artery at 72 fps, and 1.8 cm/s pull back was
achieved. For a pull-back time of 6.5s and pull-back length of 11.7 cm, the corresponding
correctional IVUS-OCT image pairs and 3D reconstruction image pairs were shown in Figure 2-10
(d-e) and Figure 2-10 (i-j) respectively. Again, the IVUS is able provide the overall visualization
of the entire coronary artery volume with deep penetration, and the OCT is able to image the
detailed luminal structure with high resolution. An IVUS-OCT imaging pair of TCFA was shown
in Figure 2-10 (a-c). As shown in the IVUS image (Figure 2-10 (a)), an echo signal pool region
was indicated by the half-moon shape suggesting the existence of the lipid content, and the in the
OCT image (Figure 2-10 (a)), a fibrous cap region was indicated by the star. Both of the IVUS
finding and OCT finding agree very well with the histology image (Figure 2-10 (c)) with CD 68
40

stain, which confirmed the existence of TCFA in this imaging correction. The IVUS, OCT and
histology combinations of another example of complex atherosclerotic coronary artery with
confirmed TCFA was shown in Figure 2-10 (f-h). Cross-sectional OCT (Figure 2-10 f) and IVUS
(Figure 2-10 g) images clearly demonstrate complementary information about the coronary artery
wall. OCT allows for recognition of the thin cap feature, which is not seen in the IVUS image,
thanks to its high spatial resolution. IVUS detects the presence of an echolucent region,
representing the necrotic core. These two examples demonstrated the superiority of using
integrated IVUS-OCT technology to enhance the accurate characterization of human
atherosclerotic plaques, especially the vulnerable plaque TCFA. Given the fact that the typical
length of a human coronary is about 10 cm(Waller, Orr et al. 1992), with only 6 s, this ultra-high
speed IVUS-OCT image platform is able to allow the clinicians to have a 3D visualization of the
entire branch of the coronary artery by providing co-registered IVUS-OCT images.

41

Figure 2-10: (a) IVUS image with a large lipid-rich necrotic core indicated by the “half-moon”
shape. (b) OCT image with a thin fibrous cap indicated by the “star”. (c) Histology image
corresponding to (a) and (b) showing the indicators of TCFA. (d) Longitudinal cross-sectional
pull-back IVUS image with 6.5s pull-back time and 8.125 cm pull-back length. (e) The
corresponding longitudinal cross-sectional pull-back OCT image to (d). (f) IVUS image with a
calcified plaque indicatd by the double star and a region of lipid-deposition indicated by the arrow.
(g) The corresponding OCT to (f). (h) Histology image corresponding to (f) and (g) showing the
complex atherosclerotic coronary artery. (i) and (j): The 3D reconstruction of IVUS image and
OCT image, respectively.
42

To determine whether this system could provide enough mechanical stability, system
robustness, handling capability and imaging quality in clinical settings at such a high speed, live
healthy rabbits and atherosclerotic rabbits were imaged. The Institutional Animal Care and Use
Committee at the University of California Irvine approved the study for the use of New Zealand
white rabbits. Animal care and use was performed by qualified individuals and supervised by
clinical veterinarians. The first step was to develop a model of atherosclerosis. Two male New
Zealand white rabbits were fed a high-cholesterol diet (0.5% cholesterol, 6% peanut oil, Newco
Distributors, Inc). After 1 week on the diet, de-endothelialization procedures were performed on
all rabbits. We inserted a 4F Fogarty arterial catheter via a femoral artery and advanced to the level
of diaphragmatic recess of the aorta. Next, we inflated the balloon catheter to 8 atm and pulled
back in the abdominal aorta to the level of approximately the common iliac arteries. The balloon
was deflated and the above de-endotheliazation process was repeated for a total of three passes
within the abdominal aorta. After surgery, rabbits were continued on a high cholesterol diet. After
11-12 weeks, lesion formation was mature. It is believed that these lesions produced by balloon
de-endothelization and high-cholesterol diet are similar to human atherosclerosis plaques(Frank D.
Kolodgie 2003). A total of 12 volumetric data sets were obtained from 2 atherosclerotic rabbits
and 2 healthy rabbits (control). During the imaging procedures, the rabbits were anesthetized,
incubated and mechanically ventilated followed by general anesthesia administration. Under
general anesthesia, a laparotomy was performed to expose the abdominal aorta. A 6-F arterial
catheter was then inserted into the aorta(Hoang KC 2009) to the renal arteries in a superior to
inferior direction to correspond to anterograde arterial blood flow towards the lower extremities.
The IVUS-OCT catheter was advanced through the 6-F arterial catheter and into the abdominal
aorta. During 4 seconds, 72 mm long aorta segments were imaged. Omnipaque (a conventional
43

clinically used CT contrast agent) was used for blood clearance for OCT imaging. Before imaging,
a 12 cc flushing agent was flushed into the rabbit aorta at ~3 cc/s. After imaging, the imaged area
of each abdominal aorta was dissected, fixed, embedded, sectioned to 6 μm-thick slides and stained
with H&E stain.
Imaging at 72 fps was performed within the lumen of rabbit abdominal aortas, which are
of similar caliber to human coronary arteries. A four-second flushing agent injection was applied
at a speed of 3 ml/s to clear OCT images, i.e., the same amount of flushing agent as used in clinical
OCT. The pull-back was achieved by a computer controlled linear stage at a rate of 1.8 cm/s.
Volumetric imaging of arteries was obtained (Figure 2-11 I). According to IVUS-OCT images,
plaques can be clearly visualized and characterized (Figure 2-11 II, III and IV). Regions of interest
(ROIs) with intimal thickening that were observed by IVUS and OCT images (Figure 2-11 IIa, IIb,
IIIa, IIIb, IVa and IVb) correlated well with ROIs with pathological intimal thickening in Figure
2-11 IId, IIId and IVd.
44

Figure 2-11: Ultrafast imaging of a rabbit abdominal aorta in vivo. (I) Three-dimensional cut-away
rendering of the volumetric data set acquired with an intravascular catheter in abdominal aorta of
a live rabbit. The volume comprises 288 frames of images acquired in 4 s during the injection of
iohexol at a rate of 3 ml/s. Red, artery wall; semi-transparent white, lipid. Circular cross-section
IVUS (IIa) (IIIa) (IVa) OCT (IIb) (IIIb) (IVb) fused IVUS-OCT (IIc) (IIIc) (IVc) image pairs and
the corresponding H&E histology photos (IId) (IIId) (IVd) at locations 1, 2 and 3 denoted in (I).
Arrows point at lipid-rich plaque regions. Scale bar: 0.5mm. The shape of this artery changed
between in vivo imaging and histology due to the reduced intra-lumen pressure after this artery
was harvested.

In this study, we showed the feasibility of an ultrafast integrated OCT-IVUS system to
image and classify atherosclerotic plaques in vivo. We also confirmed that the full integration of
these two complementary techniques permits accurate evaluation of total plaque burden and plaque
types by using an in vitro human cadaver study. The fully integrated imaging system demonstrated
in this paper is well suited to identify TCFA. This is because it has a high resolution to identify
thin caps and, simultaneously, deep penetration to visualize lipid cores. This simultaneous IVUS-
45

OCT imaging technique has many advantages over previously reported reconstruction
techniques(Takahiro Sawada, Junya Shite et al. 2008, Räber L, Heo JH et al. 2012), which used
separately obtained OCT and IVUS data sets, in evaluating the two characteristics of TCFA. First,
the integrated system reduces the complexity of co-registering separately obtained OCT and IVUS
data sets. Second, the operation time and cost of procedures will be highly reduced compared to
using an IVUS catheter and OCT catheter separately, and requiring placement of the two catheters
(IVUS and OCT) in separate steps. Furthermore, under the guidance of IVUS, a minimal dose of
OCT flushing agents is needed, which diminishes the side effects caused by such agents. The fully
integrated IVUS-OCT technology has great potential to accelerate the clinical development of real-
time accurate identification of vulnerable plaques in humans. Limited speed means more injection
of contrast agents and also a higher risk of catheter-induced spasm(Seung-Jung Park, Young-Hak
Kim et al. 2007). Here, we successfully addressed this challenge by the development and in vivo
application of a 72 fps IVUS-OCT imaging system and catheter. This integrated system is able to
image at ~2.5 times the speed of common commercially available IVUS-only imaging systems.
This breakthrough was achieved through a series of technical advancements, including a more
advanced IVUS pulser/receiver, electrical slip ring, graphic processing unit, solid state drive, and
customized catheter design. This ultrafast system has the capability to perform volumetric imaging
of coronary arteries in several seconds and have the potential to evaluate plaque vulnerability with
great accuracy(Takahiro Sawada, Junya Shite et al. 2008, Fujii K, Hao H et al. 2015). This work
greatly narrows the gap in translating the IVUS-OCT technology to clinical applications.

46

Chapter 3 Diagnostic Accuracy and Diagnostic Criteria of
Integrated IVUS-OCT System
3.1 Background and Literature Review
Both diagnostic criteria of IVUS (Mintz, Nissen et al. 2001) and OCT (Jang, Bouma et al.
2002) were developed previously according to the recommendations of the American College of
Cardiology. A general comparison of the diagnostic criteria were listed in Table 3-1.

Table 3-1: Comparison of diagnostic criteria of atherosclerotic plaque components, adapted from
(Kawasaki, Bouma et al. 2006).
IVUS OCT
Calcification
Bright echoes, which have density equal
to or greater than that of the adventitia
with a phenomenon known as “acoustic
shadowing”
Heterogeneous, sharply delineated signal-
poor or signal-rich region or alternating
signal-poor or signal-rich region.
Fibrosis
An intermediate echogenicity between
echo-lucent athermanous and highly
echogenic calcified plaques
Homogenous, signal-rich region
Lipid pool
Homogenous echo-density less than that
adventitia, and no calcification was
present
Homogenous, diffusely bordered, signal-
poor regions with overlying signal-rich
bands

There are several studies comparing the diagnostic accuracy of IVUS and OCT. The
sensitivity/specificity of IVUS based imaging diagnosis and OCT-based imaging diagnosis for
calcified plaque, fibrous plaque and lipid-rich plaque in Rieber’s (Rieber 2006), Kume’s (Kume T
2006), and Kawasaki‘s (Kawasaki M 2006) papers are listed in Table 1. In general, OCT is superior
in differentiating lipid plaque and fibrous plaque (soft tissues) while IVUS is superior in
visualizing and characterizing deep tissue components (deeper than 500 µm) as summarized in
47

Table 3-2. In general, OCT is superior in differentiating lipid plaque and fibrous plaque (soft
tissues) while IVUS is superior in visualizing and characterizing deep tissue components (deeper
than 500µm) as summarized in Table 3-3. However, all three of these studies expose the natural
limitation that the comparison requires offline-fusion of images acquired by separated IVUS and
OCT systems. This limitation would not only contribute to the errors caused by inferior co-
registration of IVUS and OCT but also reduce the significance of translating these studies to
clinical benefits.

Table 3-2: Previous reported diagnostic accuracy (sensitivity/specificity) of IVUS-only and OCT-
only based diagnosis by Rieber’s (Rieber 2006), Kume’s (Kume T 2006), and Kawasaki‘s
(Kawasaki M 2006).
Sensitivity/
Specificity
Rieber’s Kume’s Kawasaki‘s
IVUS OCT IVUS OCT IVUS OCT
Calcified 76%/98% 67%/97% 98%/96% 96%/88% 100%/99% 100%/100%
Fibrous 63%/59% 64%/88% 88%/86% 79%/99% 93%/61% 98%/94%
Lipid-rich 10%/96% 77%/94% 59%/97% 85%/94% 67%/95% 95%/98%

Table 3-3: The advantages and disadvantages of OCT and IVUS in classifying each type of
atherosclerotic plaque.
Calcified Lipid-rich Fibrous
OCT
Advantages
Assesses detailed
calcification boundary
By optical contrast,
provides higher accuracy
than IVUS
By optical contrast,
provides higher accuracy
than IVUS
Disadvantages
Limited penetration
depth: Deep calcification
may not be imaged
Limited penetration depth Limited penetration depth
IVUS
Advantages
Distinguished strong echo
signal
NA NA
Disadvantages
Acoustic shadow blocks
visualization of the entire
calcification
Low soft tissue contrast
Low soft tissue contrast
and deep fibrous plaque
may be interpreted as
calcified plaque

48

Our group developed a fully-integrated dual-modality IVUS-OCT imaging system and
3.6F automatically co-registered catheter for simultaneous IVUS-OCT imaging with a high
resolution and deep penetration depth(Yin, Li et al. 2011, Li, Li et al. 2014, Li, Li et al. 2014). The
purpose of the present study was to investigate the diagnostic accuracy of our integrated IVUS-
OCT system and develop clinical objective diagnostic criteria for diagnosing atherosclerosis by
combined use of IVUS and OCT. This synergistic approach may serve as the optimized
intravascular imaging tool to access artery stability with the promising future of using in clinic.
3.2 Statistical Experiment Design
3.2.1 Specimen Preparation
To bring a valuable data to bear on the issue of imaging atherosclerotic plaques, we
carefully collected samples from cadavers who died of acute coronary events or were diagnosed
with atherosclerosis. A total of 241 regions of interest (ROI) were examined from 175 diseased
coronary arterial segments and 20 cadavers (12 females and 8 males, mean age 77+-13) up to 48
hours postmortem. After harvesting, the specimens were stored at 4
o
C until imaged with the IVUS-
OCT integrated system in warmed phosphate buffered saline (PSB) at 37
o
C. The study was
approved by the Institutional Review Board of the University of California, Irvine.
49

3.2.2 Histology Analysis
The imaged artery blocks were marked by a ink mark and needle, and then these blocks
were dissected, numbered, fixed with 10% buffered formalin, decalcified in a standard ethylene
diaminetetraaceitc acid-4 Na-20% citric acid solution for 10 hours, and then embedded in paraffin.
The blocks were finally sectioned to 6 μm-thick slides along the longitudinal pull back axis of
artery, and the cross-sections were stained with H&E, Elastic, Trichrome and CD 68 stain.
According to the American College of Cardiology clinical standard, these stains would routinely
allow for the classification of calcified, fibrous and lipid-rich plaque. All the histological
classification were evaluated by a single experienced pathologist (Dr. Correa) blinded to the results
of any imaging modalities.
3.2.3 Imaging-based Diagnosis Analysis and Diagnostic Criteria
We have set a total of 241 regions of interests (ROI: one quadrant of the whole cross-
sections) on both the IVUS and OCT images. All IVUS-only diagnosis and OCT-only diagnosis
were performed by two skilled interventional cardiologists (Dr. Patel and Dr. Mohar) with random
order. OCT-only ROIs and IVUS-only ROIs were classified as calcified, fibrous and lipid-rich by
two cardiologists as to compare the diagnosis results by using IVUS-OCT image pairs later.
Cardiologists classified the OCT-only images, blinded to IVUS and histology, and then classified
IVUS-only images, blinded to OCT and histology. Using previously established criteria (Hiroshi
Yabushita 2002, Guillermo J. Tearney 2006, Kawasaki M 2006), for OCT images, the calcified
plaque was defined as signal-poor, intimal-thickening with sharp borders; the lipid-rich plaque was
defined as signal-poor, intimal-thickening with diffuse borders; fibrous plaque was defined as a
50

signal-high, intimal-thickening region. In IVUS images, calcified plaque was defined as acoustic
shadowing; lipid-rich as intimal thickening with echo density less than adventitia; fibrous plaque
as intimal thickening with echogenicity between lipid and calcification.
The existing IVUS diagnostic criteria (Gary S Mintz 2001) and OCT diagnosis
criteria(Jang, Bouma et al. 2002) were also adopted as references to develop this IVUS-OCT
diagnostic criteria (shown in Figure 3-1). IVUS images were mainly used to differentiate between
calcified tissue and soft (fibrous and lipid-rich) tissue due to its high sensitivity of identifying
calcification and deep imaging depth according to previous reports(Kawasaki M 2006, Kume T
2006, Rieber 2006). Although OCT is not capable of identifying calcified plaque beyond its
shallow imaging depth, it is still able to yield supplementary information on the exact location and
size of superficial calcified plaques. The diagnosis loop for the calcified plaque is established by
using IVUS as the main determination factor and OCT as the supplementary factor (loop 1). The
OCT diagnosis played a decisive role in distinguishing the fibrous and lipid-rich plaque based on
its high resolution and relatively higher optical contrast (Hiroshi Yabushita 2002, Guillermo J.
Tearney 2006). Meanwhile, the IVUS images offer complementary depth information and acoustic
contrast to make a secondary supportive evidence for the OCT initial assessment which forms two
more loops of criteria for fibrous plaque (loop 2) and lipid rich plaque (loop3). A three-loop
structure formed by main determinant and supportive evidence is established by the
complementary use of IVUS and OCT, which would hypothetically improve the diagnostic
accuracy of these three plaque classifications, especially the lipid-rich plaque.

51

Figure 3-1: Flow chart for objective diagnostic criteria of IVUS-OCT. Solid arrow with rectangular
block represent main determinant path, dashed arrow with elliptic block represent secondary
supportive evidence path. By combined use the complementary information of both IVUS and
OCT, three loops diagnostic criteria are formed to characterize calcified (loop 1), fibrous (loop 2)
and lipid-rich (loop 3) plaques.

3.2.4 Statistical Study
We evaluated the predictive ability of each modality by calculating the sensitivity and
specificity of each different imaging technique and comparing the point estimates with 95%
confidence intervals. The histopathology diagnoses were set as the “gold standard” for each tissue
component. We used ROIs in which the diagnoses made by the two readers were identical. All the
numerical data were expressed as the mean +- standard deviation. A p value of 0.05 was considered
statistically significant by conducting independent student t-test. We further quantified the
agreement between results of each imaging technique and histopathology diagnoses, and intra-
observer variability of each imaging technique by Cohen’s κ test for concordance. A Cohen’s κ
value of 0.61-80 indicates substantial agreement, and 0.81-1 indicates almost perfect agreement.
52

All statistical analyses were performed using commercial software MedCalc for Windows, version
12.5 (MedCalc Software, Ostend, Belgium).
3.3 Diagnostic Accuracy of Integrated IVUS-OCT System
3.3.1 Intraobserver Variability
Two physicians who have experience in examining IVUS and OCT intravascular imaging
first made the diagnosis based on IVUS-only, OCT-only images and IVUS-OCT paired images
for the selected 241 ROIs from the volumetric data blinded to each other’s diagnosis, other imaging
results and histological results. Only the identical diagnoses between the two cardiologists were
used to make the statistical validation of imaging diagnoses compared to the histology results. The
IVUS-OCT diagnoses had the perfect overall agreement between the two cardiologists with the
Cohen’s κ = 0.86 (95% confidence interval (CI) 0.81 to 0.92) and 221 identical diagnoses. The
overall agreement between the two cardiologists of OCT-only diagnoses and IVUS-only diagnoses
were 0.78 (95%CI 0.71-0.85) and 0.72 (95% CI 0.65-0.80) with the identical diagnoses number of
207 and 200, respectively. As shown in Table 3-4, the IVUS-OCT diagnoses between the two
cardiologists had higher overall agreements and more identical diagnoses than that of OCT-only
and IVUS-only diagnoses.

53

Table 3-4: Interobserver variability of each imaging diagnosis.

3.3.2 Histological Diagnosis vs Imaging-based Diagnosis
As shown in Table 3-5, within the 221 ROIs where identical diagnoses were made by the
two cardiologists, the IVUS-OCT diagnosis had the highest overall agreement with histology
diagnosis with the Cohen’s κ= 0.96 (95% CI 0.81 to 0.92). The overall agreement between OCT-
only diagnosis and histology diagnosis was 0.91 (95% CI 0.86-0.96) within the 207 ROIs where
Interobserver Variability of IVUS-OCT Diagnosis
Cardiologist 2
Cardiologist 1 Calcified Fibrous Lipid Total
Calcified 92 1 1 94
Fibrous 6 101 5 112
Lipid 1 6 28 35
Total 99 108 34 241
Cohen’s κ = 0.86(0.81-0.92)
Interobserver Variability of OCT-only Diagnosis
Cardiologist 2
Cardiologist 1 Calcified Fibrous Lipid Total
Calcified 76 1 0 77
Fibrous 8 98 14 120
Lipid 9 2 33 44
Total 93 101 47 241
Cohen’s κ = 0.78(0.71-0.85)
Interobserver Variability of IVUS-only Diagnosis
Cardiologist 2
Cardiologist 1 Calcified Fibrous Lipid Total
Calcified 87 8 4 99
Fibrous 2 98 11 111
Lipid 1 14 16 31
Total 90 120 31 241
Cohen’s κ = 0.72(0.65-0.80)
54

identical diagnoses were made. The overall agreement between IVUS-only diagnosis and
histology diagnosis was lowest (κ = 0.89, 95% CI 0.83-0.94) within the 200 ROIs where identical
diagnoses were made. The lipid-rich plaque was the most misidentified plaque type by using the
IVUS-only diagnosis.

Table 3-5: Overall agreement between the imaging based diagnosis and histological diagnosis.
Comparison between IVUS-OCT diagnosis and histological diagnosis
Histology
IVUS-OCT Calcified Fibrous Lipid Total
Calcified 92 0 0 92
Fibrous 0 97 3 100
Lipid 0 2 27 29
Total 92 99 30 221
Cohen’s κ = 0.96(0.93-1.00)
Comparison between OCT-only diagnosis and histological diagnosis
Histology
OCT Calcified Fibrous Lipid Total
Calcified 76 0 0 76
Fibrous 2 92 5 99
Lipid 1 3 28
Total 79 95 33 207
Cohen’s κ = 0.91(0.86-0.96)
Comparison between IVUS-only diagnosis and histological diagnosis
Histology
IVUS Calcified Fibrous Lipid Total
Calcified 85 1 0 86
Fibrous 2 87 9 98
Lipid 0 1 15 16
Total 87 89 24 200
Cohen’s κ = 0.89(0.83-0.94)
55

3.3.3 Sensitivity and Specificity Quantification
The diagnostic accuracy of each imaging technique is listed in Table 3-6. The
corresponding sensitivity of IVUS-OCT diagnosis for charactering calcified, fibrous and lipid-rich
plaque was 100%, 98%, and 90%. The specificity of IVUS-OCT diagnosis was 100%, 97.5% and
98.4%, respectively. The respective sensitivity of OCT-only diagnosis for charactering calcified,
fibrous and lipid-rich plaque was 96.2%, 96.8%, and 84.9%. The specificity of OCT-only
diagnosis was 100%, 93.8% and 97.7%, respectively. The sensitivity/specificity of IVUS-only
diagnosis were 97.7%/91.1%, 97.8%/90.1% and 62.5%/99.4% for charactering calcified, fibrous
and lipid-rich plaque, correspondingly. The histogram in Figure 3-2 is an alternative representation
of diagnosis accuracies of three imaging-based diagnoses for charactering three different plaques.
The sensitivity of IVUS-OCT on classifying lipid-rich was statistically higher than that of OCT-
only and IVUS-only diagnosis with a p-value less than 0.05. On the other hand, due to fact that
less lipid-rich plaques were misclassified by IVUS-OCT diagnosis, the specificity of IVUS-OCT
diagnosis was also statistically higher than that of OCT-only and IVUS-only diagnosis.

Figure 3-2: Histograms of sensitivity and specificity of imaging-based diagnosis. *Data
statistically different when comparing IVUS-OCT diagnosis to IVUS-only or OCT-only diagnosis.

56

Table 3-6: Diagnostic accuracy (sensitivity and specificity) of IVUS-OCT, OCT-only and IVUS-
only imaging diagnosis for characterizing calcified, fibrous and lipid-rich plaques. Data are
percentages with 95% confidence intervals.

IVUS/OCT
(n=221)
OCT-only
(n=207)
IVUS-only
(n=200)
Sensitivity Specificity Sensitivity Specificity Sensitivity Specificity
Calcified
100.0
(96.3-
100.0)
n = 92
100.0
(97.2-
100.0)
n =92
96.2
(89.3-99.2)
n = 79
100.0
(97.1-
100.0)
n =79
97.7
(91.9-99.7)
n = 87
99.1
(95.2-99.9)
n =87
Fibrous
98.0
(92.9-99.7)
n = 99
97.5
(93.0-99.5)
n = 99
96.8
(91.0-99.3)
n = 95
93.8
(87.5-97.4)
n = 95
97.8
(92.1-99.7)
n = 89
90.1
(83.0-94.9)
n = 89
Lipid-rich
90.0
(73.4-97.8)
n=30
98.4
(95.5-99.7)
n=30
84.9
(68.1-94.8)
n=33
97.7
(94.2-99.4)
n=33
62.5
(40.6-81.2)
n=24
99.4
(96.9-99.9)
n=24

3.4 Characterization of Calcified, Fibrous and Lipid-rich Plaques
Characterization of calcified plaque
Both IVUS-only diagnosis and OCT-only diagnosis demonstrated superior capability of
identifying calcified plaque with high sensitivity and specificity in the present study, which was
consistent with previous conclusions. However, both IVUS and OCT run into problems in
providing a full characterization of calcification. As shown in Figure 3-3, a deep calcified plaque
obviously distinguished by IVUS because of the unique feature of bright echo signal followed by
acoustic shadowing. Conversely, due to the limited penetration depth of the infrared light beam,
OCT was unable to provide any information on the deeply accumulated calcium, which might lead
to a misdiagnosis of calcified plaque to be fibrous plaque. However, for the superficial calcification,
57

strong acoustic shadowing artifacts caused by acoustic impedance difference of calcium and
relatively poor resolution made it impossible for IVUS to provide an entire morphological
visualization of the calcified plaque, especially the small calcification. On the other hand, OCT
outlined the entire boundary of the calcified plaque and targeted the precise location of the small
calcification (Figure 3-4) owing to its high resolution. Therefore, by combing the best features of
both techniques while minimizing their respective weaknesses, the IVUS-OCT diagnostic criteria
carrying the complementary information from both acoustic and optical contrast are capable of
presenting all the major histological features of calcified plaques.

Figure 3-3: Example of deep calcified plaque detection. (A) OCT image: due to limited imaging
depth, a deep calcified plaque (within the elliptic ROI) was misdiagnosed to be fibrous plaque by
OCT-only diagnosis. (B) IVUS image: a calcified plaque were diagnosis with clear future of bright
echo signal followed with acoustic shadow. (C) Histology image (H&E stain) confirmed a deep
calcified plaque.

58

Figure 3-4: Example of superficial calcified plaque characterization. (A) OCT image: within the
ROI, clear boundary and precise location of a large calcified plaque as well as a small calcified
plaque (pointed by arrow) were characterized by OCT diagnosis. (B) IVUS image: due to the poor
resolution and acoustic shadowing artifacts, the size and shape of the calcified plaques could not
be detail characterized. (C) Histology image (H&E stain) confirmed a large calcified plaque and a
small calcified plaque within the ROI.
Characterization of lipid-rich plaque
According to a previous study(Kawasaki M 2006), a higher frequency transducer (40MHz)
was able to detect intimal lesions more easily than a lower frequency transducer (30MHz). In the
present study, a 45 MHz transducer was used. As a result of the stronger focusing characteristics
of higher frequency acoustic beams, a 45MHz transducer enables higher axial resolution and a
more limited focal zone. This strength is comprised by downgrading the lateral resolution and
detection sensitivity beyond the focal zone, which made the position of transducer inside the artery
become an influential factor for IVUS diagnosis. For example, as shown in Figure 3-5, an
accumulated lipid deposit was confirmed with histological results, and the position of this lipid-
rich ROI was relatively farther away from the transducer. A false negative case of lipid-rich plaque
diagnosis based on IVUS-only was produced due to insufficient resolution and sensitivity.
However, using the OCT image as the reference, a slightly larger echolucent region compared with
an adjacent media layer allows it to be interpolated to serve as the secondary supportive
59

verification in the IVUS-OCT diagnostic criteria. Past data have attributed that false-negative OCT
diagnosis of lipid-rich plaque to the limited penetration depth of OCT, causing some thick-capped,
large lipid pools to be misinterpreted as fibrous plaque (Hiroshi Yabushita 2002) as the example
shown in Figure 3-6. However, by adding the complementary depth information of IVUS, this
false-negative diagnosis can be eliminated in the IVUS-OCT diagnosis criteria. Meanwhile, the
specificity of charactering fibrous plaque was also slightly improved since this type of false-
positive diagnosis of fibrous plaque was reduced. Therefore, the present study not only supports
the previous report that OCT diagnosis could detect lipid-rich plaque more accurately than IVUS
diagnosis, but also demonstrates the objective IVUS-OCT diagnostic criteria could further increase
the sensitivity of differentiating lipid-rich plaque with statistically significance.

Figure 3-5: Example of discrepancy between the OCT and IVUS on lipid-rich plaque diagnosis.
(A) OCT image: a lipid rich plaque was detected by OCT as a diffused boarded, signal-poor
regions with overlying signal-rich bands. (B) IVUS image: a false negative case of same lipid-rich
plaque by IVUS-only diagnose to be fibrous plaque. Referenced by OCT image, a corresponding
region of signal-poor characteristic was interpolated to be the supportive evidence in IVUS-OCT
diagnosis. (C) Histology images: Top image (H&E stain) and bottom image (highly magnified
image of CD68 stain).

60

Figure 3-6: Example of a false-negative diagnosis of lipid-rich plaque by OCT-only diagnosis. (A)
OCT image: a lipid-rich plaque was misdiagnosed as fibrous plaque by OCT-only diagnosis. (B)
IVUS image: a region homogenous low echo-density region was shown (pointed by the arrow),
but the lipid-rich plaque still could not be clearly discriminated without using OCT as a reference.
(C) Histology image (CD 68 Stain).

Discrimination of fibrous plaque
In previous studies (Kawasaki M 2006, Kume T 2006), both OCT and IVUS demonstrated
high diagnostic accuracy for charactering fibrous plaques, which were supported by our present
data. In the present study, all of the false-negative diagnosis cases of fibrous plaques were linked
to the false-positive of lipid-rich plaques in IVUS-OCT diagnosis and OCT-only diagnosis except
for IVUS diagnosis. According to Yabushita (Hiroshi Yabushita 2002) , this type of plaque often
contains a dominate amount of fibrous component and a small amount of lipid distribution. As
shown in Figure 3-7, the IVUS images offered the strong evidence of fibrous plaque with overall
intimal thickening. In spite of this, like the OCT-only diagnosis, the IVUS-OCT diagnosis still
misclassifies this ROI as a lipid-rich plaque because OCT characteristics served as the major
determinant in differentiating fibrous and lipid-rich plaque in the OCT-IVUS diagnosis criteria.
As a result, the current IVUS-OCT diagnostic criteria should be further modified to add more
61

classification features in differentiating clinically relevant significant and insignificant lipid
accumulations.

Figure 3-7: Example of false-negative IVUS-OCT diagnosis of fibrous plaque within overall
intimal thickening. (A) OCT image: ROI was misdiagnosed as lipid-rich plaque by OCT-only, and
IVUS-OCT diagnosis since OCT served as the major diagnostic factor. (B) IVUS image: whole
three-layer structure with overall intimal thickening were visualized by IVUS image. (C) Histology
image (H&E stain).

3.5 Study Limitation and Future Improvement
There are several limitations associated with this study that makes it difficult to allow our
finding to be used directly in a clinical setting. First, even though the imaging processes were
performed within 48 hours postmortem, the specimen degradation caused by artery tissue changes
was not evaluated in this study, which was a natural limitation by using cadaver specimens. Second,
different from clinical settings, the flow of PBS through the arteries and physiological pressure
were not maintained in the present study. Third, although we eliminated most histology images
with tissue-fold or stain artifacts, histology processes may cause some artifacts, such as changes
of luminal area. The slice thickness of histology is 6 μm, where OCT lateral resolution is 30 μm
62

and IVUS 200 μm. This difference may cause imperfect matches for IVUS-OCT and
corresponding histology images and thus may affect the result. Fourth, even though the testing
probe enables the auto co-registration of IVUS and OCT images within one image frame, the
transducer and OCT probe’s position and angle to the plaque may also affect the accuracy of the
diagnoses. Finally, the selected ROI were simply classified into calcified, fibrous and lipid plaques,
while the heterogeneity of atherosclerotic plaque composed of variously complex tissue
components was not fully considered. Therefore, IVUS-OCT diagnostic criteria should be
modified further to include additional classification features for differentiating plaque components,
especially the lipid pools and insignificant lipid accumulation in fibrous tissue dominant plaque.
We have imaged 241 ROI; but for lipid-rich plaque, we have only imaged 36 ROI in total due to
the limited access to younger patients’ coronary arteries. Further studies, with a larger sample set
and in vivo clinical imaging, will be required to provide a more accurate sensitivity/specificity
assessment of this system with higher statistical significance for identifying each plaque types and
TCFA.

63

Chapter 4 Multi-frequency Intravascular Ultrasound (IVUS)
Imaging
Acute coronary syndrome (ACS) is frequently associated with the sudden rupture of a
vulnerable atherosclerotic plaque within the coronary artery. Several unique physiological features
including a thin fibrous cap accompanied by a necrotic lipid core ，are the targeted indicators for
identifying the vulnerable plaques. Intravascular ultrasound (IVUS), a catheter-based imaging
technology, has been routinely performed in clinics for over 20 years to describe the morphology
of the coronary artery and guide percutaneous coronary interventions. However, conventional
IVUS cannot facilitate the risk assessment of ACS due to its intrinsic limitations, such as
insufficient resolution. Renovation of the IVUS technology is essentially needed to overcome the
limitations and enhance the coronary artery characterization. In this paper, a multi-frequency
intravascular ultrasound (IVUS) imaging system was developed by incorporating a higher
frequency IVUS transducer (80-150 MHz) with the conventional IVUS (30-50 MHz) system. The
newly developed system maintains the advantage of deeply penetrated imaging with the
conventional IVUS, while offers improved higher resolution image with IVUS at a higher
frequency. The prototyped multi-frequency catheter has a clinically compatible size of 0.95 mm
and a favorable capability of automated image co-registration. In vitro human coronary artery
imaging has demonstrated the feasibility and superiority of the multi-frequency IVUS imaging
system to deliver a more comprehensive visualization of the coronary artery. This ultrasonic-only
intravascular imaging technique, based on a moderate refinement of the conventional IVUS system,
is not only cost-effective from the perspective of manufacturing and clinical practice, but also
holds the promise of future translation into clinical benefits.

64

4.1 Introduction
The catheter-based grayscale intravascular ultrasound (IVUS) imaging, based on the
echogenicity of acoustic waves, has been clinically available for 20 years to provide the cross-
sectional visualization of the coronary artery wall and the quantitative evaluation of the lumen
dimensions and the plaque area (Potkin, Bartorelli et al. 1990, Aoki, Abizaid et al. 2005). The
aperture size of the piezoelectric transducer incorporated at the catheter tip, usually smaller than
0.8mm, is strictly limited by the confined size of the coronary artery lumen and the curvy structure
of coronary artery system (Foster, Pavlin et al. 2000). The typical center frequencies of IVUS
transducers range from 20 to 40MHz, providing 70-200 μm axial resolution, 200-400 μm lateral
resolution and 5-10mm imaging depth (Elliott and Thrush 1996, Brezinski, Tearney et al. 1997).
As a result, the spatial resolution of conventional IVUS is insufficient to measure the thin fibrous
cap thickness, which is usually smaller than 65 μm. A newly developed radiofrequency backscatter
spectrum analysis algorithm, Virtual Histology IVUS system (VH-IVUS), is capable of predicting
the plaque vulnerability through characterizing plaque composition (Nair, Kuban et al. 2002, Nasu,
Tsuchikane et al. 2006, Nair, Margolis et al. 2007). It is also a fact that data analyzed by VH is
displayed on the order of 250 μm, which intrinsically downgrades the reliability to detect the thin
fibrous cap of this technique (Garcia-Garcia, Mintz et al. 2009). Super-harmonic IVUS imaging
has been recently developed to image coronary vasa vasorum during the contrast agent injection;
however, in vivo validation and long-term optimization of this technique are needed to prove its
capability to perform accurate vulnerable plaque assessment (Ma, Martin et al. 2014). Optical
coherence tomography (OCT), which utilizes back-scattered infrared light to generate high speed
and high spatial resolution (10-30 μm) images of microstructures of blood vessels such as thin
fibrous cap, is hypothesized to be a substitute of IVUS (Brezinski, Tearney et al. 1996, Regar,
65

Schaar et al. 2003). However, the penetration depth through blood and vascular tissues of OCT is
shallow. A synergistic approach combining IVUS and OCT seems favorable by simultaneously
providing the deep penetration depth of IVUS and the high spatial resolution of OCT (Li, Li et al.
2014). Several designs of integrated IVUS-OCT catheters have previously been evaluated both in
vitro and in vivo to demonstrate the feasibility of this dual-modality intravascular imaging
technique that allows more accurate plaque characterization than using IVUS or OCT alone (Li,
Yin et al. 2010, Yin, Li et al. 2011, Bourantas, Garcia-Garcia et al. 2013, Li, Li et al. 2014).
Nevertheless, technical requirements such as advancing IVUS-OCT catheter design, increasing
the imaging speed and enhancing the accuracy of the co-registration between IVUS and OCT
images need to be satisfied before this technique can be implemented in clinical practice
(Bourantas, Garcia-Garcia et al. 2013). In addition, the manufacturing cost of such a hybrid system
will be dramatically increased because two independent systems must be integrated into one single
unit, which requires deliberation between translational strategies and long-term clinical
utility(Maresca, Adams et al. 2014). Given the fact that OCT is the optical analogue of ultrasound,
a question is then raised: can ultra-high frequency ultrasonic imaging be considered as an
alternative and cost-effective solution to replace OCT? Ultra-high frequency IVUS at 80MHz has
been previously investigated and proved to be able to improve artery characterization with much
higher axial resolution (Li, Wu et al. 2011). Even though there is a foreseeable drawback that
higher frequency ultrasound will have stronger attenuation in the blood and the vascular tissue,
such transducers at 80 MHz center frequency can still provide an imaging depth of 2 mm that is
comparable to the penetration depth of OCT. In addition, further increasing the frequency and
bandwidth of the ultrasound transducer is a possible approach to reach the axial resolution level of
OCT.
66

Although it is hard to identify the vulnerable plaques with the conventional IVUS because
of its low resolution, it is still a reliable technique that cannot be easily substituted in the near
future due to its accurate and deeply penetrated imaging capability (Puri, Worthley et al. 2011).
Therefore, compared to the integrated IVUS-OCT, incorporating another transducer at a higher
frequency to the current IVUS system seems to be a simpler and more cost-effective approach to
overcome the resolution limit of IVUS (Puri, Worthley et al. 2011). In this paper, we present the
development of a multi-frequency IVUS system by integrating a conventional transducer (35 MHz)
and an ultra-high frequency transducer (80-150 MHz) into one single catheter. Three prototypes
of the multi-frequency IVUS catheters with different frequency combinations (35/90 MHz, 35/120
MHz and 35/150 MHz) were fabricated and evaluated. The two transducer elements were arranged
in a back-to-back configuration to facilitate automatic image co-registration at the same
longitudinal location of the artery. The flexible catheters were miniaturized to have an outer
diameter of 0.95 mm and a front rigid length of 2 mm to enable the catheters’ clinical compatibility.
The multi-frequency IVUS imaging was assessed with a tissue mimicking phantom with and
without the presence of blood to evaluate the imaging depth, resolution and contrast-to-noise ratio
(CNR) of the imaging system. In vitro intravascular imaging of human cadaver coronary arteries
with atherosclerosis was conducted to demonstrate the merit of multi-frequency IVUS which
possesses the complementary nature of both low frequency and high frequency transducers. The
system provides the deep penetration to image the whole artery wall of the low frequency
transducer and the fine resolution in the lumen area of the high frequency transducer, allowing
more comprehensive visualization of the coronary artery. These results suggest that the multi-
frequency IVUS system appears to be a feasible and more cost-effective approach to overcome the
current limitations of the conventional IVUS system.
67

4.2 Method and Material
4.2.1 Catheter Design and Fabrication
The square element size of transducer was restricted to be less than 0.8 mm in the
conventional IVUS catheter. In order to fit the two transducers in the small catheter, the transducer
element size and thickness were fixed to be 0.5 x 0.5 mm
2
and 0.3 mm for various center
frequencies (35 MHz, 90 MHz, 120 MHz and 150 MHz) in this study. Many different piezoelectric
materials, including piezoceramics, piezoelectric polymers and ferroelectric single crystals, can be
used when designing a single element transducer. Choices between the materials are made based
on the piezoelectric properties and the specific requirements of the designed transducers such as
center frequency, aperture size and focal depth. Electromechanical coupling coefficient (kt),
piezoelectric coefficient (d33) and dielectric permittivity (
33 0
/
s
ε ε ), listed in Table 4-1, are the major
parameters that determine the performance of a transducer (Li, Ma et al. 2014). Since the
transducer aperture size is already determined in this study, the effects caused by dielectric
permittivity should be carefully taken into account during the material selection. The reason of
that is the dielectric permittivity, together with the surface area of piezoelectric material,
determines the electrical impedance of a transducer (Li, Wu et al. 2011). A properly matched
electrical impedance of 50 Ohms to the electronics will result in an optimized sensitivity in both
transmitting and receiving. Pb(Zr,Ti)O3 (PZT) ceramics has been widely used in fabrication of
IVUS transducers in the frequency range of 20-50 MHz (Lockwood, Turnbull et al. 1996).
Compared to PZT, the recently developed single crystal Pb(Mg1/3Nb2/3)-PbTiO3 (PMN-PT) (from
H.C. Materials Inc) exhibits improved piezoelectric performance on account of its outstanding kt
68

and d33 (Table.1), making it a more favorable candidate for ultrasonic transducer fabrication (Zhou,
Xu et al. 2007). In addition, PMN-PT is more suitable for high sensitivity, small aperture
ultrasound transducer application in a frequency range of 20-100 MHz, such as IVUS transducers,
because of its superior dielectric permittivity value (
33 0
/
s
ε ε ~5229) that makes the electrical
impedance of the transducer to be better matched with the 50 Ohms electronics within a tiny
surface area. In consequence, PMN-PT was used in this study to fabricate the 35MHz and 90MHz
transducer elements for the multi-frequency IVUS catheter. Nevertheless, for center frequency of
over 100 MHz, the electrical impedance mismatch between the PMN-PT transducer and the
acquisition platform will become significant for the same element size. And it is very challenging
to further miniaturize the aperture size of element to be less than 0.3 mm. A need for materials
with even lower dielectric permittivity rises for fabricating transducers with center frequency of
over 100 MHz. Lead-free single crystal lithium niobate (LiNbO3 or LNO) provides a comparable
kt to PZT, a much lower dielectric permittivity, and high longitudinal sound speed (v~7340 m/s).
It is suitable for designing sensitive large aperture high frequency single element transducers
(Cannata, Ritter et al. 2003). Therefore, LNO was selected to fabricate 120 MHz and 150 MHz
transducer elements.

Table 4-1: Piezoelectric properties of materials for IVUS imaging application.
PZT-5H
(Snook, Zhao et al. 2002)
PMN-PT
(Zhou, Xu et al. 2007)
LNO
(Cannata, Ritter et al. 2003)
Type Ceramic Single crystal Single crystal
kt 0.51 0.58 0.49
d33(pm/V) 593 2000 6
33 0
/
s
ε ε

1470 5229 39
v (m/s) 4580 4610 7340
Za (MRayl) 36.0 36.9 34
*Transducer fabrication in this study 35 & 90 MHz 120 & 150 MHz

69

The combination of two transducer elements in the multi-frequency IVUS catheter shares
a similar principle with the integration of a transducer and optical probe in the IVUS-OCT catheter,
as well as the hybrid catheter design for the other multi-modality intravascular imaging systems.
The design scheme of the intravascular catheter should not only allow for the technical feasibility
but also fulfill the clinical requirements. Several studies on the design of integrated IVUS-OCT
catheter have been reported individually (Li, Yin et al. 2010, Yin, Li et al. 2011, Bourantas, Garcia-
Garcia et al. 2013, Li, Li et al. 2014). Each of the designs carries its own features and limitations.
Based on the curvy structure of the cardiovascular system, a catheter with small outer diameter
(OD), short front rigid length and high flexibility is demanded to enable the safe delivery of
catheter to the coronary artery (Bourantas, Garcia-Garcia et al. 2013). Given the fact that the
cardiovascular intervention procedure is time-limited, the multi-frequency IVUS system should be
able to facilitate accurate fusion of two IVUS in a real time manner. Based on the previous IVUS-
OCT catheter designs, three design schemes, with different configurations of how the two
transducers of the same shape are aligned, of the multi-frequency IVUS catheter are presented and
summarized in Figure 4-1. These design schemes include aligning the two transducers in the
configurations of left-and-right, fore-and-aft and back-to-back. For the left-and-right configuration
(Figure 4-1 (a)), on-line image co-registration can be achieved by implementing a simple post-
processing algorithm since the two transducers are imaging the same cross section within each
image frame. However, this design scheme has an enlarged OD that is almost doubled as the single
element IVUS catheter. The fore-and-aft configuration (Figure 4-1 (b)) has a satisfactory OD that
is the same size as the single element IVUS catheter. But the increased front rigid length makes it
less flexible when going through sharp turns in the cardiovascular system. Moreover, image co-
registration has to be performed through pull-back scanning because the two transducers have a
70

separation of more than 0.5 mm, which may result in inaccurate image co-registration for the artery
walls that will be changing dynamically during each cardiac cycle. As shown in Figure 4-1 (c), the
back-to-back configuration provides a solution to the image co-registration problem in the fore-
and-aft configuration, since the two transducers generate images of same cross section within one
frame. This design scheme is preferred to the other two because it aligns the two transducers in the
thickness-direction, thus having the most effective use of space inside the cylindrical housing, and
consequently offers a small OD and short front rigid length. Furthermore, based on the unique
feature of back-to-back configuration, the real-time image co-registration at two frequencies can
be accomplished by simply rotating one of the IVUS images of the same cross section by 180
degree apart.

Figure 4-1: Illustrations of design schemes of multi-frequency IVUS catheter. (a) Left-and-right
configuration. (b) Fore-and-aft configuration. (c) Back-to-back configuration.

In this study, three prototypes of back-to-back multi-frequency IVUS catheters with
different frequency combinations (35/90 MHz, 35/120 MHz and 35/150 MHz) were fabricated and
evaluated. The general fabrication techniques described by Cannata et al. were used to prepare for
the single element IVUS transducer before assembling them into a catheter (Cannata, Ritter et al.
71

2003). The PMN-PT single crystal was lapped to 30 μm and 28 μm for the IVUS transducer
operating at 35 MHz and 90 MHz, respectively. LNO wafer of 22 μm and 15 μm were also acquired
to fabricate the transducer at 120 MHz and 150 MHz. All the wafers were sputtered a 1500 Å
chrome/gold on both sides to serve as the front and back electrodes. Due to the difficulties of
lapping the piezoelectric material down to a thickness less than 5 μm, only the 35 MHz and 90
MHz transducers had a matching layer made of the mixture of Insulcast 501 and 2-3 μm silver
particle. The matching layer was cast on to the front electrode of piezoelectric material, and then
lapped to the designed thickness listed in Table 4-2. Conductive epoxy (E-Solder 3022) was casted
onto the back electrodes of the wafers, and all of the wafers were lapped to a thickness of 0.3 mm.
The transducer element, together with the backing layer, was diced into a 0.5*0.5 mm
2
square
shape. The front electrode and back electrode were connected to the shielding wires and central
wires of the coaxial cable insulated by the epoxy, respectively. A parylene layer was deposited on
to the entire element of the transducers to serve as the 2
nd
matching layer of 35 MHz and 90 MHz
transducer, and the 1
st
matching layer for the 120 MHz and 150 MHz transducer. The thickness of
the parylene layer for each transducer was listed in Table 2. The two elements of different center
frequencies were carefully aligned into the back-to-back configuration before inserted into a two-
window stainless steel cap (0.95 mm OD and 2 mm length). A polyimide layer was bonded by
epoxy in between the two backings of the IVUS transducers so as to further insulate the electrical
signals. A triple wrapped torque coil (OD: 0.9 mm) was connected to the catheter cap, covering
the two electrical wires of the transducers in order to provide the smooth torque translation. The
two coaxial cables, a total of four electrical wires, were then connected to the separated channels
of an eight-channel slip ring (SRH0317, Prosper M&E Tech Co, Hangzhou, China) to allow for
the IVUS signal coupling for the two transducers during the rotational scan. The schematic and
72

photograph of a back-to-back multi-frequency IVUS catheter were shown in Figure 4-2 (a) and
(b). The overall size of the multi-frequency IVUS catheter is 0.95 mm in diameter with a front
rigid length of 2 mm, which is comparable to the size of a commercial IVUS catheter.

Table 4-2: Properties of the materials used in IVUS transducer fabrication (Cannata, Ritter et al.
2003)
Material Use
Density
(g/cm
3
)
Longitudinal sound
speed (m/s)
Acoustic impedance
(MRayl)
Insulcast 501 and 2-
3μm silver particles
1
st
Matching layer for
30 MHz (12 μm)
90 MHz (5 μm)
3.86 1900 7.3
Parylene
2
nd
matching layer for
30 MHz (12 um)
90 MHz (5 μm);
1
st
matching layer for
120 MHz (3 μm)
150 MHz (2 μm)
1.18 2200 2.6
E-Solder 3022 Backing layer 3.20 1890 5.9
EPO-TEK 301 Insolating Epoxy 1.15 2650 3.1

Figure 4-2: (a) Diagram of back-to-back multi-frequency IVUS catheter. Middle: 3D drawing.
Left-bottom: sectional drawing. (b) Photograph of a multi-frequency IVUS catheter prototype.
Enlarged photograph: side view (top) and front view (bottom) of catheter tip.
73

4.2.2 Phantom Preparation and Experimental Set-up
An agar-based tissue mimicking phantom with silicon carbide powder as the sound scatters
(Figure 4-3), having a 3-mm diameter lumen in the center, was fabricated to evaluate the CNR and
the imaging depth of the multi-frequency IVUS catheter (Ryan and Foster 1997, Teirlinck,
Bezemer et al. 1998). A polyimide tube with a 1.5 mm OD and a 50 μm wall thickness was placed
right next to the central lumen. A graphite rod with a 0.5 mm OD was placed at a distance of 0.5
mm away from the border of central lumen. The polyimide tube wall was designed to be a
resolution target, which was an analogue to the thin fibrous cap. The graphite rod was a target with
strong acoustic reflection.

Figure 4-3: Illustration of agar-based tissue mimicking phantom. (a) 3D drawing. (b) Sectional
drawing.

The experimental imaging set-up is illustrated in Figure 4-4. A low-frequency pulser
(AVTECH AVB2-TB-C, Avtech Electrosystems Ltd, Ogdensburg, NY) and a high-frequency
pulser (AVTECH AVB2-TC-C, Avtech Electrosystems Ltd, Ogdensburg, NY) were used to excite
the low-frequency transducer (35 MHz) and the high-frequency transducer (90 MHz, 120 MHz
and 150 MHz), respectively. The received radiofrequency (RF) signals were amplified by 33dB
74

(Miteq AU1114, MITEQ Inc, Hauppauge, NY), and digitized by a 12-bit data acquisition board
(Alazar Technologies Inc, Pointe-Claire, Canada) at a sampling frequency of 1.8 GS/s. Two
function generators were used to synchronize the pulser/receiver, digitizer and the motor unit, and
one of them has a 50 μs time delay in respect of the other. The saved RF data were processed and
displayed using a custom-developed LabVIEW program (National Instruments, Austin, TX).
During the imaging experiments, the catheter tip was positioned inside the central lumen of the
phantom and the catheter was rotated by the motor unit while the phantom and the slip ring were
kept stationary.

Figure 4-4: A diagram of the multi-frequency IVUS imaging system.

4.3 Transducer Characterization
Pulse-echo testing (Cannata, Ritter et al. 2003) was performed to evaluate the performance
of the transducers. An X-cut quartz, placed at an approximate distance of 1.9 mm away from the
transducers, was used as a reflecting target during the tests. The received echo signals in time
domain and the frequency responses of the 35 MHz transducer of the three catheters were recorded
and only one of them, as a representative, is shown in Figure 4-5(a). The echo signals and the
75

frequency responses of the 90 MHz, 120 MHz and 150 MHz transducers from the pulse-echo
testing are displayed in Figure 4-5(b-d), respectively. To evaluate the axial and lateral resolution
of the transducers, 6 μm diameter tungsten wire targets were imaged. The measured center
frequency, -6dB fractional bandwidth, axial resolution and lateral resolution of these transducers
are listed in Table 4-3.

Figure 4-5: Pulse-echo measurement results. Time-domain echo signals and frequency responses
of a representative (a) 35 MHz transducer, (b) 90 MHz transducer, (c) 120 MHz transducer and (d)
150 MHz transducer.

Table 4-3. Measured center frequencies, bandwidths and resolutions of the representative
transducers used in this study.
Designed Center Frequency (MHz) 35 90 120 150
Measured Center Frequency (MHz) 33.6 91.2 120.0 149.7
-6dB Fractional Bandwidth (%) 47.7 42.0 24.1 28.1
Axial Resolution (μm) 46.0 21.5 25.7 17.2
Lateral Resolution (μm) 231.5 123.5 105.3 87.3

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The measured center frequencies of these transducers are in reasonably good agreement
with the designed center frequencies. The comparisons in Fig. 5 also show that as the center
frequency of the transducer goes higher, the amplitude of the echo signals becomes smaller. These
transducers exhibit various bandwidth characteristics. The -6 dB fractional bandwidths of 35 MHz
and 90 MHz transducer are 47.4% and 42.0%, respectively, which is attributed to the better
piezoelectric properties of the PMN-PT single crystal as well as the presence of the silver epoxy
matching layer. However, due to the missing of the matching layer, the 120 MHz and 150 MHz
transducers made from LNO exhibit narrower bandwidths of 24.1% and 28.1% respectively.
Theoretically, a broader bandwidth will result in a shorter pulse length during the monocycle
excitation, and then a better axial resolution of a transducer can be achieved owing to the
broadband characteristics(Zhou, Lau et al. 2011). It should be noted that the axial resolution of the
90 MHz transducer is even better than that of the 120 MHz transducer. This can be explained by
the narrowband characteristics of the 120 MHz transducer. These results suggest that the high
frequency transducers ranging from 90 MHz to 150 MHz in this study are potentially capable of
resolving the thin fibrous cap in the axial direction. The lateral resolution is primarily dependent
on the beam width within the imaging range. Generally, the center frequency of a transducer has
a dominant influence on the lateral resolution, and hence a higher frequency transducer is able to
provide a better lateral resolution. The measured lateral resolutions of different transducers are
consistent with this theory, where the 150 MHz transducer provides the best lateral resolution of
87.3 μm. The axial resolution (17.2 μm) of the 150 MHz transducer can reach the same level of
OCT. However, given that the lateral resolution of the IVUS transducers in this study is
approximately four times of the axial resolution, the lateral resolution of IVUS is the least
competitive aspect when comparing with that of OCT.
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4.4 Tissue Mimicking Phantom Imaging Results
To evaluate the imaging capability of the multi-frequency IVUS catheter, tissue mimicking
phantom images without the presence of blood were initially acquired. The central lumen and the
polyimide tube were filled with DI water. A phantom image [Figure 4-6 (a)] captured by one of
the three 35 MHz IVUS demonstrated an imaging depth of 5 mm at this frequency. The graphite
rod was clearly distinguished from the surrounding agar with strong echo signal followed by an
acoustic shadow. The front and back surfaces of the polyimide tube could be identified, but the
actual thickness of the polyimide tube could not be precisely resolved due to insufficient resolution.
Another important evaluation parameter of an IVUS image is the CNR, which is also critical for
the detection of sub-resolution targets. The CNR was calculated by using the following equation
(Li and O'Donnell 1994, Li, Ma et al. 2014):

CNR =
�
（𝑚𝑚 𝑙𝑙 𝑙𝑙 𝑚𝑚 𝑡𝑡 − 𝑚𝑚 𝑙𝑙 𝑙𝑙 𝑚𝑚 𝑛𝑛 ）
2
𝑣𝑣 𝑙𝑙𝑙𝑙
𝑡𝑡 + 𝑣𝑣 𝑙𝑙𝑙𝑙
𝑛𝑛 (Equation 4-1)

where meant and meann stand for the mean of the signal of the imaging target and the mean of the
background noise; vart and varn represent the signal variance of the imaging target and the
background noise. In this case, the imaging target is the agar and the background noise is the water
filled lumen within the polyimide tube. The CNR of the phantom image of the 35 MHz transducer
is 5.1. The phantom images of the 90 MHz and 120 MHz transducers are shown in Figure 4-6 (b)
and (c), respectively. Because resolution has been improved, the front and back surfaces of the
polyimide tube could be better differentiated. A more detailed structure around the boundary of
the graphite rod could be visualized. Moreover, due to the stronger attenuation of higher frequency
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ultrasound, a significant decrease in imaging depths, about 2 mm and 1mm compared to 5 mm
with the 35 MHz transducer, was observed at 90 MHz and 120 MHz, respectively. At the same
time, the CNRs of the images at 90 MHz and 120 MHz dropped to 2.1 and 1.6, respectively. Figure
4-6(d) shows the phantom image generated by the 150 MHz transducer. Although the resolution
of the image was further improved, the image could only penetrate less than 500 μm in depth and
provided weaker contrast for the strong acoustic reflectors, such as surface of polyimide tube and
boundary of graphite rod. Thus, it appears that transducer at such frequency is not suitable for
IVUS imaging applications.

Figure 4-6: Tissue mimicking phantom images without presence of blood at (a) 35 MHz, (b) 90
MHz, (c) 120 MHz and (d) 150 MHz. Dynamic Range: 45 dB. Scale bar: 1 mm.

Despite the decreased penetration depth and CNR, IVUS transducers of 90 MHz and 120
MHz are still capable of providing valuable high resolution information around the inner lumen
area. The fused phantom images captured by 35/90 MHz catheter and 35/120 MHz catheter are
shown in Figure 4-7 (a) and (b), respectively. The image co-registration in each imaging pair is
accomplished by simply rotating one of the IVUS images by 180 degree. These results suggest
that the multi-frequency catheters can achieve better characterization of the artery tissue by
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integrating the deep imaging depth of lower frequency transducer and high resolution of higher
frequency transducer.

Figure 4-7: Fused tissue mimicking phantom images captured by (a) 35/90 MHz multi-frequency
IVUS catheter and (b) 35/120 MHz multi-frequency IVUS catheter. White color: 35 MHz
ultrasound image. Orange color: 90 MHz ultrasound image. Green color: 120 MHz ultrasound
image. Dynamic range: 45 dB. Scale bar: 1 mm.

To further investigate the feasibility of the multi-frequency catheters in a set-up that is
closer to the clinical settings, tissue mimicking phantom imaging was performed with the presence
of blood. The center lumen of the phantom was filled with fresh swine blood and the polyimide
tube was still filled with DI water. As expected, a slightly decreased penetration depth of 4 mm
and a reduced CNR value of 3.2 were obtained in the image at 35 MHz [Figure 4-8 (a)] due to the
strong attention of the blood in the lumen. As shown in Figure 4-8 (b-d), the much stronger
attenuation of the higher frequency ultrasonic waves in the blood dramatically limits the imaging
depth and degrades the image quality. These results indicate that to improve imaging depth with a
high frequency transducer may require the temporal removal of luminal blood during the in vivo
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imaging, similar to the flushing mechanism in OCT, which is an intrinsic drawback of multi-
frequency IVUS imaging.

Figure 4-8: Tissue mimicking phantom images in presence of blood at (a) 35 MHz, (b) 90 MHz,
(c) 120 MHz and (d) 150 MHz. Dynamic Range: 45 dB. Scale bar: 1 mm.

4.5 In vitro Human Cadaver Coronary Artery Imaging
Human cadaver coronary artery images acquired at 35 MHz, 90MHz, and 120 MHz are
displayed in Fig. 9. The 35 MHz transducer provides more complete morphological information
of the coronary artery owing to the deep penetration depth [Figure 4-9 (a)]. With the 90 MHz
transducer, the three-layer structure (intima, media and adventitia) pointed by the red arrow is
identified in Figure 4-9 (b) because of the improved axial resolution. However, it is blurred and
not apparent in Figure 4-9 (b). In Fig. 9 (c), although the 120 MHz transducer can only image
through the intima layer due to the limited penetration depth, an improvement in both axial
resolution and lateral resolution is achieved, indicated by a reduced speckle size in the image of
intima layer. The fused image pairs acquired by the 35/90 MHz and 35/120 MHz integrated
catheters were shown in Figure 4-10 (a) and (b), respectively. The integrated image pairs,
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combining the advantages of the high resolution superficial image of lumen area offered by the
high frequency IVUS transducer (90 MHz or 120 MHz) and the deep penetration image of the
entire artery wall provided by the low frequency transducer (35 MHz), yield a more comprehensive
visualization of the artery wall and plaque volume.

Figure 4-9: IVUS images of human coronary artery at (a) 35 MHz, (b) 90 MHz and (c) 120 MHz.
Dynamic Range: 50 dB. Scale bar: 1 mm.

Figure 4-10: Fused IVUS images of human coronary artery captured by (a) 35/90 MHz multi-
frequency IVUS catheter and (b) 35/120 MHz multi-frequency IVUS catheter. White color: 35
MHz IVUS image. Orange color: 90 MHz IVUS image. Green color: 120 MHz IVUS image.
Dynamic range: 50 dB. Scale bar: 1 mm.
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4.6 Discussions and Conclusion
The performance of the IVUS transducers used in this study are summarized in Figure 4-11,
including center frequency, imaging depth, imaging contrast and imaging resolution. The results
are in agreement with the classic ultrasound theory that increasing the center frequency of the
transducer results in better imaging resolution and decreased imaging depth. Even though different
piezoelectric materials were selected to fabricate the IVUS transducers at different center
frequencies, there was still some electrical impedance mismatch between the IVUS transducers
and electrical system due to the fact that the transducer aperture size was set to be 0.5 mm. Future
implementation of a matching circuit into the system will potentially solve this issue and improve
the overall performance of multi-frequency IVUS catheter. The lateral resolution of the multi-
frequency IVUS catheter system is almost three to four times worse than the axial resolution, which
is also the technical barrier and natural shortcoming of all other IVUS systems. There is a
significant gap between the conventional IVUS and the competitive technology OCT, indicated
by the red dot, regarding the image resolution and penetration depth. Combining a higher
frequency IVUS transducer in a frequency range of 90 MHz to 120 MHz with the conventional
IVUS catheter is a more feasible and simpler solution to reduce the controversy caused by
insufficient resolution and fill the gap between the conventional IVUS and OCT. However, the
requirement of temporal removal of luminal blood with the aim of eliminating the stronger
attenuation effect for higher frequency ultrasound, is a weakness of this technology that needs to
be addressed in the future. Although further increasing the center frequency of the transducer to
150 MHz or higher could theoretically reach the resolution level of OCT, the extremely shallow
imaging depth and reduced imaging contrast will dramatically degrade the image quality. Thus, it
may not be worthwhile to use the transducer with such high frequencies for IVUS applications. As
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discussed above, owing to its broadband characteristics, the 90 MHz transducer exhibits a better
axial resolution than the 120 MHz transducer. This suggests that the integration of a broader
bandwidth transducer is favorable to further renovate the multi-frequency IVUS catheters. The
newly developed micro-machined PIN-PMN-PT single crystal 1-3 composite transducer at 40
MHz for IVUS application, providing an improved axial resolution of 43 μm and a comparable
penetration depth to conventional IVUS transducers, was investigated (Yuan, Rhee et al. 2008, Li,
Li et al. 2014). For the possible implementation of 1-3 composite material in multi-frequency
IVUS imaging, the proposed 1-3 composite transducers in a frequency range of 60-90 MHz,
indicated by the blue dashed dot in Figure 4-11, serves as a more promising substitute for the high
frequency transducers in the multi-frequency IVUS catheters so that the enhanced resolution can
be achieved without excessively sacrificing imaging depth. Furthermore, the mechanical flexibility
of 1-3 composite material makes it possible to mechanically focus such a tiny transducer with the
intention of further improving the lateral resolution in the near future.
We have successfully developed and prototyped multi-frequency IVUS imaging system
catheters with three different frequency combinations prepared by PMN-PT and LNO single
crystals. The multi-frequency IVUS catheter, with a clinical compatible size of 0.95 mm in
diameter, is featured by the back-to-back arrangement of a conventional IVUS transducer and a
high frequency IVUS transducer to achieve accurate co-registration of two IVUS images. The
performance of the high frequency IVUS transducer at different frequency ranges (90 MHz, 120
MHz and 150 MHz) was evaluated and compared to find the optimal frequency range for the high
frequency transducer in the multi-frequency IVUS catheter, considering imaging depth, imaging
resolution and CNR. Tissue mimicking phantom imaging with and without the presence of blood
shows that the multi-frequency catheter carries the complementary strengths of the deep imaging
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depth of the conventional IVUS and the high resolution of the high frequency transducer. On the
other hand, these results also point out a potential weakness of the multi-frequency catheter, which
is flushing of the luminal blood is required to ensure the functionality of this technique. The in
vitro human cadaver coronary artery imaging demonstrates the capability of the multi-frequency
catheter to provide more comprehensive visualization of the vascular structure and to facilitate the
assessment of the vulnerable plaque. Compared to other multi-modality intravascular imaging
techniques, the multi-frequency IVUS imaging capitalizes the advantage of cost-effectiveness
because only a moderate modification of the current commercial IVUS system is needed. Besides,
the apparent clinical utility of this ultrasound-only technology can be promptly explored during
the translational stage since most of the interventional physicians are familiar with the ultrasound
technology. The future translation of the multi-frequency IVUS imaging into clinical use will not
only consolidate the leading status of the IVUS technology in the interventional cardiology
practice, but also prosperously lead to patient benefits.

Figure 4-11: Summaries of IVUS transducers’ performances at different center frequencies in this
study, including imaging depth, imaging contrast, and imaging resolution. Red dot: OCT. Dashed
blue dot: 1-3 composite IVUS transducer.
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Chapter 5 High-speed Intravascular Photoacoustic Imaging
5.1 Background
Lipid deposition inside arterial wall is a key indicator of plaque vulnerability. Quantifying
the size of lipid core will not only help doctors to provide accurate diagnosis and treatment plans,
but also evaluate efficacy of cholesterol lowering therapeutics. Among all interventional imaging
methods, intravascular photoacoustic (IVPA) imaging is considered as the most promising
candidate to fulfill the unmet need of quantifying the lipid inside arterial wall. However, the current
reported IVPA system suffered from slow imaging speed (~50 s per frame) due to the lack of
suitable laser source, which hindered its translational potential. In this study, we demonstrated an
IVPA system with the frame rate of 2 Hz by employing master oscillator power amplifier (MOPA)-
pumped barium nitrite [Ba(NO3)2] crystal-based Raman laser. This advancement increased the
imaging speed of IVPA system ~ 2 orders of magnitude, and thus bridge the gap of translating
IVPA technology to clinical setting.
There is a formidable barrier that blocks the transition of IVPA system from bench top to
bedside - the slow imaging speed. The current IVPA system employed a Nd:YAG-pumped optical
parametric oscillator (OPO) system with 10 Hz repetition rate to generate the excitation at 1.7 µm
and 1.2 µm wavelength for lipid visualization(Jansen, van der Steen et al. 2011, Wang, Karpiouk
et al. 2012, Bai, Gong et al. 2014). This laser repetition rate translates to a cross-sectional imaging
speed of 50 s per frame if 500 a-lines per image is acquired. Such speed is hardly applicable for
future clinical application, in which real-time frame rate is usually required. Therefore, to break
the bottleneck for developing a high-speed IVPA system, a nanosecond laser source with few kilo
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Hertz which can still provide the optimal wavelengths at 1.2 or 1.7 μm for lipid imaging is
demanded. The conventional method to generate nanosecond laser with 1.2 or 1.7 μm is to use a
Nd:YAG pumped optical parametric oscillator (OPO) system. At low repetition rate, high pump
energy systems can achieve high conversion efficiency, however, at kHz rates the high-energy
laser system becomes cost prohibitive and bulky. Small size kHz-rate laser system can generate
pulse energy in the range of several mJ. At such small energies the effect of walk-off limits the
useful non-linear crystal length, as the beam diameter has to be small in order to maintain high
power density required for OPO generation. The additional challenge in choosing the laser system
for IVPA is to obtain an optimal laser pulse duration. The optimal frequency responds of small
transducers used in IVPA is in tens of MHz range. The tissue acoustic frequency depends on
optical pulse duration, therefore the control over pulse duration is important for overall IVPA
performance. Unfortunately, most of commercially available kHz-rate pump lasers are Q-switch
lasers with fixed pulse duration.
Here in this work, we overcame abovementioned shortcomings by developing a Raman laser
which is consisted by a 2 kHz master oscillator power amplifier (MOPA) pump laser with tunable
pulse duration and a Ba(NO3)2-based Raman shifters. The Raman shifter works at the principle of
stimulated Raman scattering. The output wave wavelength of a Raman shifter is determined by
the pump wavelength and the Raman shifts of the medium. In our study, we applied Ba(NO3)2-
based Raman shifter, whose major Raman shift (Ω) at 1047 cm
-1
, to convert the 1064 nm pump to
a 1197 nm output. The successful application of Ba(NO3)2-based Raman laser for photoacoustic
tomography of lipid has been demonstrated at 10 Hz repetition rate (Li, Slipchenko et al. 2013).
Herein, we employed a 2 kHz MOPA system as a pumping source to obtain an output of 2 mJ at
1197 nm at 2 kHz repetition rate from the Raman shifter. This new high repetition rate laser system
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enables the IVPA imaging of lipid-laden plaque with 2 Hz frame rate which is 2 orders of
magnitude faster than the currently available systems (Jansen, van der Steen et al. 2011, Wang,
Karpiouk et al. 2012, Bai, Gong et al. 2014).
5.2 IVPA System Setup
5.2.1 Ramen Laser
Schematic of the Raman laser cavity is shown in Figure 5-1 (b). The crystal was installed
in a flat-flat resonator with a cavity length of about 10 cm. For the Ba(NO3)2-based Raman laser,
the resonator’s end mirror was coated with anti-reflectivity (AR) at 1064 nm, and high reflectivity
(HR) at 1197 nm. The output coupler was coated with high reflectivity at 1064 nm, and 50%
transmission at 1197 nm. Wavelength shift was accomplished in a Ba(NO)3 crystal (MolTech,
Germany) and AR coated at 1197 nm.
MOPA pump laser with tunable pulse duration (Spectral Energy LLC, Beavercreek, Ohio)
was employed as the pumping source, which provides up to 7 mJ pulse energy with a 2 kHz
repetition rate with the arbitrary pulse duration. The optical layout is shown in Figure 5-1 (b). The
output of a directly modulated diode laser (1064.4 nm vacuum wavelength, 100 mW peak power)
is first preamplified in 30 dB Ytterbium fiber amplifier before being amplified in two diode
pumped Nd:YAG amplifiers arranged in a double pass configuration. Lenses L1 and L4 with 50
mm focal length were used to compensate thermal lensing in the rods. To minimize the
depolarization effect the quartz rotator was placed between two amplifier modules. In addition, to
minimize the amplified spontaneous emission the pinholes were placed at focal plane of optical
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relay composed by lenses L2 and L3 and at the focal plane of second amplifier module. After
double passing amplifier modules the beam is directed in to the Raman shifter.

Figure 5-1: Principles and schematics of the Raman laser system. (a) The principle of the Ba
(NO3)2 crystals-based Raman Laser. (b) The Schematics of the Raman shifter: M1-M7: 45° 1064
nm reflective mirror; PBS: polarizing beam splitter; HWP: half wave plate; M8: resonator end
mirror; M9: output coupler; M10: silver mirror. (c) The schematics of the MOPA system: Amp:
amplifier; PH: pin hole; QR: quartz rotator; OI: optical isolator; FA: fiber amplifier; DL: Diode
laser; AOM: acousto-optical modulator.

5.2.2 3D Pull-back Rotary Scanning System
In order to demonstrate the high-speed IVPA imaging, we have developed a high speed
IVPA scanning, data acquisition, and processing system Figure 5-2(a). We assembled a
mechanical scanning system by integrating an optical rotary joint with electrical slip rings (Moog,
Inc., Torrance, CA) (Figure 5-2 (c)). The optical rotary joint was designed and constructed under
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the concept of free space coupling with large beam size to avoid the damage of optics. The distal
end of the fiber and electrical wires is connected to a fiber optical rotation joint and electric slip-
rings, respectively. The catheter was driven by a computer controlled servo motor (Moog, Inc.,
Torrance, CA) at desired rotation per minute, while the outer housing remains stationary. The
video in the supplementary information shows that the scanning system is rotating in 60 rotations
per min while still transmit the optical excitation. The trigger of the laser was used to synchronize
the data acquisition of both PA and US imaging. A delay generator was used to set an 11 us delay
between the laser pulse and pulser/receiver (5073PR, Olympus, Inc., Center Valley, PA). The
detected PA signal will be preamplified and then sent to a receiver. The total amplification was set
as 69 dB. The signal was digitized and recorded by a PC. A digitizer with 180 MS/s sampling rate
and 16 bits resolution (AlazerTech, Canada) was applied to enable high speed data acquisition and
transfer. A modern i7 quad-core processor will be employed for data processing. The data
acquisition software was developed in Labview. Data analysis was performed off-line by Matlab.
A 20 MHz digital high-pass filter was applied for US image while a 10 MHz digital high-pass
filter was applied for PA image. The PA spectroscopy on PE tube was performed by a Nd:YAG
pumped OPO system (Surelite, Continuum, San Jose, CA).
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Figure 5-2: (a) Block diagram showing the data acquisition system. FC: fiber coupler; DAQ: data
acquisition. (b) The photograph of the scanning assembly. (c) The explosive view of the schematic
of the rotary joint.
5.3 Catheter Design
5.3.1 Coaxial Design
A 35 MHz ring-shape transducer with 65% bandwidth and 3 mm focal length was applied
in the coaxial design of IVPA catheter (Figure 5-3). The ring-shape transducer had a 0.5 mm center
hole with which a 200 um core multimode fiber (Thorlabs Inc., Newton, NJ) was concentrically
aligned. This design ensured that the US pulse and optical excitation were aligned during the
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procedure. Both the excitation and the ultrasound transmission were deflected by a 45 degree rod
mirror (Edmund Optics, Barrington, NJ) with 2.9 mm size at the tip of the probe. Also, the
ultrasound echoes and the excited PA waves from the sample are deflected by the mirror and
detected by the ultrasound transducer. The micro rod mirror shared by the coaxial laser and
acoustic beams assures the total overlap of the laser and acoustic beams along the transmitting
path. Snell’s law governs the path of reflected and refracted waves when the acoustic wave
encounters an interface of two media (Cobbold 2007). The ratio of sound-propagation speeds
(1.5/5.1, longitudinal wave; 1.5/3.3 shear wave) in water and glass is large enough so that the total
internal reflection occurs at the interface of water and glass (Yang, Maslov et al. 2009). In other
words, there is no additional propagation loss on the transmitting path of the ultrasonic wave. The
mirror, optical fiber and ultrasonic transducer are fixed and packaged in a steel tube in which a
window is made to allow the laser beams and ultrasound beams to pass through. A torque coil was
used to house the fiber and electric wire and provided the torque directly to the tip of the probe.
The size of the probe is 2.9 mm in diameter.

Figure 5-3: Design of coaxial IVPA catheter. (a) Schematic of coaxial IVPA probe. (b) Photograph
of the coaxial IVPA probe.
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5.3.2 Sequential Design
The miniaturized IVUS/IVPA catheter is composed of sequential arranged side-firing
optical probe and side-viewing ultrasonic transducer, shown in Figure 5-4. A 200-µm-core
multimode fiber is used to deliver 1197 nm pulsed laser beams. Covered by a glued-on quarts cap,
the fiber tip is polished under a 40 degree angle. Air is trapped inside the tube to form air/glass
interface polished surface to redirect laser beams to match the field of view of ultrasonic transducer.
Similar to the integrated IVUS-OCT catheter discussed in Chapter 3 and Chapter 4, a 45MHz
PMN-PT ultrasonic transducer was assembled into IVUS/IVPA probes to detect the laser induced
photoacoustic signal and create IVUS images. The optical fiber and ultrasonic transducer are
arranged sequentially and packaged in a customized plastic tube (1.2mm OD) connected with a
1mm OD torque coil tube.

Figure 5-4: Design of sequential IVPA catheter. (a) Schematic of sequential IVPA probe. (b)
Photograph of the sequential IVPA probe.

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5.4 High Speed IVPA Imaging Results
5.4.1 High Speed PA Imaging of Lipid-mimicking Phantom by the Coaxial Catheter
We tested the characteristics of the high-speed IVPA imaging system with the excitation
provided by Ba(NO3)2-Raman laser (Figure 5-5). 1.2 mm polyethylene (PE) tubes were applied as
lipid-mimicking phantom to demonstrate the C-H bond-selective PA imaging by Ba(NO3)2 –based
Raman laser (Figure 5-5 a-c). The PA image (Figure 5-5 a) and the US image (Figure 5-5 b) were
acquired simultaneously, and the merged image (Figure 5-5(c)) confirmed the co-registration of
PA and US images. 1000 A-lines were acquired for one 2-D cross-sectional image, resulting in a
2 Hz frame rate. This speed is 2 order of magnitude faster than the current reported IVPA system
(Jansen, van der Steen et al. 2011, Wang, Karpiouk et al. 2012, Bai, Gong et al. 2014). The PA
spectroscopy of PE showed the signature peak of C-H2 bond at 1210 nm, which confirmed that the
contrast was indeed from C-H bond vibration (Figure 5-5(d)).

Figure 5-5: High-speed imaging of lipid-mimicking phantom. (a) Photoacoustic image, (b)
ultrasound image, (c) the merged image of PE tube. (d) The photoacoustic spectrum of PE tube.
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5.4.2 High Speed PA Imaging of Lipid-laden artery by the Coaxial Catheter
High-speed IVPA imaging of iliac artery from Ossabaw swine model with metabolism
syndrome was performed using Ba(NO3)2-based Raman laser (Figure 5-6). Cross-sectional
photoacoustic (Figure 5-6 a), ultrasound (Figure 5-6 b), and merged (Figure 5-6 c) images of the
atherosclerotic artery clearly shows the complementary information of the artery wall. Importantly,
the lipid deposition of the artery wall, which is not seen in the IVUS imaging, shows a clear
contrast in the IVPA image. This in vitro artery was not pressurized, thus the lumen has collapsed
partly and does not have the typical circular morphology. 2000 A-lines were acquired for the cross-
sectional image. The pulse energy which was applied to acquire each A-line was 80 µJ.

Figure 5-6: High speed PA Imaging of Lipid-laden artery acquired by coaxial catheter. (a) PA
imaging of the artery. (b) US image of the artery. (c) Merged PA & US image.
5.4.3 High Speed PA Imaging of Lipid-laden artery by the Sequential Catheter
Since the OD of the sequential catheter has been greatly reduced compared with the coaxial
catheter, the sequential catheter can be used to image smaller artery samples. In this catheter, a
higher center frequency (45 MHz) transducer were used compared with the coaxial catheter, which
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results in an improved axial resolution in both PA image (Figure 5-7 a) and US image (Figure 5-7
b). The merged US/PA image (Figure 5-7) demonstrate the IVPA system’s capability of precisely
targeting the size and location of lipid component based on the morphological information from
IVUS.

Figure 5-7: High speed PA Imaging of Lipid-laden artery acquired by a sequential catheter. (a)
PA imaging of the artery. (b) US image of the artery. (c) Merged PA & US image.

5.5 Discussion
We have constructed Ba (NO3)2-based Raman laser to generate the wavelengths at 1197
nm for lipid mapping inside the artery wall. It is known that both 1.2 µm and 1.7 µm resonant
with the overtone vibration of C-H bond, which can provide the lipid-specific contrast (Wang,
Wang et al. 2012). Studies has shown that 1.7 µm is the best wavelength for intravascular imaging
due to the high absorption coefficient and less scattering by blood (Wang, Karpiouk et al. 2012,
Wang, Wang et al. 2012). However, by taking account of the water absorption, 1.7 µm is not
always the optimal excitation in all the cases. It has been demonstrated that if the excitation light
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travels more than 4 mm to reach the lipid deposition inside the artery, it is better to use 1.2 µm
excitation due to less excitation attenuation by water absorption (Wang, Wang et al. 2012). In our
experiment configuration, the inner diameter of the artery is only ~3mm, but the distance between
the fiber tip and the mirror reflector is ~ 1.5 mm. Thus there are a ~3 mm space between the fiber
tip and the surface of the probe, in which the excitation light traveled. Moreover, considering
gaining the depth information of the arterial wall (>2 mm), we chose to use 1.2 µm excitation to
avoid the attenuation from water and obtain the best signal inside the arterial wall. For smaller size
transducer and coronary artery applications, it is still better to use 1.7 µm excitation for the imaging
of lipid-laden plaque.
Raman laser is not tunable. Therefore, it is hard to perform a multi-wavelength imaging
through a Raman laser, although multi-wavelength imaging has been proved an effective way to
differentiate tissue types in artery tissue (Wang, Wang et al. 2012, Jansen, van der Steen et al.
2014). From the practical point of view, however, there are three major reasons that single
wavelength excitation should potentially be applied instead of multi-wavelength imaging: 1)
Compared to the fibrous tissue or smooth muscle tissue, lipid core has over 10 fold of C-H bond
density. This contrast has been proved to be enough to separate lipid core with other tissue. 2) It
is true that the current reported work shows that the calcified tissue gives PA signal as well, which
is biggest contrast ambiguity we are facing (Jansen, van der Steen et al. 2014). However, since the
IVPA imaging will be performed with IVUS imaging together, the image of IVUS will help to
clarify the contrast ambiguity. 3) Building multi-wavelength excitation and scanning system will
be costly and increase the procedure time. Giving the above reasons, we believe that the additional
information provided by multi-wavelength imaging does not justify the cost and prolonged
procedure time.
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The major reason of choosing the MOPA system as the pump source is its high beam
quality. The beam quality of 1064 nm output from the free space amplifiers is measured to be M
2

= 1.6, which is owing to the utilization of a polarization-maintaining single-mode fiber in fiber
amplifier before the free space amplifiers. This high-beam quality ensured the high conversion
efficiency of the Raman shifter. Moreover, the pulse duration of the MOPA system is tunable. It
is known that the bandwidth of photoacoustic response is dictated by optical excitation pulse
duration and relaxation response of the sample. Although the general paradigm for photoacoustic
imaging is that the optimal pulse duration is around 5 ns to 10 ns, but the optimal pulse duration
for IVPA imaging using high-frequency transducer is still unknown. The pulse-duration-tunable
MOPA system can potentially provide us the answer.
In summary, the high repetition rate Raman laser breaks the bottleneck of translating IVPA
system to medical setting by improving the imaging speed by 2 orders of magnitude. It is foreseen
that this advancement in laser development will facilitate the clinically application of IVPA
technology.

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Chapter 6 Confocal Acoustic Radiation Force Optical Coherence
Elastography (ARF-OCE)
6.1 Development of ARF-OCE
6.1.1 Overview of Elastography Technology
Knowledge of tissue mechanical properties provides valuable medical information in
disease diagnosis and prognosis. There is a close correlation between tissue elasticity and
pathology. For example, measurement of tissue biomechanical properties has potential to
differentiate between various plaque components in atherosclerosis. Furthermore, tissue
mechanical properties provide critical information to assess the vulnerability of plaques.(de Korte,
Sierevogel et al. 2002, de Korte and van der Steen 2002, Rogowska, Patel et al. 2004, Baldewsing,
Schaar et al. 2005, Allen, Ham et al. 2011). The stress in the cap increases with decreasing
thickness, as well as increasing macrophage infiltration. High strain locations in the vessel wall
indicate the presence of vulnerable plaques (de Korte, Sierevogel et al. 2002, de Korte and van der
Steen 2002, Baldewsing, Schaar et al. 2005, Allen, Ham et al. 2011).
Tissue mechanical properties can be acquired by monitoring tissue’s deformation
responses to external force applied onto the tissue. Young’s modulus (E), shear modulus (μ) and
Poisson’s ratio (ν) are commonly used to represent elasticity of the material, where E is defined as
the resistance to deform in longitudinal compression, μ describes the resistance to deform in
transverse direction and ν is defined as the deformation that occurs orthogonal to that of the
external force. When considering soft tissue as a homogenous, isotropic, linear elastic material,
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elasticity of soft tissue can be expressed by three aforementioned parameters as the following
equations: 𝐸𝐸 =
𝜇𝜇 ( 3 𝜆𝜆 + 2 𝜇𝜇 )
𝜆𝜆 + 𝜇𝜇 , 𝑣𝑣 =
𝜆𝜆 2( 𝜆𝜆 + 𝜇𝜇 )
, and 𝜇𝜇 =
𝐸𝐸 2( 1 + 𝜈𝜈 )
, where λ is the Lame constant.
Elastography is an imaging-based technology to quantify tissue mechanical properties by
monitoring tissue’s responses when internal or external force is applied to deform the tissue.
Elastography is able to differentiate tissues based on their elasticity difference. This technology is
crucial especially for the tissues with similar morphological features that cannot be discriminated
by regular imaging modalities. Four critical steps to construct elastography imaging are illustrated
in Figure 6-1.

Figure 6-1: Four critical steps to construct elastography imaging.

Magnetic resonance elastography (MRE) (Mariappan, Glaser et al. 2010) and ultrasound
(US) elastography (Ophir, Cespedes et al. 1991) have been translated into clinical use to quantify
mechanical properties at tissue and organ level for years. Comparison of different elasticity
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measurements between MRE and US Elastography is summarized in Table 6-1 (Sarvazyan, Hall
et al. 2011). MRE is a phase-contrast-based MRI imaging technique. MRE is capable of
quantitatively predicting the shear modulus of the subject by visualizing and quantitatively
measuring propagating acoustic strain shear waves induced by harmonic mechanical excitation.
Ultrasound is another elasticity imaging modality intensively used (de Korte, van der Steen et al.
2000, de Korte and van der Steen 2002, Talwalkar, Kurtz et al. 2007). This technique demonstrates
great potential for assessing tissue stiffness by using either speckle tracking or Doppler velocity
method. Both methods have been currently applied for diagnosis of cancers, intravascular diseases,
and liver fibrosis (de Korte, van der Steen et al. 2000, Plewes, Bishop et al. 2000, de Korte and
van der Steen 2002, Woodrum, Romano et al. 2006, Talwalkar, Kurtz et al. 2007, Yin, Talwalkar
et al. 2007). However, resolution of these techniques, usually ranges from a few hundred
micrometers to several millimeters, limits their clinical acceptance, especially in detection of small
atherosclerotic lesions and plaque composition analysis in small arteries.
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Table 6-1: Comparison of different elasticity measurement and imaging methods, adapted from
(Sarvazyan, Hall et al. 2011).

Optical Coherence Elastography (OCE) is a novel elasticity imaging technique that is being
investigated and developing rapidly in recent years (Rogowska, Patel et al. 2004, Khalil, Chan et
al. 2005, Ko, Tan et al. 2006, Wang, Ma et al. 2006, Kennedy, Hillman et al. 2009, Kennedy, Liang
et al. 2011, Qi, Chen et al. 2012, Razani, Mariampillai et al. 2012). Using traditional optical
coherence tomography technique, OCE overcomes the resolution limitation of MRE and US
elastography techniques by detecting nano-to-micron-scale internal local deformation of the
subject. OCE is used to measure shear wave (Razani, Mariampillai et al. 2012), longitudinal
vibration (Qi, Chen et al. 2012), and surface acoustic wave propagation (Li, Guan et al. 2012),
which are further used to quantify shear modulus or Young’s modulus. OCE technique has been
applied to investigate biomechanical properties of both engineered tissue and living tissue, such as
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skin, muscle, cornea, and blood vessels (Rogowska, Patel et al. 2004, Adie, Liang et al. 2010,
Kennedy, Liang et al. 2011, Manapuram, Aglyamov et al. 2012, Qi, Chen et al. 2012). However,
current OCE techniques are mostly used to detect the shear wave propagation which greatly limits
imaging speed . There are OCE methods using dynamic excitation to achieve high speed as well.
However, the mechanical loading method limits their accessibility to internal organs, such as
arteries and retina. Therefore, it’s still a great challenge to apply OCE techniques for in vivo
intravascular imaging and ophthalmic imaging.
6.1.2 Acoustic Radiation Force (ARF) Excitation Method
Among several elastographical imaging modalities being investigated, ultrasound
elastography is the most commonly used method in clinic (Wells and Liang 2011). In traditional
ultrasound elastography, the manual palpation method, which generates a compressional force to
the tissue via a plate or the transducer itself, is applied. The deformation induced by the
compressional force is then measured to assess the tissue’s elasticity (Ophir, Cespedes et al. 1991).
However, the heavy dependence on the physicians’ experiences and skills limits the clinical use
of this technique. In order to overcome this limit, acoustic radiation force (ARF), generated during
the propagation and attenuation of ultrasonic wave within the tissue, has been used to deform the
tissue in a more accurate and controllable manner (Nightingale, Palmeri et al. 2001). At any given
location, the ARF can be expressed as

𝐹𝐹 =
2 α I
c
(Equation 6-1)
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where F is the acoustic radiation force in kg/s
2
cm
2
, α is the absorption (i.e., attenuation) coefficient
in Np/cm, I is the time-average intensity of acoustic wave in W/cm
2
, and c is the speed of sound
in the medium in cm/s. As shown in the equation, speed of acoustic wave remains constant within
a homogenous medium at a certain temperature. Therefore, the absorption and intensity of the
acoustic wave are the two major factors affecting the magnitude of ARF. In order to generate
sufficient ARF to induce detectable displacements in the soft tissue (1-10 μm), a focused transmit
beam is usually used to generate high intensity acoustic waves by using higher power and/or longer
duration excitations. The absorption coefficient is proportional to the square of center frequency
of acoustic waves, which means that increasing center frequency would potentially enhance the
momentum transfer to the medium, thus increasing the acoustic radiation force. However, the
strong absorption of high frequency acoustic wave makes it hard to reach a sufficient intensity
level and consequently limits the penetration depth. Therefore, the center frequency of the
excitation transducer has to be selected with considering the tradeoffs between the penetration
depth and intensity of acoustic waves.
As illustrated in Figure 6-2, there are three major types of ARF excitation methods
(Doherty, Trahey et al. 2013). The quasi-static method uses a long duration pulse train to deform
the tissue with a fixed ARF amplitude, and both of the steady-state tissue response and the
relaxation response can be used to characterize the mechanical properties of the tissue (Nightingale,
Palmeri et al. 2001). The transient method utilizes a short duration toneburst (0.01-1 ms) to attain
the transient deformation response of the tissue. Many ARF-based US elastography techniques,
such as acoustic radiation force impulse (ARFI) imaging (Nightingale 2011), supersonic shear
wave imaging (SSI) (Bercoff, Tanter et al. 2004), and shear wave elastography (SWE) (Sarvazyan,
Rudenko et al. 1998), use this impulse-like exciation to quantify the elasticity of soft tissue.
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Harmonic excitation is another method to generate dynamic ARF and create localized vibration of
the soft tissue. The dynamic ARF can be created in two ways: (a) using amplitude modulated (sine
wave or square wave) ultrasound by a single focused transducer, such as harmonic motion imaging
(HMI) (Maleke, Pernot et al. 2006, Maleke and Konofagou 2008, Vappou, Maleke et al. 2009,
Maleke, Luo et al. 2010); (2) using the interference of two ultrasound beams with slightly
difference, such as vibro-acoustography (Fatemi and Greenleaf 1998). This vibrational response
under the harmonic ARF excitation can be also used to assess the mechanical properties of soft
tissue.

Figure 6-2: Three major ARF excitation method: (a) quasi-static excitation method, (b) transient
excitation method, and (d) harmonic excitation method.

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6.1.3 Concept of ARF-OCE
Basic development concept of ARF-OCE is shown in Figure 6-3. Ultrasonic transducer
provides external excitation to tissue by generating dynamic acoustic radiation force. Localized
vibration is generated by low frequency oscillation within focal zone of the focused ultrasonic
transducer, which leads to more accurate excitation and easy detection. A SDOCT system is used
to detect the ARF-induced vibrational movement and also acquire imaging data. Based on phase-
resolved OCE algorithms, mechanical properties of tissue, especially relative Young’s modulus
can be quantified to construct elastogram.

Figure 6-3: Development of concept of ARF-OCE.

Schematic diagram of ARF-OCE system is shown in Figure 6-4. The integrated system
consists of two subsystems: an OCT subsystem as detection unit and an ultrasound subsystem as
stimulation unit (Qi, Chen et al. 2012). Acoustic radiation force was generated by a focused
ultrasound transducer, which transmitted 4 MHz ultrasound waves with a lateral focal width of 2.3
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mm and a length of 18 mm at a working distance around 60 mm. The ultrasound focus located on
the surface of the phantom along Z-axis. An RF power amplifier, with a linear gain of 46 dB
between 0.15 MHz and 230 MHz, amplified the signals that drive the transducer. To create a cyclic
acoustic radiation force, the ultrasound transducer was driven by a signal that was amplitude-
modulated (AM) by a square wave. A function generator and a pulse delay generator were used to
create the AM waveform, which drove the ultrasound transducer after power amplification. The
pulse delay generator generated a low kHz square wave (50% duty cycle amplitude modulation-
AM) which modulated the amplitude of the 4 MHz burst generated by the function generator. The
modulation frequency and amplitude were chosen for each sample in such way that the absolute
value of the phase difference induced between adjacent A-lines is large to enhance the sensitivity
but less than to avoid phase wrapping. For ex-vivo imaging, the sample was scanned within
the focal area of the transducer, where we assumed that the acoustic radiation force is evenly
distributed. The local vibration phase of the sample is detected by a phase-resolved OCT system,
which is capable of imaging at a frame rate of 20 kHz with a 3.5 µm axial resolution.
Phase resolved Doppler OCT method, which decouples velocity sensitivity and imaging
speed by using phase change between sequential A-scans to calculate particle velocity, was used
to calculate ARF-induced sample displacement (Zhao, Chen et al. 2000). Based on the Doppler
Effect, the frequency change of moving source is defined as

𝑓𝑓 𝐷𝐷 =
2 𝑣𝑣 co s 𝜃𝜃 𝜆𝜆 0
(Equation 6-2)

where fD is the Doppler frequency shift, v is the velocity of moving source, 𝜃𝜃 is the angle between
the incident light and the moving particle, and 𝜆𝜆 0
is the center wavelength of the light source.
| π |
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The phase-resolved OCT method measures the particle motion induced phase shift from
the complex depth encoded fringe signal S
�
( 𝑧𝑧 )

S
�
( 𝑥𝑥 , 𝑧𝑧 , 𝑡𝑡 ) = 𝐴𝐴 ( 𝑥𝑥 , 𝑧𝑧 , 𝑡𝑡 ) 𝑒𝑒 𝑎𝑎 ∆ 𝜑𝜑 ( 𝑎𝑎 , 𝑧𝑧 , 𝑙𝑙 )
(Equation 6-3)

where, x represents the lateral location, z represents the axial location, and 𝐴𝐴 ( 𝑥𝑥 , 𝑧𝑧 , 𝑡𝑡 ) and
∆ 𝜑𝜑 ( 𝑥𝑥 , 𝑧𝑧 , 𝑡𝑡 ) are the amplitude and phase of the fringe signal, respectively. The frequency shift is
determined by the cross-correlation between A-scans:

𝑓𝑓 𝐷𝐷 =
∆ 𝜑𝜑 ( 𝑎𝑎 , 𝑧𝑧 , 𝑙𝑙 )
2 𝜋𝜋 𝑚𝑚 τ
(Equation 6-4)

where 𝑛𝑛 ≈ 1.38 is the index of refractivity of tissue and τ is the integration time for CCD camera.
Thus, the moving source’s velocity can be calculated as:

𝑣𝑣 ( 𝑥𝑥 , 𝑧𝑧 , 𝑡𝑡 ) =
∆ 𝜑𝜑 ( 𝑎𝑎 , 𝑧𝑧 , 𝑙𝑙 )
4 𝜋𝜋 𝑚𝑚 τco s 𝜃𝜃 (Equation 6-5)

Within a certain customized time window, the displacement d and the axial strain ε of the sample
are expressed as

𝑑𝑑 = ∫
Δ 𝜙𝜙 ( 𝑎𝑎 , 𝑧𝑧 , 𝑙𝑙 ) 𝜆𝜆 0
4 𝜋𝜋 𝑚𝑚 τ
𝑑𝑑𝑡𝑡
𝑙𝑙 2
𝑙𝑙 1
(Equation 6-6)
ε = ∫
Δ 𝜙𝜙 ( 𝑎𝑎 , 𝑧𝑧 , 𝑙𝑙 ) 𝜆𝜆 0
4 𝜋𝜋 𝑚𝑚 τ z
0
𝑑𝑑𝑡𝑡
𝑙𝑙 2
𝑙𝑙 1
(Equation 6-7)
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Where z0 is the original thickness of the sample. Thus, the Young’s Modulus E can be estimated
as:

𝐸𝐸 =
𝜎𝜎 𝜀𝜀 (Equation 6-8)

To differentiate tissue with difference elasticity, where 𝜎𝜎 is the axial stress acting on the sample.

Figure 6-4: Schematic diagram of spectral-domain ARF-OCE system. SLD: superluminescent
diode, CCD: charge-coupled device, US: ultrasonic transducer, FG: function generator.

6.2 Resonant Frequency ARF-OCE
We have presented a resonant ARF-OCE technique, which takes advantage of the fact that
materials respond primarily at their mechanical resonant frequencies, to effectively distinguish
samples with varying stiffness. This method provides a significant contrast to previously reported
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acoustic radiation force optical coherence elastography technique (Qi, Chen et al. 2012). Resonant
frequencies of silicone phantoms with different Young’s modulus were investigated first with a
focused ultrasound transducer that generated local acoustic radiation force stimulation at step-
driven frequencies on the phantoms. A well fitted linear dependency curve of the resonant
frequency on the square root of Young’s modulus was presented and thus validated the hypothesis
of the method. To demonstrate the potential of the resonant ARF-OCE technique for medical
diagnosis and prognosis, we furthermore performed the resonant ARF-OCE measurement on a
section of post-mortem human coronary artery with atherosclerotic plaques. A 2D OCT-structural
image and a relative ODT phase map were presented and correlated with the histological image.
The phase map identified regions of thin loose and thick dense fibrous cap with excitation
frequencies of 500 Hz and 800 Hz, respectively. The results of the current study demonstrate the
capability of the resonant ARF-OCE method as a non-invasive assessment of vulnerability of
atherosclerotic plaques with the potential application in clinical settings in the future.
6.2.1 Principle of Resonant Frequency
The mechanical resonant frequency of material in response to external force is closely
related to its elastic properties. The resonance frequency measurement techniques, such as resonant
ultrasound spectroscopy, have been employed for decades to assess the elastic moduli in
nondestructive evaluation of materials with known shape (Migliori, Sarrao et al. 1993). Realizing
that biological samples also exhibit mechanical resonance inherent to the samples, investigators
have developed a variety of resonance frequency imaging techniques to evaluate the corresponding
elastic moduli (Migliori, Sarrao et al. 1993, Fatemi and Greenleaf 1998, Lee, Lakes et al. 2002,
Muller, Sutin et al. 2005, Taeyong, Wen-Ming et al. 2008, Oldenburg and Boppart 2010). However,
110

these existing techniques have limited sensitivity and are difficult to be adapted for in vivo imaging.
Recently we have developed a phase-resolved ARF-OCE system that uses an amplitude modulated
(AM) acoustic wave to apply dynamic pressure to the tissue and uses phase-resolved OCT to
evaluate the elastic properties of vascular tissue (Qi, Chen et al. 2012). The phase resolved ARF-
OCE combines the high-speed excitation of ARF with sub-micrometer/nanometer detection
sensitivity of phase resolved OCT to achieve high speed and high sensitivity mapping of elastic
properties of tissue, which has great potential for clinical cardiovascular imaging. However, while
relative value of strain and Young’s module can be imaged with ARF-OCE, the absolute
determination of these biomedical properties requires knowledge of ARF applied to the tissue.
Although ARF can be determined by simulation and calibration, adaption for in vivo quantification
with constant change in geometry will be a significant challenge. In this section, we report a
resonant phase resolved ARF-OCE technique utilizing the mechanical resonant frequency to
imaging and quantifying tissue mechanical parameter without knowledge of ARF parameters.
Using the ARF as excitation allows us to sweep different ARF frequencies and measure the
frequency dependent displacement in order to determine tissue resonance frequency, which can be
used to imaging and quantifying the tissue mechanical properties.
Biological solid soft tissues, behaving intermediately between liquid and solid-elastic
materials, are considered as viscoelastic materials, which usually be described by the Voigt model.
This model is composed of combinations of a linear spring with elastic constant and a dashpot
k
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with coefficient of viscosity . Under external force stimulation, this model can be described by
(Liang, Oldenburg et al. 2008)

(Equation 6-9)

where 𝑚𝑚 is the mass of the sample, 𝑧𝑧 ( 𝑡𝑡 ) is the local displacement of the sample and 𝐹𝐹 ( 𝑡𝑡 ) is the
acoustic radiation force exerted on the sample. When the deformation is small (<0.1%), the elastic
constants of soft tissues can be assumed to be linear(Sun, Standish et al. 2011). Given the
displacement of the sample, one can determine 𝛾𝛾 and 𝑘𝑘 and thus solves the Young’s modulus
under Hook’s Law

(Equation 6-10)

where and is the thickness and area of the sample, respectively. The damping coefficient
is defined as (Liang, Oldenburg et al. 2008)

(Equation 6-11)

For a certain material, the damping coefficient is constant. Therefore there exists a linear
relationship between the square root of the modulus and the resonant frequency of the sample with
a fixed geometry.
To test this linear relationship, the frequency responses of silicone phantoms with varying
Young’s moduli were measured using our resonant ARF-OCE method by applying step frequency
γ
) ( ) ( ) ( ) ( t F t kz t z t z m = + +    γ
S mL A kL E ) (
2 2
λ ω + = =
L A
λ
m 2 γ λ − =
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excitations. Several homogenous silicone phantoms with different silicone to activator ratios were
fabricated and tested to find the exact Young’s Moduli. The picture of phantom and testing results
is shown in Figure 6-5. For each phantom, the displacement of sample at different swept
frequencies was recorded and plotted with a polynomial curve fitting in Figure 6-6. The respective
frequency with maximum displacement was considered as the resonant frequency of the sample.
Figure 6-7 shows the linear dependency of the resonant frequency square on the corresponding
Young’s modulus of the material with an R
2
coefficient close to 1, confirming the linear
relationship and showing the potential for inverting resonant frequency to differentiate materials
with varying stiffness.

Figure 6-5: Displacement at varying frequencies of two silicon phantoms. The resonant frequency
is defined as the frequency where the peak displacement located.

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Figure 6-6: Displacement at varying frequencies of two silicon phantoms. The resonant frequency
is defined as the frequency where the peak displacement located.

Figure 6-7: Linear dependency curve of resonant frequencies on varying Young's Moduli of
silicone tissue phantoms.

6.2.2 Imaging Results and Discussion
To demonstrate the mechanical contrast of the resonant ARF-OCE method, we first tested
an agar phantom with a metal ball embedded inside. The measured frequency response
spectrogram of agar and metal ball were plotted in Figure 6-8.With different vibrational amplitudes
due to significant elastic property differences, very strong resonances at 60 Hz and 1080 Hz were
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observed for the agar and stainless steel ball, respectively. This indicates that if a driving frequency
of 1080 Hz were to be applied to the sample, one should be able to differentiate the stainless steel
ball from the surrounding agar. We imaged the agar phantom under a modulation frequency of
1080 Hz, which is the resonant frequency of the stainless steel ball. As expected, the metal ball
produced a distinctive vibration amplitude in comparison to the surrounding agar, yielding high-
contrast in the resonant elastography map (Figure 6-8 (b)). Only the top of the metal ball can be
seen in the images due to the highly reflective index of the material.

Figure 6-8: (a) Frequency response spectrogram of agar and metal ball. M-mode vibration phase
amplitude was recorded while the targeting point was stimulated by amplitude modulated acoustic
radiation force. The modulation frequency was swept over a range of 50 Hz to 1600 Hz, covering
the resonant frequency of both materials. The resonant frequency of agar and metal ball were 60
Hz and 1080 Hz, respectively. (b) 3D OCE image. (c) The sample image. The area within the red-
dash box was the imaging area.

Finally, to test the feasibility of applying this resonant ARF-OCE technique to image and
differentiate atherosclerotic plaques, an ex vivo resonant ARF-OCE imaging of a section of post-
mortem human coronary artery was performed at varying frequencies. During the experiment, the
human coronary was immersed in PBS buffer solution, which serves as both the coupling media
for the ultrasonic wave and also the bio-environment for the tissue, and laterally scanned 3.5 mm
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within the focal area of the ultrasonic transducer where the vibration of the sample induced by the
acoustic radiation force was assumed to be evenly distributed. After ARF-OCE imaging, the
sample was fixed using 10% formalin solution, and sectioned for histological analysis. The
histological sections were interpreted by a pathologist who has no access to the information
provided by the resonant ARF-OCE method. The processed sample histology (Figure 6-9 (d) &
(e)) was confirmed as a necrotic core fibroatheroma with a fibrous cap, pointed by black arrows,
on top of a necrotic lipid core (NC). Region I and III of the fibrous cap are thin loose fibrous tissues
(~100 µm thickness), where the plaque is more likely prone to rupture. In region IIII, the fibrous
tissue becomes thicker and denser, which is considered as stable area of the plaque. Tiny
microscopic nodules of calcium salts are found at the boundary between the lipid core and the
fibrous cap. The structure of the NCFA was reconstructed in the OCT image (Figure 6-9(a)), due
to the limited penetration depth, only the fibrous cap and part of the lipid core can be seen in the
OCT image. The structure revealed in the OCT image corresponded really well with the
histological sections (Figure 6-9 (d)). The resonant ARF-OCE distinguished different components
in the plaque at varying frequencies. The thin loose fibrous cap (region I and III) showed higher
resonant amplitude at 500 Hz driving frequency (Figure 6-9 (b)), as opposed to the thick dense
fibrous cap (region II) which showed very weak vibration at this frequency. Conversely, when the
sample was excited under 800 Hz, the thick dense fibrous cap portion started to show stronger
motion than the portion with thin loose fibrous cap. In Figure 6-9 (c), the left part of thin fibrous
cap shows higher vibration than that on the right side of the image. This may resulted from the
calcium salts deposit on the left of the plaque, where higher reflection for the acoustic radiation
force induced relative stronger vibration than the area without microscopic calcium nodules. Since
the mechanical characteristics of the fibrous cap determines the stability of the plaque, the
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resonant-ARF-OCE method could provide useful mechanical information about the fibrous cap,
thus may serve as a predictor of the atherosclerotic plaque stability and provide useful information
during clinical interventions, such as stent and balloon catheter insertion.

Figure 6-9: Frequency response of human coronary artery. (a)OCT morphological image of the
coronary artery segment in the dotted area in (e), (b) (c) resonant-ARF-OCE images showing
frequency response at 500 Hz and 800 Hz. A higher vibration amplitude is measured on the left
and right side of the resonant-ARF-OCE image (b) at 500 Hz, corresponding to the thin loose
fibrous cap. High vibration is detected at 800 Hz at the center of the NCFA (c) corresponding to a
thicker and denser portion of the fibrous cap. (d) and (e) Histological sections showing a necrotic
core fibroatheroma (NCFA) with a fibrous cap (arrow) overlying a large necrotic lipid core (NC).
(d) Close-up view of the scanned area of plaque (dotted area in (e)).

6.3 Confocal ARF-OCE by Using Single Ring Transducer
We designed and developed a novel confocal acoustic radiation force optical coherence
elastography system. A ring ultrasound transducer was used to achieve reflection mode excitation
and generate an oscillating acoustic radiation force in order to generate displacements within the
tissue which were detected using the phase-resolved optical coherence elastography method. Both
phantom and human tissue tests indicate that this system is able to sense the stiffness difference of
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samples and quantitatively map the elastic property of materials. Our confocal setup promises a
great potential for point by point elastic imaging in vivo and differentiation of diseased tissues
from normal tissue.
6.3.1 Limitation of Previous ARF-OCE System
The previous reported system used a transmission mode where the ultrasound transducer
and optical detection were located on opposite sides of the tissue. In order to have compatibility
with a catheter design for intravascular imaging, in this paper, we have further improved the system
by using a ring transducer to achieve co-registered excitation and detection from the same tissue
side. The benefit from this confocal configuration is that the adaptation for an endoscopic probe
can be achieved by using the confocal configuration. Moreover, because of the high sensitivity of
phase-resolved OCT, only minimal force needs to be applied to the object in order to generate the
elastogram, which is most desirable for non-invasive intravascular imaging. Finally, the newly
proposed system configuration provides more accurate local displacement information and holds
promise for in vivo endoscopic intravascular elastography for imaging and quantifying
atherosclerosis as well as ophthalmic elastography for imaging and quantifying drusen deposition
in age related macular degeneration disease.
6.3.2 Confocal ARF-OCE and Ring Transducer Characterization
The schematic of the confocal ARF-OCE system is shown in Figure 6-10 (a). The system
is based on an 890 nm SD-OCT system. The acquisition rate of this system was 20 kHz. The axial
and lateral resolutions of the system were measured to be 3.5 and 14.8 μm, respectively. The
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signal-to-noise-ratio (SNR) of the system was 100 dB with 650 μW of sample arm power and a
50-μs A-line rate. The minimum detectable phase for this system was measured to be 1.5 mrad,
which corresponded to a velocity sensitivity of 2.13 μm/s and a displacement sensitivity of less
than 1 nm. A water cell was inserted in the reference arm in the SD-OCT system to compensate
for the dispersion induced by the water in the sample arm.
Unlike our previously published experimental setup with a transmission mode where the
ultrasound transducer excites the sample from the bottom and optical detection is from the opposite
direction, this new experimental design features a reflection mode. In this configuration, the
acoustic excitation and OCT detection are arranged in a way so that the light and the ultrasound
shine on the sample from the same side and completely overlap with each other at the focal point
where the sample will be placed. A custom-made focused-ring ultrasound transducer Figure 6-10
(b) with a 5 mm hole at the center to make room for the OCT probing beam was used to achieve
the reflection confocal mode. Hard PZT material was used to fabricate the ring transducer because
it can be subjected to high electrical and mechanical stresses and their properties experience little
change under these conditions. The advantages of these PZT materials are the moderate
permittivity, large piezoelectric coupling factors, high qualities and very good stability under high
mechanical loads and operating fields. The inner hole diameter is made around 5 mm, which allows
the OCT beam to scan a small area. The outer diameter of the ring transducer is around 30 mm.
The height of the transducer is designed to be 10 mm so that there will be more space for
adjustment when combined with the OCT system.

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Figure 6-10: (a) Schematic of the confocal ARF-OCE system, including a SD-OCT system and a
customized focused ring transducer (4 MHz) transducer with a 30mm aperture and a 5mm inner
hole.

In this configuration, the acoustic excitation and OCT detection are arranged in a way so
that the light and the ultrasound shine on the sample from the same side and completely overlap
with each other at the focal point where the sample will be placed. To generate enough acoustic
radiation force at 50mm focal depth and coordinate with the optical scanning set-up, the center
frequency of ultrasonic transducer was designed to be 4MHz and stable piezoelectric ceramic PZT
was selected as the functional material. The acoustic induced vibrational area was directly related
to the beam diameter of the ultrasonic transducer defined in the following equation:

𝐵𝐵𝐵𝐵 = 1.02 ∗ 𝐹𝐹 # ∗ �
𝑐𝑐 𝑓𝑓 � (Equation 6-12)

where BD is the beam diameter (-6dB), F# is the ratio of the focal depth and diameter of the ultrasonic
transducer, c is the speed of sound and f is the center frequency. Similarly to the articles reported by Sun et
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al.,(Sun, Park et al. 2009, Sun, Chaudhari et al. 2011) the acoustic output and sensitivity of the ring
transducer would be reduced compared to a standard focused transducer due to loss of inner functional
material. However, according to the Field II simulation in Figure 6-11 (b), the acoustic beam characteristics
of the ring transducer at the focal zone did not have significant change. Therefore, the ring transducer could
still provide similar OCT-detectable displacements in the focal zone as a standard focused transducer.
Because the focal length of the US transducer is 50 mm, an objective lens with a 70 mm focal length in the
OCT detection arm was used so that the focal point of the US transducer and the OCT probing light could
overlap with each other.

Figure 6-12: Ring transducer design: (a) photograph of the ring transducer with 30mm diameter
and 10mm height and a 5 mm hole, and (b) 2D intensity profile from Field II simulation.

To quantitatively evaluate the performance of the ring transducer, an acoustic output
measurement is performed. The testing condition is similar to the actual experiment condition: 200
mVpp with 50 dB amplification driving voltage, 10-cycle burst sine wave and 200 Hz pulse
reputation frequency. The acoustic output wave and spectrum at the focal point is shown in Figure
6-12 and the acoustic output parameters of FDA guideline are shown in Table 6-2.
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Table 6-2: Acoustic output parameters (Hydrophone test).
Center Frequency 4.06 [MHz]
Bandwidth(-6dB) 0.55 [MHz]
Fractional Bandwidth(-6dB) 13.5%
Pulse Duration 2.3 [us]
Focal Depth 49.8 [mm]
Spatial peak-temporal average intensity ISPTA 75.00235 [mW/cm
2
]
Spatial peak-pulse average intensity ISPPA 162.69 [W/cm
2
]
Pressue (Pr) 3.02256 [MPa]
Mechanical Index (MI) 0.74747

Figure 6-13: Acoustic output wave (a) and spectrum of the output wave (b) at the focal point.

The axial acoustic output profile and lateral output profiles are shown in Figure 6-13 and
Figure 6-14. As shown in Figure 6-13, the ring transducer has a depth of focus of 5 cm and a -6dB
beam width of 1 mm along the axial direction. The lateral beam profile of this ring transducer was
shown in Figure 6-14. At the focal plane (z=5 cm), the ring transducer has -6dB beam width of 0.5
mm with the maximum acoustic output. The acoustic field 1cm away from the focal plane (z =
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4cm and z = 6cm) has a medium acoustic output but relatively uniform distribution. The
measurement results indicate that the focal plane (z = 5 cm) would allow large vibration amplitude
and small insonation area. Moreover, the near field plane (z = 4 cm) and far field plane (z = 6 cm)
would provide medium vibration amplitude and relatively large insonation area.

Figure 6-14: Relative acoustic output amplitude (left) and relative pulse intensity integral (right)
along axial direction. The x-axis in this plot is axial direction z = 0 refers to the focal depth (axial
position of 5cm away from the surface of transducer).

Figure 6-15: Acoustic output amplitude (left) and relative pulse intensity integral (right) along
lateral direction at different axial position (z=2cm, z=3cm, z=4cm, z=5cm and z=6cm).

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6.3.3 Imaging Results and Discussion
An experiment from a homogeneous phantom confirmed that the ARF induced
displacement was uniform over a 1.5 mm lateral length, as shown in Figure 6-15. The OCT
intensity image (Figure 6-15 (a)) provided the structural information of the phantom. The ARF-
OCE image (Figure 6-15 (b)) associated with the phase map shows displacements of the particle
in the sample. Since the light beam width is about 14.8 µm, which is much less than the ultrasound
beam width and the acoustic field is evenly distributed, it allows the light to scan within a 1.5 mm
length. For all the experiments, the scanning area was confined within a 0.5 mm x 0.3 mm area
where we assumed that the acoustic field was uniform. The transducer was driven by a signal that
was amplitude modulated by a square wave to generate a periodic acoustic radiation force
perpendicularly onto the sample. The pulse delay generator (DS345, Stanford Research Systems,
USA) generated a low kHz square wave (50% duty cycle amplitude modulation-AM) which
modulated the amplitude of the 4 MHz burst generated by the function generator (33220A, Agilent
Technologies, USA). Then the modulated signal was amplified by a RF power amplifier (PAS-
000023-25, Spanawave, USA), with a linear gain of 46 dB between 0.15 MHz and 230 MHz.
Lateral scans were only made within the ultrasound focal zone where we assumed that the acoustic
radiation force that was used to induce particle displacement was evenly distributed.

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Figure 6-16: Scanning area validation on a homogeneous silicone phantom with 1.5 mm lateral
scan. (a) OCT intensity image and (b) phase map induced by 800 Hz ARF excitation on the
phantom.

The feasibility of the proposed confocal ARF-OCE system was first investigated on
silicone phantoms with different stiffnesses which were controlled by the ratio of silicone to its
associated activator. The displacement of the sample over time, which is used to quantify the tissue
stiffness is linearly proportional to the adjacent A-line phase shift at each lateral location and was
calculated. From the ARF-OCE measurement (Figure 6-16), the displacements were 0.198 µm for
the silicone phantom with a 1:30 ratio of the silicone to the activator and 0.28 μm for the second
phantom with a ratio of 1:26, respectively. The Young’s moduli for phantoms with 1:26 and 1:30
ratio of the silicone to the curing agent were 75.1 and 53.7 kPa, respectively, which were measured
under a compression test yielding a Young’s modulus ratio around 1:1.40, similar to the calculated
displacement ratio from our ARF-OCE measurements of 1:1.41. The results indicate that the
displacement from our confocal ARF-OCE system is able to provide a reliable relative Young’s
modulus for the materials.

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Figure 6-17: Axial displacements of silicone phantoms with different stiffness. R: ratio of the
silicone to the related activator.

We further characterized our confocal ARF-OCE system on an agar phantom with a
stainless steel sphere (513µm in diameter) embedded in the center. The phantom was placed about
50mm below the surface of the US transducer and immersed in water. While the phantom was
stimulated at a square wave modulation frequency of 1050 Hz, 3D scans, consisting of 150 frames,
were made at 9.8 frames per second with 2048 A-lines per frame, covering a 0.5 mm by 0.3 mm
area over the sphere (Figure 6-17 (c)). The elastograph was reconstructed afterwards. Due to the
penatration limitation for OCT imaging, only the top portion of the stainless steel ball is shown in
the images. From the 2D elastograph, we observed a substantial difference in the vibration
amplitude between the sphere and the agar. As expected, the surface of the sphere and the area
above produced distinctive phase vibrations compared with the rest of the phantom, yielding a
high contrast area in OCE images (Figure 6-17 (a-b)). The results indicates that our confocal ARF-
OCE system can efficiently differentiate materials of different stiffness.
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Figure 6-18: 2D and 3D ARF-OCE (a~b) and the sample image of agar phantom (c) with a stainless
steel sphere embedded inside stimulated at a fixed frequency of 1050 Hz. The surface of the metal
ball shows distinctive vibration amplitude due to its resonance. The agar phantom, however,
vibrates much less since the driving frequency is far away from its resonant frequency.

Finally, we tested our confocal ARF-OCE technique on a section of a human cadaver
coronary artery to investigate its potential in intravascular imaging to resolve plaque composition.
Atherosclerosis is a complex disease in which multiple plaques build up within the arteries, altering
the mechanical property of the arteries. Visualizing plaques to help understand the progression of
disease and to aid in diagnosis and treatment is highly desirable. The artery sample was cut open,
flattened, mounted with a fixed bottom (Figure 6-18 (f)) and immersed in a water tank filled with
a phosphate buffered saline solution to maintain the osmolarity of the cells. A 500 Hz-square wave-
modulation frequency was applied to stimulate the tissue during the experiment. The sample was
scanned three-dimensionally over a 0.5 mm by 0.3 mm area within 15.4 seconds at the position
indicated in Figure 6-18 (f) by the red dashed box. The 0.24 µm A-line spacing used in the 3D data
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acquisition has sufficient oversampling for phase calculation. 2D and 3D structural images and
elastograms were reconstructed (Figure 6-18 (a-e)). The sample was diagnosed as fibroatheroma
with a necrotic core according the the histological information (Figure 6-18 (g)). In the 3D OCT
image, shown in Figure 6-18 (a), a general morphological view of the tissue was obtained, but no
obvious evidence of atherosclerosis was found based on the optical scattering property. However,
in Figure 6-18 (b), a strong vibration phase contrast can clearly be seen in the ARF-OCE image.
The necrotic core (NC) and fibrous cap (FC) in the plaque, identified in the histological section,
may contribute to the vibration phase difference shown in the 3D ARF-OCE image. Figure 6-18
(c), the fused OCT and OCE image illustrates the fact that ARF-OCE provides additional imaging
contrast which can be used to identify different types based on tissue mechanical properties. The
detailed correlation between pathology and the OCE map is shown in 2D images. The 2D OCT
image (Figure 6-18 (d) shows the structure of the artery segment where the distinction between
different tissue types is barely discernable. However, it is apparent thtat there is a significant
displacement difference between the FC on the top right and the NC on the left from the 2D
elastograph (Figure 6-18 (e)), which shows the elasticity difference between the two tissue types.
The dark green area represents larger phase vibrations (softer tissue) and the red color area within
the blue dashed box indicates smaller phase vibrations (stiffer tissue). These results demonstrate
the ability of our confocal ARF-OCE method to differentiate micro-scaled biomechanical property
alterations in human tissues which is especially significant when the optical scattering properties
alone cannot provide substantial evidence to identify the lesions.
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.
Figure 6-19: (a) 3D OCT image (b) 3D ARF-OCE phase image of a human cadaver coronary artery
(c) fused OCT and ARF-OCE images (d) 2D OCT (e) 2D ARF-OCE (f) sample image (g) the
histological image (h) the close up view of the atherosclerotic lesion. FC: fibrous cap. NC: necrotic
core.

6.4 Confocal ARF-OCE by Using a Dual-ring Transducer
As discussed in section 6.1.2, there are two ways to create dynamic ARF. In section 6.2
and 6.3, amplitude modulation with a single ultrasonic beam was used in ARF-OCE imaging
system. In this section, we report a method of acoustic radiation force optical coherence
elastography (ARF-OCE) based on the methods of vibro-acoustography, which uses a dual-ring
ultrasonic transducer in order to excite a highly localized 3-D field. The single element transducer
introduced previously in our ARF imaging has low depth resolution because the ARF is difficult
to discriminate along the entire ultrasound propagation path. The novel dual-ring approach takes
advantage of two overlapping acoustic fields and a few-hundred-Hertz difference in the signal
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frequencies of the two unmodulated confocal ring transducers in order to confine the acoustic
stress field within a smaller volume. This frequency difference is the resulting “beating” frequency
of the system. The frequency modulation of the transducers has been validated by comparing the
dual ring ARF-OCE measurement to that of the single ring using a homogeneous silicone phantom.
We have compared and analyzed the phantom resonance frequency to show the feasibility of our
approach. We also show phantom images of the ARF-OCE based vibro-acoustography method
and map out its acoustic stress region. We concluded that the dual-ring transducer is able to better
localize the excitation to a smaller region to induce a focused force, which allows for highly
selective excitation of small regions. The beat-frequency elastography method has great potential
to achieve high-resolution elastography for ophthalmology and cardiovascular applications.
6.4.1 Dual-ring Transducer Characterization
The schematic diagram and a photo of the dual-ring transducer are shown in Figure 6-19
(a). Both of the inner ring and outer ring transducers, made of modified hard PZT material, have
a center frequency of 2.1 MHz and a focal depth of 30 mm. During the experiment, both of the
inner ring transducer and outer ring transducer were driven by two continuous waves around 2.1
MHz with a “beating” frequency difference (100 Hz to 5 kHz). As shown in Figure 6-19 (b), at the
interference region of the two ultrasound beams, the imaging samples would undergo vibrational
movement at the “beating” frequency The imaging setup is shown in Figure 6-19 (c), which has a
same OCT detection system as discussed in the previous section 6.2 and 6.3. For the ultrasound
excitation system, two power amplifiers were used to drive the inner ring and outer ring transducer
separately.
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The results of acoustic beam profile characterization were shown in Figure 6-20. Figure
6-20 (a-c) and (d-f) display the lateral beam profile of the inner ring transducer and the outer ring
transducer, respectively. Along the lateral direction, the two transducers were aligned in a confocal
configuration. The lateral beam width of the inner ring transducer is slightly higher than that of
the outer ring transducer, and the side lobe amplitude of the inner ring transducer is lower than that
of the outer ring transducer. In both axial and lateral directions, the -6dB interference region of the
dual-ring transducer will be smaller than that of either the inner ring or the outer ring, which will
create a more localized vibration of the tissue.

Figure 6-20: (a) Schematic diagram and photography of dual-ring transducer. A center hole is
available for OCT beam delivery. (b) Illustration of beat pattern generation. The two elements of
the transducer are driven with frequencies with a Δω difference and are focused at the same
location on the sample(Fatemi and Greenleaf 1998). (c) Modified ARF-OCE imaging system set-
up.
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Figure 6-21: (a-c) Lateral beam profile of inner ring transducer. (d-f) Lateral beam profile of outer
ring transducer. (g) Axial beam profile of inner ring and outer ring transducer.

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6.4.2 Imaging Results and Discussion
The feasibility of the beating frequency approach was first tested on a homogeneous
silicone phantom. In order to make a comparison between the single ring modulation method and
the dual ring beating frequency method, we imaged a section of the same uniform silicone
phantom. In the single ring experiment, we used a function generator to directly apply a modulated
pulse whose frequency varies from 100Hz to 5000Hz. In the dual ring experiment, we used the
function generator to apply two continuous wave signals, with a “beating” frequency difference of
100Hz to 5000Hz, mimicking the same modulation frequency at the focal region. We applied a
similar pre-amplified voltage in both cases, 200mVpp to one transducer for the single ring case,
and 100mVpp to each of two transducers in the dual ring experiment. The displacement differences
are likely due to the differences in amplification of the inputs to the two transducers. Using the
principles of Doppler, we were able to obtain the average maximum vibrational displacement of
the phantom under each excitation condition for both the single and dual ring case, shown in Figure
6-21. Because the displacement values represent relative vibrational response, we verified the
feasibility of the dual ring modulation by comparing the resonance frequency. As shown in Figure
6-21, for both cases, the signal increases when the modulation is below 2000Hz, then peaks at
2000 Hz, which is the resonance frequency of the silicone phantom, and finally decreases when
frequency is greater than 2000 Hz.

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Figure 6-22: Comparison of displacement of tissue when using single ring vs. dual ring excitation.
Resonance frequency of phantom is 2000Hz.

Next, we imaged a section of a dual-layered silicone phantom using the dual ring approach,
shown in Figure 6-22. Our goal was to focus the acoustic stress field to an area near the boundary
of the two phantoms for better distinction. The resultant focal area is labeled by a red box, and
shows a boundary between the signal region and the non-signal region, especially on the upper
boundary. It is important to note that the top area above the red box shows the phantom with no
modulated signal. This means that the dual-ring transducer was able to penetrate through the top
of the phantom to focus on the region of interest, which is where the layers overlap. This is a
phenomenon that was not observed in the single ring transducer, which has a less focused axial
focal region.

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Figure 6-23: OCE image using dual ring vibro-acoustography approach showing displacement
shift of dual-layered silicone phantom at resonance frequency excitation of 2000Hz. Red box
represents focal zone.

We have developed a method of ARF-OCE using the beating frequency of two ultrasonic
transducers to generate a highly concentrated 3-dimensional focal region. The feasibility of this
method was initially tested on uniform tissue-mimicking phantoms, where we confirmed that the
signal is more highly focused in a smaller zone. We also proved that the resonance frequency of
the sample measured from the dual ring beating frequency approach is consistent with the
resonance frequency obtained from the single ring transducer method. We have performed
imaging of a two-layer silicon phantom with the beat frequency ARF-OCE. We were able to focus
the concentrated signals onto the region where the boundary between the two phantoms are, and
generate images to show the two layers. The acoustic radiation force was able to penetrate the top
of the phantom and focus directly on the region of interest. These results show that our beating
frequency ARF-OCE method can form a highly confined 3-D ARF excitation region. This method
has great potential to produce high-resolution images of tissue samples and quantitatively
characterize mechanical properties of these samples using the resonance frequency.

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Chapter 7 High Resolution Acoustic Radiation Force Based
Ultrasonic Elastography
Many acoustic radiation force (ARF) based ultrasound elastography, including acoustic
radiation force impulse imaging (ARFI) and harmonic motion imaging (HMI), have been
developed to remotely assess the elastic properties of tissues. However, due to the lower operating
frequencies of these approaches, their spatial resolutions are insufficient for revealing stiffness
distribution on small scale applications, such as cancerous tumor margin detection, atherosclerotic
plaque composition analysis and ophthalmologic tissue characterization. Though recently
developed ARF-based optical coherence elastography (OCE) methods open a new window for the
high resolution elastography, shallow imaging depths significantly limit their usefulness in clinics.
The aim of this study is to develop a high-resolution HMI method to assess the tissue
biomechanical properties with acceptable field of view using a 4 MHz ring transducer for efficient
excitation and a 40 MHz needle transducer for accurate detection. Under precisely aligned two
confocal transducers (Using two precisely aligned confocal transducers), the high-resolution HMI
system has a lateral resolution of 314 μm and an axial resolution of 147 μm with an effective field
of view (FOV) of 2 mm in depth. The performance of this high resolution imaging system was
validated on the agar-based tissue mimicking phantoms with different stiffness distributions. These
data demonstrated the imaging system’s improved resolution and sensitivity on differentiating
materials with varying stiffness. In addition, ex vivo imaging of a human atherosclerosis coronary
artery demonstrated the capability of high resolution HMI in identifying layer-specific structures
and characterizing atherosclerotic plaques based on their stiffness differences. All together high
resolution HMI appears to be a promising ultrasound-only technology for characterizing tissue
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biomechanical properties at the microstructural level to improve the image-based diseases
diagnosis in multiple clinical applications.
7.1 Background and Literature Review
Tissue biomechanical properties, highly correlated to the tissue pathophysiological
changes such as inflammation, aging and tumorous process, are commonly used by clinicians to
identify the diseased tissue and determine the disease states(Parker, Doyley et al. 2011). For
example, cancerous lesions are often times stiffer than the surrounding tissue and the mechanical
properties of atherosclerosis plaques are linked to the vulnerability of the plaques (Cheng, Loree
et al. 1993, Garra, Cespedes et al. 1997). Elastography has been developed in the past two decades
to quantitatively map the tissue biomechanical properties onto the structural image by measuring
the tissue deformation amplitude under internal or external mechanical excitation(Ophir, Cespedes
et al. 1991). Among several elastographical imaging techniques being investigated, ultrasound
elastography is the most commonly used method clinically (Wells and Liang 2011). In traditional
ultrasound elastography, the palpation method uses a compressional force to the tissue via a plate
or the transducer itself and the induced deformation is measured to assess the tissue’s elasticity
(Ophir, Cespedes et al. 1991). However, the heavy dependence on the physicians’ experiences and
skills limits the clinical use of this technique. As a more reliable substitute for the palpation method,
acoustic radiation force (ARF), generated during the propagation and attenuation of ultrasonic
wave within the tissue, has been used to deform the tissue in a more accurate and controllable
manner(Nightingale, Palmeri et al. 2001). Many ARF-based imaging techniques have been
investigated for tissue elasticity characterization, such as acoustic radiation force impulse (ARFI)
imaging(Nightingale 2011), vibroacoustic imaging(Fatemi and Greenleaf 1998), supersonic shear
137

wave imaging (SSI)(Bercoff, Tanter et al. 2004), shear wave elastography (SWE)(Sarvazyan,
Rudenko et al. 1998) and harmonic motion imaging (HMI)(Maleke, Pernot et al. 2006, Maleke
and Konofagou 2008, Vappou, Maleke et al. 2009, Maleke, Luo et al. 2010). Nonetheless, the
spatial resolution of the elastography images in most of these studies is significantly limited by the
low operating frequency (<15 MHz), which makes it difficult to characterize the tissue
biomechanical properties at the microstructural level (Righetti, Ophir et al. 2002, Righetti,
Srinivasan et al. 2003). Therefore, a high resolution elastography is desired to access the tissue
biomechanical properties in a small scale so as to improve the diagnosis of diseases such as the
tumor margin detection, atherosclerosis plaque composition analysis and ophthalmologic tissue
characterization. In 2007, phase sensitive or phase resolved optical coherence elastography (OCE),
an approach based on the measurement of phase changes in optical coherence tomography (OCT)
images, has been developed to generate the microstrain map of tissue subjected to a dynamic
compression in real time(Wang, Kirkpatrick et al. 2007). Later, by combining ARF-based
excitation method and OCE-based detection method, acoustic radiation force optical coherence
elastography (ARF-OCE) was developed. Based on the measurement of the vibrational movement
induced by dynamic ultrasound waves in longitudinal direction, 3D elasticity maps can be obtained
with both high temporal and spatial resolutions (Qi, Chen et al. 2012, Qi, Li et al. 2014). Similarly,
shear wave optical coherence elastography (SW-OCE) is another attempt to integrate ARF and
OCE to facilitate the high-resolution shear modulus map of tissues by tracking the propagating
shear wave in the transverse direction(Nguyen, Song et al. 2014). The recently developed resonant
ARF-OCE imaging technique utilizes the concept of mechanical resonant frequency and harmonic
motion imaging to characterize and identify tissues of different types by sweeping different ARF
modulation frequencies and measuring the frequency-dependent displacements, which provides
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an additional contrast to the ARF-OCE technique(Qi, Li et al. 2013). Although ARF-based
mechanical excitation capitalizes the advantage of providing the accurate remote palpation, the
OCE-based detection mechanism still suffers from the shallow depth penetration, which greatly
limits the clinical practicality of these OCE techniques. Given that there is a significant gap
between ultrasonic elastography and OCE on the imaging resolution and depth penetration, Shih
et al. improved the resolution of ARFI imaging by using a dual-element ultrasonic transducer to
accomplish the low frequency (11 MHz) ARF excitation and high frequency (48 MHz) ultrasonic
detection. The increased detection frequency has significantly improved the spatial resolutions
when compared with the traditional ARFI imaging operating in the low frequency range(Shih,
Huang et al. 2013). However, due to the restricted confocal region of dual elements transducers
with large frequency difference, this method requires time-consuming multiple axial depths scan
(B/D scan) to generate a 2 mm imaging field of view (FOV).
The aim of this study is to develop a high-resolution harmonic motion imaging (HR-HMI)
technique for characterizing tissue biomechanical properties in a small scale. A focused 4 MHz
large aperture ring shape transducer for generating effective ARF excited displacements and a 40
MHz unfocused small aperture needle transducer for detecting the ARF induced vibrational
displacements were designed and fabricated in this study. The ring transducer and needle
transducer were carefully arranged in a confocal configuration to maintain an improved sensitivity
and a more satisfactory FOV during the experiments. Imaging tests on both a tissue mimicking
phantom and an ex vivo human atherosclerosis coronary cadaver sample were carried out to
evaluate the performance of this imaging system. The experimental results suggest that this
ultrasound-only technique offers a more reliable capability of differentiating tissue biomechanical
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properties with promising translational potential by filling the resolution and imaging depth gap
between the ultrasonic elastography and OCE.
7.2 Methods and Materials
7.2.1 Ultrasonic Transducer Design and Experimental Setup
The schematic and a photograph of the experimental setup are shown in Figure 7-1. A
focused 4 MHz large aperture ring shaped transducer and a 40 MHz unfocused small aperture
needle transducer were designed and fabricated in this study. The general design parameters of
these two transducers are listed in Table 7-1. The 4 MHz ultrasonic transducer was made of
modified Pb(Zr,Ti)O3 (PZT) ceramic dedicated for high power applications. This focused ring
shaped transducer has an outer diameter (OD) of 30 mm, an inner diameter (ID) of 10 mm, and a
focal length of 30 mm. The 4 MHz transducer was responsible for inducing the periodically
vibrational movement of the imaging sample under a square wave modulated driving RF signal.
The single crystal Pb(Mg1/3Nb2/3)-PbTiO3 (PMN-PT), exhibiting outstanding electromechanical
coupling coefficient and piezoelectric coefficients, was used to fabricate the unfocused 40 MHz
detection transducer for tracking the vibrational movement of imaging sample. The general
fabrication procedures of needle transducers were described in our previous study (Ma, Zhang et
al. 2014).
Before the imaging experiment, the needle transducer was inserted from the center hole of
the excitation transducer and the two transducers were carefully aligned in a confocal manner
along both axial and lateral direction under the guidance of hydrophone. This precise alignment
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allowed the maximum overlapping of the low frequency ultrasound excitation zone and the high
frequency ultrasound detection zone. In the excitation system, the 4 MHz ring transducer was
excited by a 100 Hz square-wave modulated RF signal with a duty cycle of 50 % that was amplified
to 80-100 V by a power amplifier. Meanwhile, the 40 MHz ultrasonic transducer was driven by
200 MHz bandwidth pulser/receiver (5900PR, Panameterics, Waltham, WA, U.S.) with a pulse
repetition rate of 20 kHz. A 20 ms imaging window was applied to cover 2 periods of the harmonic
motion. The backscattered echo signals was amplified by 26dB and filtered by a 10 MH-100 MHz
band-pass filter before being digitized by a 2 GHz sampling frequency digitizer (121G11U,
DynamicSignals, Lockport, IL, USA). Digital filtering was then carried out to remove the
influence of low frequency component of excitation beam. A normalized cross-correlation method
was used to estimate the displacement by using the first A-line within the imaging window as the
reference. The average peak to peak displacement values were mapped to the final image for all
detected depths. To obtain a 2-D displacement map, the imaging subject was placed on a motorized
stage with 50 μm step size and up to a scanning length of 4 mm along lateral direction. Finally, the
displacement amplitudes of all detected depth at each scanning position were used to reconstruct
the 2-D HMI image.

Table 7-1: Design parameters and measured properties of transducers
Excitation Transducer Detection Transducer
Material PZT ceramics PMN-PT single crystal
Shape Focused ring-shape Unfocused square-shape
Center Frequency 4 MHz 40 MHz
Aperture Size 30 mm OD and 10 mm ID 0.56 mm side length
Focal Depth 30 mm 2.3 mm
Lateral Focal Zone 0.36 mm (-6dB) 0.31 mm (-3dB)
Axial Focal Zone 2 mm (-3dB) 4.3 mm (-3dB)

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Figure 7-1: (a) Schematic of experimental setup. (b) Photograph of arrangement of ultrasonic
transducers.

7.2.2 Phantom Preparation
Three agar-based tissue mimicking phantoms comprising of silicon dioxide powder as the
sound scatterers were fabricated to evaluate the performance of imaging system (Hall, Bilgen et
al. 1997). Two types of phantom with agar (Agar A360-500, Fisher Scientific, USA)
concentrations of 0.5% and 1.5% were fabricated to mimic the relatively soft and hard tissue,
respectively. Same concentration of silicon dioxide powder (S5631, Sigma-aldrich, St. Louis, MO,
USA) with particle size between 1 and 5 μm was added for echogenic enhancement. The three
different types of phantom (left-and-right phantom, up-and-down phantom and circular inclusion
phantom) were illustrated in Figure 7-2 (a-c), respectively. For the up-and-down phantom, the
thickness of the upper layer was 0.5 mm. For the inclusion phantom, the radius of the cylindrical
inclusion was about 2 mm.
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Figure 7-2: Geometry and composition illustration of (a) left-and-right phantom, (b) up-and-down
phantom, and (c) inclusion phantom.

7.3 Results and Discussion
7.3.1 Transducer Alignment and Acoustic Field Characterization
The 4 MHz ring shape transducer was first placed in the water tank, and the 2D acoustic
beam profile [Figure 7-3(a)] at the focal plane and the 1D acoustic profiles along axial direction
[Figure 7-3 (c)] were mapped with a hydrophone. Under the guidance of the hydrophone, the 40
MHz needle was inserted through the inner hole and carefully positioned to ensure confocal
alignment of the two transducers along both axial and lateral direction. The acoustic profiles of
ring transducer and needle transducer, as shown in Figure 7-3 (b-d) were captured by the
hydrophone with identical scanning range. A comparison of Figure 7-3 (a) and Figure 7-3 (b)
indicated that the inserted needle transducer did not appear to have any significant influence on
the acoustic beam profile of the ring shape transducer, and there was only 7.6% peak pressure drop
after inserting the needle transducer. The -6dB beamwidth was used to determine the focal zone
of the 4 MHz ring transducer during the one-way excitation process. With the needle transducer
inserted, the 4 MHz ring transducer had a focal zone of 0.36 mm laterally and 2.0 mm axially. As
expected, the 40 MHz needle transducer had a square-shape 2D beam profile that matched with
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the square shape element. Since the transducer element was not focused, the axial beam profile
exhibited relatively parallel characteristic to enlarge imaging depth. The -3dB beamwidth was used
to determine the focal zone of 40 MHz needle transducer during the two-way detection process.
The 40 MHz needle transducer had a focal zone of 0.31 mm laterally and 4.3 mm axially. As
shown in Figure 7-3 (b) and Figure 7-3 (c), it was observed that the 4 MHz ring transducer and the
40 MHz needle transducer were confocal in the lateral direction, where the focal zone of excitation
transducer covered the focal zone of the needle transducer. Moreover, with the confocal alignment
of the two transducers along axial direction [Figure 7-3 (d)], the relatively parallel beam profile of
40 MHz needle transducer well covered the focal zone of the 4 MHz ring transducer. These results
from hydrophone tests confirmed that the 4 MHz ring transducer and 40 MHz needle transducer
had the exactly confocal alignment along both lateral and axial directions.

Figure 7-3: (a) 2D beam profile of 4 MHz ring transducer at focal plane without needle transducer
insertion. (b) 2D beam profile of 4 MHz ring transducer at focal plane with needle transducer
insertion. (c) 2D pressure profile of 40 MHz needle transducer. (d) 1D beam profile along the axial
direction of 40 MHz needle transducer, and the 1D beam profile along the axial direction of 4 MHz
ring transducer with and without needle transducer insertion.
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Figure 7-4 illustrates the confocal alignment procedures of the two transducers and the
FOV determination of the HMI system. As shown in Figure 7-4 (a), the excitation zone of HMI
system was determined by the -6dB beamwidth of 4 MHz ring transducer, where the ARF induced
displacements were evenly distributed. Moreover, the detection zone [Figure 7-4 (b)] was
considered to be the -3dB beamwidth (corresponding to -6dB for two-way pulse-echo) of 40 MHz
transducer, within which the detection transducer had similar imaging capability. To determine the
FOV of HMI system, the detection zone should fall into the excitation zone with uniformly
distributed ARF in the lateral direction so as to ensure the accuracy of the HMI. Furthermore,
along the axial direction, the detection zone should cover the excitation zone so that the sensitivity
of the HMI was enhanced since all of the particle motions induced by the ARF could be monitored
at each imaging depth. Therefore, under the precise confocal alignment of excitation transducer
and detection transducer, the effective FOV of this HMI system was the overlapping region of the
excitation zone and the detection zone (indicated by the red arrow in Figure 7-4 (c)), which was
29.5-31.5 mm away from the 4 MHz ring transducer surface and 1.5-3.5 mm away from the 40
MHz needle transducer surface. During the HMI experiment, the imaging subject was placed
within this region to ensure the sensitivity and accuracy of HMI imaging system.
Several confocal dual-element transducer designs have been reported previously for high
resolution ARFI imaging (Shih, Huang et al. 2013) and acoustic angiography(Gessner, Frederick
et al. 2013), but they all exhibit the disadvantages of misalignment of the two transducer elements,
which result in a downgraded sensitivity and decreased imaging FOV. Moreover, the high
frequency detection transducer and the low frequency excitation transducer have the same working
distance in these designs, which significantly downgrades the sensitivity and FOV of the high
frequency detection transducer due to the higher attenuation of higher frequency ultrasound.
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Therefore, the unique combination of a focused ring transducer and an unfocused needle
transducer not only allowed for the precise confocal alignment of the two transducers in both axial
and lateral direction to enhance the sensitivity, but also effectively decreased the attenuation of the
detection ultrasound beam by adjusting their working distance to enlarge the FOV of this HMI
system.

Figure 7-4: Illustration of confocal alignment procedures of transducers and the FOV
determination HMI system. (a) Excitation zone of ring transducer. (b) Detection zone of needle
transducer. (c). FOV of HMI system: the overlapped region of excitation zone and detection zone.

7.3.2 Phantom Imaging Results
The 0.5 % concentration agar phantom and 1.5% concentration agar phantom were firstly
placed inside the FOV separately to perform HMI at one location, where the ARF induced
harmonic motion based displacements were assumed to be equally distributed along the axial
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direction inside each homogenous phantom. Figure 7-5 (a) shows the estimated dynamic
displacement curves of 0.5% agar phantom and 1.5% agar phantom at the axial depths of 1.7, 2.1,
2.5 and 2.9 mm. Within the 20 ms imaging widow, two periods of harmonic motion (100 Hz
modulation frequency) were tracked in both phantoms. It was observed that the dynamic
displacement curves exhibited a small variance along the imaging depth. As shown in Figure 7-5
(b), the average harmonic motion amplitudes along the axial direction of FOV for the 0.5%-agar
phantom and 1.5%-agar phantom were 7.08 ± 0.86 μm and 2.23 ± 0.26 μm, respectively. The
capability of the HMI imaging system to provide distinguishable amplitudes of the harmonic
motion based displacements within the two phantoms suggests that it can reliably discern the
materials of varying stiffness within the FOV.

Figure 7-5: (a) Dynamic displacement curves within 20 ms imaging window of 0.5% agar phantom
and 1.5% agar phantom at the axial depth of 1.7, 2.1, 2.5 and 2.9 mm. (b) Average amplitudes of
harmonic motion of the 0.5% agar phantom and 1.5% agar phantom along the axial direction.
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A total of 80 A-lines 50 μm apart from each other were used to reconstruct the B-mode
image and the corresponding displacement map (HMI image) with an imaging region of 2 mm × 4
mm. Figure 7-6 shows the B-mode images of the three types of phantoms (left-and-right, up-and-
down, inclusion) and the corresponding HMI images. It was observed that the regions with
different stiffness exhibited a homogenous echogenicity in the B-mode images, and the boundaries
between which (indicated by the red dotted lines) could not be easily distinguished (except for the
up-and-down phantom, in which the bright boundary was caused by the precipitation of silicon
dioxide powder). On the other hand, the HMI images provide a clear visualization of the regions
with different stiffness. The relative stiffness of the phantom was calculated and mapped to
different colors. The red color and blue color indicate the lower stiffness with larger displacements
and higher stiffness with smaller displacements, respectively. These phantom results suggest that
the high resolution HMI system has the great potential to differentiate the tissue components with
different biomechanical properties by mapping the relative stiffness onto the structural image.
To further evaluate the performance of the high resolution HMI system, the imaging results
of left-and-right phantom and up-and-down phantom were used to quantify the actual lateral
resolution and axial resolution of this imaging technique, accordingly. The displacement curves
along the lateral direction at the different axial locations (2.1, 2.3, 2.5, 2.7, and 3.0 mm) of the left-
and-right phantom, plotted in Figure 7-7 (a), indicate that the displacement variation tendency
matched favorably with the actual stiffness distribution of the phantom. The displacements were
uniformly distributed within the left part and right part with a transition region in the middle. The
displacement curves along the axial direction at different lateral locations (0.75, 1.75, 2.00, 2.75
and 3.50 mm) of the up-and-down phantom are plotted in Figure 7-7 (b), and a similar trend of
displacements distribution is observed compared with the left-and-right phantom. The two
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corresponding averaged displacement curves are given in Figure 7-7 (c) and (d), and both fitted
with a sigmoid function for resolution evaluation based on the standards reported previously
(Rouze, Wang et al. 2012, Shih, Huang et al. 2013). The 20% to 80% transition regions in the two
fitting curves were used to quantify the axial and lateral resolution of this imaging system. The
estimated the lateral and axial resolutions of this HMI system were 314 and 133 μm, respectively.

Figure 7-6: B-mode image (a) and its corresponding high resolution HMI image (b) of left-and-
right phantom. B-mode image (c) and its corresponding high resolution HMI image (d) of up-and-
down phantom. B-mode image (e) and its corresponding high resolution HMI image (f) of left-
and-right phantom. The red dashed lines in the B-mode image represent the boundary estimated
from the corresponding HMI image. S: soft 0.5%-agar phantom, H: hard 1.5%-agar phantom.

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Figure 7-7: (a) Displacement curves of left-and-right along the lateral direction at the axial location
of 2.8, 2.31, 2.54, 2.77 and 3.00 mm. (b) Displacement curves of up-and-down phantom along the
axial direction at the axial location of 0.75, 1.75, 2.00, 2.75 and 3.50 mm. (c) Averaged
displacement curves of left-and-right along the lateral direction with fitting curve. (d) Averaged
displacement curves of up-and-down phantom along the axial direction with fitting curve.

Theoretically, the lateral resolution in elastography is limited by the beamwidth of the
detection transducer without dependence on cross-correlation window size. The estimated lateral
resolution (314 μm) of this imaging system matches the measured -3dB beamwidth (310 μm) of
the detection transducer. The pulse width and the cross-correlation window size together determine
theoretical axial resolution in elastography. In this study, the pulse width of 40 MHz detection
transducer was 75 μm that was smaller than the chosen cross-correlation window size of 147 μm.
The estimated axial resolution of 154 μm is in reasonably agreement with the cross-correlation
window size that is the major determiner of axial resolution in this study.

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7.3.3 Ex vivo Human Coronary Artery Image
Finally, to demonstrate the feasibility of utilizing this high resolution HMI system to image
and characterize the biomechanical properties of artery tissue, ex vivo HMI of a section of post-
mortem atherosclerotic human coronary artery was performed. The human coronary artery was
prepared and immersed in phosphate-buffered saline (PBS) solution during the imaging process.
The B-mode reveals [Figure 7-8 (a)] that irregular thickening intima layer indicated by arrow I,
the thin echolucent media layer indicated by arrow M, and the adventitia layer with surrounding
tissue indicated by arrow A. A large calcified lesion, indicated by arrow C, is identified as a strong
echogenicity region with acoustic shadowing. Even though the high frequency B-mode image is
able to provide detailed structural information of the coronary artery, it cannot directly assess the
biomechanical information of the artery tissue. The high resolution HMI image of the coronary
artery is shown in Figure 7-8 (b). In the HMI image, the adventitia layer can be clearly discerned
from the intima-media layer with higher displacement amplitude under the excitation, which
agrees with fact that intima-media layers are stiffer than the adventitia layer (Holzapfel, Sommer
et al. 2005). As expected, the calcification region exhibits a much smaller displacement than the
adventitia region on the left and the intima layer above, which shows that the stiffness of calcified
plaque is higher than the surrounding vascular tissue. The high resolution HMI image is able to
provide the point-to-point stiffness mapping of the coronary artery, which is in reasonable
agreement with the pathological information provided by the B-mode image.
These results demonstrate that the high resolution HMI is a promising ultrasound
elastographical technique for tissue biomechanical property characterization at a small scale.
Owing to the unique confocal alignment of the low frequency excitation transducer and the high
frequency detection transducer, the lateral resolution and axial resolution of HMI are significantly
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improved. The spatial resolution of this HMI system can be further improved by using a higher
frequency and smaller aperture detection transducer; however, the trade-off between the imaging
resolution and size of FOV should be carefully considered during optimization. Using the similar
excitation method, the recently developed resonant ARF-OCE has successfully provided resonant
frequency specific contrast to the elastography image by sweeping the excitation frequency(Qi, Li
et al. 2013). This method can also be implemented on this high resolution HMI system to enhance
the tissue biomechanical property characterization, which serves as an additional preponderance
of HMI over the traditional ARFI imaging.

Figure 7-8: B-mode image (a) and its corresponding high resolution HMI image of a section of
human atherosclerosis coronary artery. I: intima layer, M: media layer, A: adventitia layer and
surrounding tissue, C: calcified plaque.

7.4 Conclusions
In this study, a high resolution HMI technique is developed to accurately distinguish
imaging subjects with varying stiffness at a small scale. A 4 MHz focused ring shape transducer
was designed to generate periodic ARF and induce the vibrational movements of sample in an
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efficient manner. Meanwhile, a 40 MHz unfocused needle transducer was used to track the
movement and quantify the relative stiffness. The acoustic beams of two ultrasonic transducers
were precisely aligned into confocal configuration to provide an effective FOV of 2 mm in depth.
The measured lateral and axial resolutions of HMI system were 314 and 154 μm, respectively. The
feasibility of this HMI system on differentiating materials with different stiffness was validated on
three different agar-based tissue-mimicking phantoms. These results demonstrate that the high
resolution HMI is able to accurately map the stiffness distribution onto the structural ultrasound
B-mode image. The HMI of ex-vivo human atherosclerosis coronary artery is able to determine
the layer-specific pathological structure and identify the calcified plaque based on the
biomechanical properties of the coronary artery. The high resolution HMI appears to offer a
promising ultrasound-only technology for charactering tissue biomechanical properties at the
microstructural level to improve the image-based diseases diagnosis in multiple clinical
applications.

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Chapter 8 Summary and Perspectives
8.1 Summary of the Thesis
Catheter-based intravascular imaging modalities are being investigated to visualize
pathologies, such as vulnerable atherosclerotic plaques known as thin-cap fibroatheroma (TCFA),
in coronary arteries, thus guiding therapeutic strategy at preventing acute coronary syndromes
(ACS). Mounting evidences have demonstrated there are three distinctive histopathological
features - (1) the presence of a thin fibrous cap, (2) a lipid-rich necrotic core, and (3) numerous
infiltrating macrophages – serving as key markers of increased vulnerability in atherosclerotic
plaques. To monitor the changing of these features, most catheter-based imaging modalities used
intravascular ultrasound (IVUS) as the basic imaging technology, with integrating emerging
intravascular imaging techniques to enhance the characterization of vulnerable plaques. However,
no current imaging technology can be regarded as the “gold standard” for the diagnosis of
vulnerable atherosclerotic plaques. Each intravascular imaging technology possesses its own
unique features that yield valuable information. On the other hand, the development of each
technology is hindered by their inherent limitations. Therefore, a synergistic method by integrating
difference imaging modalities can be a favorable approach to access the vulnerability of the
atherosclerotic plaques. In order to overcome the technical barriers, we have developed several
multi-modality intravascular imaging systems by combining ultrasonic and optical techniques. The
contributions of thesis to the intravascular imaging field are summarized as follows:
In chapter 2, we presented an ultra-high speed fully integrated IVUS-OCT imaging system
and a clinical compatible catheter solution. We reported the detailed technical specifications of
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this integrated IVUS-OCT imaging system and conducted several intracoronary artery imaging
experiments both in vivo and ex vivo to demonstrate the feasibility of the system, and offered the
complementary morphological description of coronary arteries. The miniaturized hybrid IVUS-
OCT catheter design is optimized and featured with the back-to-back arrangement of the IVUS
transducer and the OCT ball lens probe, which facilitate the real-time online fusion function. By
using an improved mechanical design and an advanced data processing algorithm, we further
increased the imaging speed of the integrated IVUS-OCT system to 73 frames per second and a
1.8 cm/s pull-back speed. This imaging speed is comparable to that of the commercial OCT
systems and three times faster than the commercial IVUS systems. These technical development
and improvements have made the integrated IVUS-OCT imaging system a promising candidate
that can be translated into clinical use. Thus, the integrated IVUS-OCT technology is likely to be
a most currently accessible and reliable approach to provide accurate identification of vulnerable
plaque(Takahiro Sawada, Junya Shite et al. 2008) in clinical practice and tackle the burgeoning
challenge of AVS morbidity and mortality today’s world. Last but not least, this research built a
solid foundation for other optical-ultrasonic dual modality imaging techniques, such as IVPA,
multi-frequency IVUS and ARF-OCE imaging systems.
In chapter 3, a pilot study on the diagnostic accuracy of atherosclerosis using the integrated
IVUS-OCT system is reported. During a study period of about 1 and a half years, 20 human
cadaver coronary artery samples were scanned to form 241 pairs of IVUS and OCT images with
the region of interests (ROI) classified as calcified plaque, fibrous plaque and lipid-rich plaques.
The results have demonstrated that the diagnostic accuracy of atherosclerosis by using the IVUS-
OCT system was improved with statistical significance. More importantly, based on the existing
diagnostic criteria, the first objective diagnostic criteria of IVUS-OCT with a three-loop structure
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is developed and reported, through closely working with experienced interventional cardiologists
and pathologists. From a clinical perspective, the present findings also suggested the fully
integrated IVUS-OCT system holds great promise for improving diagnosis of atherosclerosis and
translating into clinical benefits.
In chapter 4, we have successfully developed and prototyped multi-frequency IVUS
imaging system catheters with three different frequency combinations provided by PMN-PT and
LNO single crystals. The multi-frequency IVUS catheter, with a clinical compatible size of 0.95
mm in diameter, is featured by the back-to-back arrangement of a conventional IVUS transducer
and a high frequency IVUS transducer to achieve accurate co-registration of two IVUS images.
The performance of the high frequency IVUS transducer at different frequency ranges (90 MHz,
120 MHz and 150 MHz) was evaluated and compared to find the optimal frequency range,
considering imaging depth, imaging resolution and CNR, for the high frequency transducer in the
multi-frequency IVUS catheter. The in vitro human cadaver coronary artery imaging demonstrates
the capability of the multi-frequency catheter to provide a more comprehensive visualization of
the vascular structure and to facilitate the assessment of the vulnerable plaque. Compared to other
multi-modality intravascular imaging techniques, the multi-frequency IVUS imaging capitalizes
the advantage of cost-effectiveness because only a moderate modification of the current
commercial IVUS system is needed. Besides, the apparent clinical utility of this ultrasound
technology can be promptly explored during the translational stage since most of the interventional
physicians are familiar with the ultrasound technology. The future translation of the multi-
frequency IVUS imaging into clinical use will not only consolidate the leading status of the IVUS
technology in the interventional cardiology practice, but also prosperously lead to patient benefits.
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In chapter 5, a new IVUS-IVPA system is developed to overcome the limitations of the
current IVPA imaging systems. Two types of flexibly rotary IVPA catheter were designed,
fabricated, and validated on the imaging system. The frame rate of the imaging system has been
increased from 0.04 fps to 4 fps, which is two order of magnitude increase. By using the strong
optical absorption contrast for the lipid component at 1197nm, the lipid core size is quantified in
the in vitro coronary artery imaging experiments. The combination of IVUS and IVPA is likely to
be a promising tool to access both the morphological and the functional information of the
coronary artery.
In chapter 6, we reported the further development of the ARF-OCE system. Based on the
mechanical resonance of tissues in response to external periodic excitations, an acoustic excitation
frequency dependent resonant ARF-OCE algorism is developed to provide additional contrast to
the current ARF-OCE system. Moreover, the confocal arrangement of the acoustic excitation and
the optical detection by using a single ring transducer and a dual-ring transducer is established.
The phantom validation study and the in vitro human cadaver sample study suggest that ARF-OCE
is capable of differentiating the coronary artery component based on the biomechanical
characteristics. The three major refinements of ARF-OCE are summarized as follows: (1) adding
resonant contrast to quantify the absolute elasticity of the tissue more precisely; (2) using a ring
transducer to achieve confocal configuration for future in vivo development; (3) using a dual-
transducer to generate a more localized ARF-OCE region, which make the current ARF-OCE more
desirable for in vivo endoscopic intravascular imaging application.
In chapter 7, a high resolution HMI technique is developed to accurately distinguish
imaging subjects with varying stiffness at a small scale. Given that OCT is the optical analogue of
ultrasound imaging, similar to the multi-frequency IVUS imaging project described in chapter 4,
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high frequency ultrasound can always fill the resolution and imaging depth gap between
conventional ultrasound and OCT. Therefore, this high resolution HMI takes advantage of low
frequency (4 MHz) excitation to generate enough ARF-induced displacements and high frequency
ultrasound detection to accurately characterize tissue’s mechanical properties at a small scale. The
acoustic beams of two ultrasonic transducers were precisely aligned into a confocal configuration
to provide an effective FOV of 2 mm in depth. The measured lateral and axial resolutions of HMI
system were 314 and 154 μm, respectively. The feasibility of this HMI system on differentiating
materials with different stiffness was validated on three different agar-based tissue-mimicking
phantoms. These results demonstrate that the high resolution HMI is able to accurately map the
stiffness distribution onto the structural ultrasound B-mode images. The HMI of ex-vivo human
atherosclerosis coronary artery is able to determine the layer-specific pathological structure and
identify the calcified plaque based on the biomechanical properties of the coronary artery. The
high resolution HMI appears to offer a promising ultrasound-only technology for charactering
tissue biomechanical properties at the microstructural level to improve the imaging-based diseases
diagnosis in multiple clinical applications.
8.2 Perspectives of Multi-modality Intravascular Imaging
Although the fully integrated IVUS-OCT system captures the most of the morphological
features of atherosclerotic plaques with both deep penetration and high resolution, it lacks
molecular specificity for characterization of the plaque composition. To solve this problem, our
group recently reported a tri-modality intravascular imaging system that combines IVUS, OCT
and fluorescence imaging as an improved extension of the integrated IVUS-OCT system(Liang,
Ma et al. 2014). A double-clad fiber combiner was used to resolve the OCT beam and fluorescence
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beam coupling in the optical sub-probe, which was aligned side-by-side with an ultrasonic
transducer to fabricate a miniature tri-modality catheter (Figure 8-1 (a)-(c)). The tri-modality
system was able to simultaneously acquire IVUS, OCT, and fluorescence signals from a coronary
artery stained with fluorescent-imaging agent Annexin V conjugated Cy5.5, which was used to
target the presence of macrophages (Figure 8-1(d)-(f)). The combination of these three modalities
is synergistic in detecting key features of a vulnerable plaque that cannot otherwise be
accomplished with a single modality like IVUS for visualizing the gross architecture, OCT for the
detailed examination of luminal microstructure, and fluorescence imaging for inflammatory
reactions. Besides further reducing the size and increasing the imaging speed for a clinically
compatible catheter, some important validations are required before translating of this technology
to in vivo human coronary artery imaging, including systematically quantifying the imaging depth
of fluorescence imaging and evaluating the long-term safety associated with the use of fluorescent-
imaging agents.
Despite challenges to its validity in characterizing vulnerable atherosclerotic plaques,
IVUS imaging still forms the basis for most multi-modality intravascular imaging systems owing
to its wide recognition and extensive scientific studies. But IVUS alone cannot meet the urgent
need for improved diagnosis of atherosclerosis to prevent heart attack, mainly because it lacks the
resolution capacity to identify features specific to vulnerable plaques such as TCFA. Instead, the
three multi-modality intravascular imaging techniques namely, IVUS-OCT, multi-frequency
IVUS, and IVUS-IVPA must meet the challenge. Two candidates are the integrated IVUS-OCT
and the multi-frequency IVUS imaging systems, which offer higher resolution imaging to visualize
the microstructure of coronary arteries and the presence of thin fibrous caps. Integrating OCT with
IVUS is considered superior to integrating an ultra-high frequency IVUS with a conventional
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IVUS because of OCT’s unique optical scattering contrast and its maturity in the market. On the
other hand, the multi-frequency IVUS imaging system, an ultrasonic-only solution, is more
advantageous in terms of low cost and simplicity for integration.

Figure 8-1: (a) Schematic of the tri-modalities integrated system and the probe. OCT and
fluorescence systems were combined with a wavelength division multiplexer. Ultrasound signal
was synchronized with optical signal by the trigger from swept source laser. (b) Structure of the
tri-modality endoscopic probe: the optical probe and ultrasound transducer were placed side-by-
side. (c) Photograph of the tri-modality catheter. The rigid portion of the probe is 7 mm and the
diameter is 1.2 mm. The scale is in centimeters. Ex vivo images from human coronary artery
(d) combined OCT and fluorescence image, (e) combined ultrasound and fluorescence image, and
(f) combined tri-modality image. Adapted from Liang et al (Liang, Ma et al. 2014).

Infraredx’s IVUS-NIRS is the only commercially available multi-modality intravascular
imaging systems. Infraredx’s IVUS-NIRS is undergoing prospective clinical trials worldwide to
determine its ability to accurately detect vulnerable plaques. Hopefully, it will become part of the
clinical practice for the diagnosis of vulnerable plaques and prevention of heart attack. Among all
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the innovative techniques that characterize lipid components inside vulnerable plaques based on
molecular specificity, IVPA is capable of quantifying the size and location of the lipid-rich necrotic
core, which makes it superior to NIRS. Upon continued refinement of the integrated IVUS-IVPA
imaging system, it is likely this technology will become a “game-changer” in the near future by
providing clinically crucial information.
Given that each intravascular imaging modality has its own distinctive advantages and
limitations, future advance is to further integrate more than two imaging modalities to complement
each other’s deficiencies and to significantly enhance the characterization of vulnerable plaques.
Multimodality intravascular imaging that can provide both structure and molecular information
will provide clinicians with a critically important tool for diagnosing vulnerable plaques,
monitoring the progression of disease, and evaluating the efficacy of intervention. Based the scope
of this thesis, integrating IVUS, OCT and IVPA into one single catheter seems a more
comprehensive and feasible solution to assess the vulnerability of atherosclerotic plaques. Such
multimodal intravascular imaging system is unique in that it combines the advantages of deep
imaging depth of IVUS to visualize the whole plaque volume, high spatial resolution of OCT to
measure the thin fibrous cap, and molecular contrast of IVPA to locate and quantify the lipid
disposition. This combined multimodal vascular imaging system will permit cross-sectional
visualization of vasculature with high spatial resolution, broad imaging depth, and high molecular
sensitivity, which is not possible by any of these technologies alone. The integrated IVUS-OCT-
IVPA imaging system will provide the physician with a powerful tool for imaging, diagnosing,
and managing vulnerable plaques. Furthermore, this multi-modal imaging strategy in a single
system permits the use of a single disposable guide wire and catheter, thereby reducing costs to
hospitals and patients and improving prognosis by early detection.
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However, the complexity of development of such imaging technique remains to be
determined. As discussed in Chapter 4, the speed of integrated IVUS-IVAP system has been
improved with two orders of magnitude (4 fps), but this is still not fast enough for the clinical
setting. The main technical barrier hindering the imaging speed of IVPA is the shortage of high
repetition rate pulsed laser at 1200 nm and 1700 nm; thus, the successful development of such
lasers will allow the integrated IVUS-IVPA imaging system to bridge the above-mentioned speed
limit. Due to the complexity of the fabrication process, most of the intravascular multi-modality
used in clinic and research were made by hand with an OD around 1 mm. No doubt, further
miniaturizing of the multi-modality intravascular catheter will be beneficial when delivering such
catheters into the complex and confined coronary circulation system. However, the current major
technological barrier limiting the further downscaling of the IVUS-based multi-modality catheters
is the size of ultrasonic transducer. Since further reducing the aperture size of IVUS transducer
would sacrifice the FOV of the IVUS image, implementation of an advanced signal processing
algorithm, such as chirp coded excitation, could potentially compensate for the lost imaging depth
from reduced aperture size (Park, Li et al. 2013).
On the other hand, the successful combination of IVUS and OCT would naturally open up
a window for the future development intravascular ARF-OCE imaging system to characterize the
mechanical properties of the coronary artery, which also provides worthless information of plaque
vulnerability. However, there are still many technical challenges associated with the development
of intravascular ARFI-OCE imaging system. The miniaturized IVUS transducer is responsible for
not only imaging but also inducing tissue displacements. Even though the phase-resolved
algorithm can have a sub-micrometer sensitivity when detecting the ARF-induced displacement,
it still requires the transducer with limited aperture size to generate high intensity ultrasound wave.
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Progress should be made to develop novel piezoelectric material that can stand higher electrical
driving power. Moreover, more precise alignment ultrasound beam and OCT light is necessary to
enhance the effectiveness of the proposed intravascular ARF-OCE imaging system. A primary
design of integrated IVUS, OCT and ARF-OCE probe is shown in Figure 8-2 (a). A GRIN
(gradient index) lens, which focuses the OCT light beam (1.3 µm in wavelength) delivered by a
single mode (SM) fiber, is designed to go through the center hole of the ring transducer. Both the
light beam and the ultrasound wave will be deflected by a mirror and focus at the same location
on the sample. The first prototype of the ring transducer was shown in Figure 8-2 (b) with a
aperture size of 3 mm in diameter and a center frequency of 10 MHz for initial concept validation
experiments.
Similarly, the extension of high resolution HMI imaging system to intravascular imaging
will still rely on the development of miniaturized transducer with the capability of generating high
intensity ultrasound and detecting the ARF-induced displacements. . However, it is very
challenging to implement ARFI or HMI on the traditional unfocused intravascular ultrasound
(IVUS) transducer due to the limited acoustic radiation force induced at such high frequency (20-
40Mz). As shown in Figure 8-3 , a confocal dual-element ultrasonic transducer for intravascular
ARFI imaging by integrating a focused low frequency (8.5 MHz) transducer for effective
excitation and a high frequency (35MHz) transducer for accurate detection is being developing. A
mechanical focusing ring transducer (8.5 MHz) with a focal depth of 5 mm was fabricated by using
modified high-Q PZT ceramics to generate detectable displacements. A flat square transducer (35
MHz) made of PMN-PT single crystal was used to detect the induced displacements. The square
transducer was aligned 1 mm above the bottom of the ring transducer to ensure the confocal field
of view of 2 mm. ARFI imaging of side-by-side gelatin phantom was performed by linearly
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scanning the dual-element transducer. The pulse echo testing results of the dual-element transducer
were shown in Figure 8-3 (c-d). The boundary of side-by-side gelatin phantom cannot be
distinguished in the B-mode image [Figure 8-3 (c)]. The corresponding ARFI image [Figure 8-3
(d)] provides a clear visualization of the regions with different stiffness by mapping the
displacements into different colors. The averaged displacements are about 2.7 µm for the left side
(13kPa) and 1.1 µm for the right side (45 kPa), respectively. The preliminary results demonstrate
the feasibility of using dual element transducer to perform IV-ARFI to characterize the mechanical
properties of atherosclerotic plaque upon further miniaturization in the near future.

Figure 8-2: (a) Integrated IVUS/OCT/ARF-OCE probe with coaxial arrangement design. Inserted
image: different view showing the mirror at the tip of the probe. GRIN lens: gradient-index lens.
US: ultrasonic transducer. (b) First prototype of ring transducer for intravascular ARF-OCE probe.

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Figure 8-3: (a) Schematic of dual-element IV-ARFI transducer. (b) Photo of the dual-element IV-
ARFI transducer prototype. (c) Pulse-echo results of ring shape excitation transducer (8.5 MHz).
(d) Pulse-echo results of square detection transducer (35 MHz). (e) B-mode Image of side-by-side
gelatin phantom (50dB dynamic range, estimated Young’s Modulus: left-13kPa, right-45kPa). (f)
ARFI image of side-by-side gelatin phantom (unit: µm).

From a sociological perspective, a successful clinical translation of multi-modality
intravascular imaging will require acceptance by the greater medical community of its diagnostic
value and willingness for clinicians to acquire training in interpreting the co-registered images
(Maresca, Adams et al. 2014). It is anticipated that the estimated cost of the integrated imaging
system console and catheter will be higher than that of a single IVUS imaging system. Among all
the IVUS-based intravascular imaging discussed in this review, the multi-frequency IVUS would
be the most cost-effective technology since it only requires a moderate refinement of current IVUS
system without the need of adding an optical laser source. However, the estimation absolute cost
of these IVUS-based multimodal intravascular imaging systems is a quite complex process, which
should weigh on the time to achieve the regulatory certificates such as FDA approval,
reimbursement plan, and the business development strategy of the companies or individuals who
are commercializing these technologies. Last but not the least, investment interests in biomedical
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device innovation and proper handling of the intellectual property rights are essential to
accelerating the future development of multi-modality intravascular imaging.

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184

Abstract (if available)

Abstract Thin-capped fibroatheroma (TCFA) is considered to be the phenotype of vulnerable atherosclerotic plaque based on the pathological studies, whose sudden rupture is frequently responsible for acute coronary syndrome (ACS). Early detection and prognosis of TCFA will not only guide the therapeutic strategy to benefit the patients, but also contribute to the study of natural history of vulnerable plaque that is still elusive. To date, various imaging modalities employing ultrasonic scattering contrast with radio frequency analysis, optical scattering contrast, optical absorption mechanism, spectroscopic analysis and targeted-molecular imaging method, provide diverse visualizations of coronary arteries both in clinic and research. However, none of these imaging modalities has been symmetrically validated to precisely detect TCFA in vivo, since any single imaging modality exhibit natural limitations when characterizing the elusive TCFA. Therefore, integration of theses imaging modalities into a single catheter is hypothesized to be the optimal method to enable the early detection of TCFA by combing best features of these techniques while compensating their respective weakness. ❧ In this thesis, several multi-modality intravascular imaging systems by combined use of ultrasonic and optical techniques were developed in three aspects to access the morphological information, functional components, and elasticity of coronary arteries. Aim to fully obtain the morphological information real time in vivo, an ultra-high speed integrated intravascular ultrasound (IVUS) and optical coherence tomography (OCT) system has been optimized and prototyped. Statistical validation study and IVUS-OCT diagnostic criteria development has demonstrated that the integrated IVUS-OCT system has an overall higher diagnostic accuracy of atherosclerotic plaques, especially for lipid-rich plaques. From the cost-effective perspectives, a multi-frequency IVUS imaging system was developed to improve the trade-off between resolution and depth of penetration of IVUS. Aiming to measure the thin fibrous cap, an ultra-high frequency IVUS transducer was incorporated into the conventional IVUS catheter to provide higher special resolution image of the coronary artery, which makes the multi-frequency IVUS imaging system an alternative of integrated IVUS-OCT system. Moreover, the development of a high speed integrated IVUS and intravascular photoacoustic (IVPA) system make it possible to quantify a key parameter of diagnosing TCFA—the size of lipid deposition inside coronary artery. In vitro imaging of lipid-laden artery was performed by using current IVUS-IVPA system with 2 orders of magnitude improvement of imaging speed, which bridged the gap of translating the IVUS-IVPA technology to clinical study. In order to characterized the biomechanical properties of plaque components, acoustic radiation force (ARF) optical coherence elastography (OCE) is further developed featured by the confocal alignment of OCT detection region with acoustic excitation field. Based on the concept of mechanical resonant frequency of tissue in response to external force, the development of resonant OCE system adds an additional contrast to the current ARF-OCE system by sweeping the acoustic excitation frequency. Finally, an ultrasonic-only high resolution elastography technique harmonic motion imaging (HMI) was developed to provide microstructural level mechanical property characterization by using low frequency excitation and high frequency detection method. This research have supported the hypothesis that multi-modality intravascular imaging by using ultrasonic and optical techniques serves as a reliable method to facilitate the early diagnosis of vulnerable atherosclerotic plaque and enhance the study of natural history of vulnerable plaque.

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Asset Metadata

Creator Ma, Teng (author)

Core Title Multi-modality intravascular imaging by combined use of ultrasonic and opticial techniques

School Viterbi School of Engineering

Degree Doctor of Philosophy

Degree Program Biomedical Engineering

Publication Date 07/29/2017

Defense Date 04/28/2015

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag atherosclerosis,high frequency ultrasound,intravascular imaging,intravascular ultrasound,multi-modality imaging,OAI-PMH Harvest,photoacoustic imaging

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Shung, Kirk Koping (committee chair), Zhou, Qifa (committee chair), Armani, Andrea M. (committee member), McCain, Megan (committee member), Yen, Jesse (committee member)

Creator Email mt880501@gmail.com,tengma@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-616089

Unique identifier UC11302136

Identifier etd-MaTeng-3760.pdf (filename),usctheses-c3-616089 (legacy record id)

Legacy Identifier etd-MaTeng-3760.pdf

Dmrecord 616089

Document Type Dissertation

Format application/pdf (imt)

Rights Ma, Teng

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA