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High-frequency ultrasound array-based imaging system for biomedical applications

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High-frequency ultrasound array-based imaging system for biomedical applications

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HIGH-FREQUENCY ULTRASOUND ARRAY-BASED IMAGING SYSTEM
FOR BIOMEDICAL APPLICATIONS

by

Bong Jin Kang

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

May 2015

Copyright 2015 Bong Jin Kang
ii

DEDICATION

I dedicate this dissertation to my beloved wife, Sung Won Park, my parents, In Soo Kang
and Sun Ja Ahn, my brother, Bong Seo Kang, my parents-in-law, Kyung Joon Park and
Hyun Tak Han, and my brother-in-law, Jung Hwan Park.
Without their patience, understanding, support, and most of all love in many difficulties,
the completion of this work would not have been possible.

iii

ACKNOWLEDGEMENTS
During six years in NIH Resource Center for Medical Ultrasonic Transducer
Technology at the University of Southern California, I have been tremendously blessed to
be accompanied and supported by many people directly or indirectly. The completion of
this dissertation would not have been possible without them. It is a great pleasure that I
have an opportunity to thank all of them.
In the first place, I would like to gratefully and sincerely thank to my advisor, Dr.
K. Kirk Shung for his guidance, understanding, and patience during my graduate studies.
Dr. Shung provided me a precious opportunity to inspire and enrich my growth as a Ph. D.
His mentorship was paramount in providing a well-rounded experience consistent my
long-term career goals. Also, he has kept consistent interest in the progress of my thesis
and was available when I need his expertise and advice.
I gratefully acknowledge my committee members, Dr. Jesse Yen and Dr. C.-C.
Jay Kuo, for their insightful comments allow me to finish this dissertation. Special thanks
go to Dr. Hyung Ham Kim, Dr. Changhong Hu, and Dr. Qifa Zhou for much of their
support for my research on high frequency ultrasound array-based imaging system.
I would like to express my thanks and appreciation to all my lab alumni, Dr.
Jungwoo Lee, Dr. Jin Ho Chang, Dr. Jinhyoung Park, Dr. Jae Yoon Hwang, Dr.
Changyang Lee, and Dr. Jong Seob Jeong for their encouragement and warm advice in
my graduate study and life. I also would like to express my thanks and appreciation to all
iv

my current lab members, Dr. Sangpil Yoon, Dr. Changhan Yoon, Mr. Hayong Jung, Mr.
Min Gon Kim, Mr. Chi Woo Yoon, Mr. Hae Gyun Lim, Mr. Kyo Suk Goo, Dr. Ying Li,
Mr. Nestor E. Cabrrera-Munoz, and Mr. Chi Tat Chiu, for their kind advice and help in
my graduate experiences.
Lastly, I would like to thank my lovely family, my wife, Sung Won Park, my
parents, In Soo Kang and Sun Ja Ahn, my brother, Bong Seo Kang, my parents-in-law,
Kyung Joon Park and Hyun Tak Han, and my brother-in-law, Jung Hwan Park. Thank
you for all your understanding, patience, and support.

v

TABLE OF CONTENTS
DEDICATION .................................................................................................................... ii
ACKNOWLEDGEMENTS ............................................................................................... iii
LIST OF TABLES ............................................................................................................. ix
LIST OF FIGURES .............................................................................................................x
ABSTRACT ....................................................................................................................xv

CHAPTER 1 Introduction
1.1 Medical Ultrasound Imaging ................................................................................ 1
1.2 High-Frequency Ultrasound ................................................................................. 5
1.2.1 High-Frequency B-mode Imaging ................................................................ 5
1.2.2 High-Frequency Pulsed-wave and Color Doppler Imaging .......................... 6
1.3 Objective of Research .......................................................................................... 7

CHAPTER 2 High Frequency Ultrasound Array-Based Imaging System
2.1 Introduction .......................................................................................................... 8
2.2 High Frequency Array-Based Imaging System ................................................... 9
2.2.1 Overall System Description .......................................................................... 9
2.2.2 Transmit Beamformer Board ...................................................................... 11
2.2.3 Digital Receive Beamformer Board............................................................ 13
2.2.4 Control Board.............................................................................................. 14
2.2.5 Backplane Board ......................................................................................... 15
2.2.6 Graphic User Interface in PC ...................................................................... 15
2.3 System Evaluation .............................................................................................. 16
2.3.1 30 MHz 256-element Linear Array Transducer .......................................... 18
2.3.2 20 MHz 192-element Convex Array Transducer ........................................ 21
2.3.3 20 MHz 48-element Phased Array Transducer ........................................... 23
2.4 Summary ............................................................................................................ 24
vi

CHAPTER 3 High Frequency Ultrasound Ophthalmic Imaging
3.1 Introduction ........................................................................................................ 25
3.2 Experimental Arrangement ................................................................................ 27
3.3 Results ................................................................................................................ 29
3.3.1 Anterior Segment Imaging using 30 MHz Linear Array Transducer ......... 29
3.3.2 Anterior and Posterior Segments Imaging using 20 MHz Convex Array
Transducer................................................................................................... 31
3.4 Summary ............................................................................................................ 31

CHAPTER 4 Interfacing High Frequency Ultrasound Pulsed-wave Doppler and
Micro-Electrocardiogram to Assess Ventricular Function in a
Zebrafish Model of Injury and Regeneration
4.1 Introduction ........................................................................................................ 33
4.2 Designs and Methods ......................................................................................... 35
4.2.1 PW Doppler Acquisition ............................................................................. 35
4.2.2 ECG Acquisition ......................................................................................... 37
4.2.3 Simultaneous Acquisition of PW Doppler and ECG .................................. 37
4.3 Results ................................................................................................................ 39
4.3.1 Synchronization of PW Doppler and ECG signals ..................................... 39
4.3.2 The Implication of E/A Ratio for Diastolic Function ................................. 40
4.3.3 Cardiac Rhythms in Response to Injury ..................................................... 40
4.4 Discussions ......................................................................................................... 43

CHAPTER 5 High Frequency Dual Mode Pulsed-Wave Doppler Imaging for
Monitoring the Functional Regeneration of Adult Zebrafish Hearts
5.1 Introduction ........................................................................................................ 45
5.2 Principles and Implementation ........................................................................... 48
5.2.1 Single mode pulsed wave Doppler ............................................................. 48
vii

5.2.2 Dual mode pulsed wave Doppler ................................................................ 49
5.3 Experimental Arrangement ................................................................................ 50
5.3.1 System Setup ............................................................................................... 50
5.3.2 Phantom Study ............................................................................................ 50
5.3.3 Adult Zebrafish Heart Doppler Imaging ..................................................... 52
5.3.4 Parameters for Assessing Diastolic Dysfunction ........................................ 54
5.4 Results ................................................................................................................ 56
5.4.1 Phantom Study Results ............................................................................... 56
5.4.2 Zebrafish Heart Results............................................................................... 61
5.5 Discussion .......................................................................................................... 65
5.6 Conclusion .......................................................................................................... 68

CHAPTER 6 High-Frequency Color Doppler Imaging using Array-Based
Ultrasound Imaging System
6.1 Introduction ........................................................................................................ 69
6.2 Methods .............................................................................................................. 72
6.2.1 Functional Block Diagram of Color Doppler Signal Processing ................ 72
6.2.2 Data Acquisition ......................................................................................... 72
6.2.3 Quadrature Demodulation ........................................................................... 74
6.2.4 Clutter Filtering ........................................................................................... 75
6.2.5 Velocity Estimation .................................................................................... 76
6.2.6 Color Mapping ............................................................................................ 79
6.3 Experimental Arrangement ................................................................................ 80
6.3.1 Flow Phantom Study ................................................................................... 80
6.3.2 Adult Zebrafish Heart Study ....................................................................... 81
6.4 Results ................................................................................................................ 82
6.4.1 Flow Phantom Results ................................................................................ 82
6.4.2 Zebrafish Heart Results............................................................................... 83
6.5 Discussion .......................................................................................................... 84
viii

CHAPTER 7 Summary and Future Works
7.1 Summary ............................................................................................................ 86
7.2 Future Works ...................................................................................................... 88
7.2.1 Real-Time Color Doppler Imaging ............................................................. 88
7.2.2 B-Flow Imaging .......................................................................................... 88

BIBLOGRAPHY ...............................................................................................................90

ix

LIST OF TABLES
Table 2.1 Characteristics of the ultrasound array transducers ...........................................17

x

LIST OF FIGURES
Figure 1.1 Ultrasound transducers: (a) single element transducer and (b) array
transducer. ............................................................................................................................2
Figure 1.2 Diagrams of mechanical and electronic scanning: (a) single element
transducer with mechanical linear scanning, (b) single element transducer with
mechanical sector scanning, and (c) array transducer with electronic scanning. ................3
Figure 2.1 Overall block diagram of the high frequency array-based imaging system.
The system is composed of four main blocks: transmit beamformer, digital receive
beamformer, control and PC. .............................................................................................10
Figure 2.2 (a) Photograph of the high frequency array-based imaging system. (b)
Simplified illustration of the system. The system is composed of eight transmit
beamformer boards, two digital receive beamformer boards, one control and
backplane board. ................................................................................................................10
Figure 2.3 Photograph of the transmit beamformer board. Transmit beamformer board
is composed of 32 channels of pulse generator, transmit/receive (T/R) switch, low-
noise amplifier (LNA) and variable gain amplifier (VGA), and one FPGA. ....................12
Figure 2.4 Photograph of the digital receive beamformer board. Receive beamformer
board is composed of 32 channels of bandpass filter (BPF), low-noise amplifier (LNA)
and variable gain amplifier (VGA), analog-to-digital converter (ADC) and one FPGA.
............................................................................................................................................13
Figure 2.5 Photograph of the control board. Control board has a PCIe connector for a
digital acquisition board, clock generator/buffers and one FPGA. ....................................15
Figure 2.6 A screen shot of graphical user interface (GUI) in PC for real-time display. ..16
Figure 2.7 Photographs of (a) 30 MHz linear array, (b) 20 MHz convex array, and (c)
20 MHz phased array transducers. .....................................................................................17
Figure 2.8 Field of view of 2-D images corresponding to (a) linear array, (b) convex
array, and (c) phased array transducers. .............................................................................18
Figure 2.9 (a) B-mode image of 20 µm tungsten wire phantom acquired using a 30
MHz linear array transducer. (b) Lateral and (c) axial beam profile at the transmit
focus at 6.4 mm. .................................................................................................................19
xi

Figure 2.10 B-mode images of an anechoic sphere phantom with (a) 1090 µm, (b)
825 µm, (c) 530 µm, and (d) 400 µm spheres in diameter. ...............................................20
Figure 2.11(a) B-mode image of 20 µm tungsten wire phantom acquired using a 20
MHz convex array transducer. (b) Lateral and (c) axial beam profile at the transmit
focus at 20 mm. ..................................................................................................................21
Figure 2.12 B-mode images of an anechoic sphere phantom with (a) 1090 µm, (b)
825 µm spheres in diameter. (c) Cross-sectional and (d) longitudinal images of wall-
less tube tissue mimicking phantom with 2 mm and 4 mm in diameter. ...........................22
Figure 2.13 (a) B-mode image of 20 µm tungsten wire phantom acquired using a 20
MHz phased array transducer. (b) Lateral and (c) axial beam profile at the transmit
focus at 6 mm. ....................................................................................................................23
Figure 3.1 Clinical images of the eye: (a) choroidal tumor and retinal attachment, (b)
retinal detachment, (c) iris crypt, and (d) accommodative lens movement (Courtesy of
Sonomed, Inc.) ...................................................................................................................26
Figure 3.2 Anterior segment imaging of the eye using a 30 MHz 256-element linear
array transducer: (a) the linear array transducer is placed over cornea for anterior
segment imaging. Red-dashed box indicates an expected imaging plane. (b) Picture of
the experimental setup for the excised bovine eye. ...........................................................28
Figure 3.3 Posterior segment imaging of the eye using a 20 MHz convex array
transducer: (a) the convex array is placed over ciliary body for posterior segment
imaging. (b) Picture of the experimental setup for the excised bovine eye. ......................29
Figure 3.4 B-mode images of anterior segments of excised (a) bovine, (b) porcine,
and (c) rabbit eye. ..............................................................................................................30
Figure 3.5 B-mode images of (a) anterior and (b) posterior segments of excised
bovine eye. .........................................................................................................................31
Figure 4.1 (a) The schematic diagram of PW Doppler and ECG systems. (b) Picture
of the experiment setup for simultaneous measurement of PW Doppler and ECG. ..........38
Figure 4.2 Synchronized Doppler and ECG recording allowed for identification of A-
wave in response to atrial contraction (P wave in ECG) as indicated by the red dashed
line, and E-wave to ventricular relaxation (T wave in ECG) by the yellow dashed line. ..39
Figure 4.3 Representative coregistration of PW Doppler signals with ECG signals
from 0 days post injury (dpi) to 3, 35, and 65 dpi. The baseline PW Doppler and ECG
signals were established on 0 dpi. E-wave velocity increased at 3 dpi and gradually
decreased toward the baseline. ...........................................................................................41
xii

Figure 4.4 Injury induced hemodynamics changes. (a) Injury of the zebrafish
ventricle significantly increased E-wave velocities at 3 dpi, which regressed toward
the baseline levels at 35 dpi in comparison with the sham. (b) A-wave velocities
decreased at 35 and 65 dpi in comparison with the sham. (c) Injury of the zebrafish
ventricle significantly increased E/A ratios at 3 and 35 dpi, which regressed to the
baseline levels at 65 dpi. In humans, the E/A ratio is clinically assessed for ventricular
compliance and it is greater than 1 for the normal ventricular diastolic function. In
zebrafish, the E/A ratio is less than 1 at baseline. ..............................................................42
Figure 4.5 Injury induced electrophysiological changes. (a) PR intervals and (b) RR
intervals remained unchanged between the injury and sham. (c) The QTc intervals
were prolonged in response to injury and did not recover. ................................................42
Figure 5.1 Beam sequences of implemented PWD: (a) Single mode PWD and (b) dual
mode PWD. The location of the gates for the dual mode PWD can be located at
different lateral and axial positions from each other. FD is Doppler flow and TD is
tissue Doppler. ...................................................................................................................49
Figure 5.2 Experimental setup for (a) flow phantom and (b) moving wire phantom.
The flow phantom is composed of a polyimide tube with an inner diameter of 510 µm,
and flow velocity is controlled by a syringe pump. The moving wire phantom is
composed of two tungsten wires of 20 µm in diameter. Black dots within the Doppler
gates are representing the cross sections of wire targets. ...................................................51
Figure 5.3 (a) The picture and (b) the diagram of the experimental setup for zebrafish
heart imaging. The adult zebrafish was sedated and placed on a chasm with the
ventral side facing upwards and the ultrasound array was positioned above the heart.
(c) Simplified schematic diagram of the zebrafish heart illustrates the atrium,
ventricle and bulbus arteriosus. The red-dashed arrows indicate the direction of blood
flow and the blue-solid arrow indicates the direction of tissue movement. .......................54
Figure 5.4 Doppler flow waveforms of the dual mode PWD acquired from the flow
phantom with the pre-set flow velocities of (a) 3 cm/s, (b) 5 cm/s, (c) 10 cm/s and (d)
15 cm/s. The measured mean peak velocities are (a) 2.9 ± 0.37 cm/s, (b) 4.9 ± 0.47
cm/s, (c) 9.9 ± 0.72 cm/s and (d) 14.9 ± 0.77 cm/s. The yellow-solid lines indicate the
maximum velocity at each moment. ..................................................................................57
Figure 5.5 Doppler flow waveforms with aliasing artifacts. Doppler waveform
generated by (a) single mode PWD and (b) dual mode PWD. Raw echo signals in the
range of (c) non-aliased and (d) aliased region, which are represented as a blue-dotted
and red-dashed box, respectively. Black-solid lines represent the raw echo signals
acquired by the single mode PWD. Red-dashed and blue-dotted lines represent the
reconstructed signals of the aliased and the non-aliased calculated by interpolating the
neighboring vectors. ...........................................................................................................59
xiii

Figure 5.6 Doppler waveforms acquired from the moving wire phantom using the
dual mode PWD: (a) Doppler flow image, (b) tissue Doppler image. Doppler intensity
profiles as a function of velocities of (c) Doppler flow and (d) tissue Doppler signals.
Note that red-dotted and black-solid lines in (c) and (d) indicate the velocity profile of
wires moving toward and away the transducer, respectively. ...........................................60
Figure 5.7 B-mode image and Doppler waveforms acquired with the dual mode PWD
from a wild-type zebrafish before the heart amputation: (a) B-mode image of
zebrafish in sagittal plane, (b) Doppler flow and tissue Doppler waveforms and (c) the
magnified Doppler signals. The scales of the velocity are cm/s and mm/s for the
Doppler flow and the TD signals, respectively. Red dots in (a) indicate the location of
Doppler gates of the dual mode PWD. A-flow, E-flow and outflow in Doppler flow
and the respective pairs of Am, Em and Sm in TD are identified at the same moments
and indicated by red-dotted lines. The time duration between the red-dashed lines
of ′5′ and ′1 ′ represents for IVRT, ′3 ′ and ′4 ′ for IVCT, and ′4′ and ′5 ′ is for ET. ...........62
Figure 5.8 Amputation injury induced changes in parameter of (a) MPI, (b) IVRT and
(c) IVCT measured in the longitudinal study. (a) MPI decreased at 3 dpa in
comparison with MPI at 0 dpa (p = 0.01<0.05). (b) IVRT also decreased from 0.10 to
0.085 at 3 dpa (p = 0.01<0.05) and then returns to 0.10 at 14 dpa. (c) IVCT does not
change significantly. ..........................................................................................................64
Figure 5.9 Amputation injury induced changes in parameters related to flow and
tissue velocities: (a) Em, (b) A, (c) E, (d) E/A, (e) E/Em measured in the longitudinal
study. Both E/A and E/Em increased at 3 dpa and recover to the value before
amputation at 21 and 32 dpa, respectively. ........................................................................65
Figure 6.1 (a) B-mode image of the fetal abdomen. B-mode image shows the
structural information. (b) Color Doppler image obtained by superimposing Doppler
information on the B-mode image. Velocity information is represented as colors
(courtesy of Samsung Medison). .......................................................................................70
Figure 6.2 (a) Pulsed-wave spectral Doppler and (b) color Doppler imaging from the
hepatic vein (courtesy of Samsung Medison). ...................................................................70
Figure 6.3 Ultrasound image of common carotid artery combined B-mode, color
Doppler mode and pulsed-wave Doppler mode (courtesy of Samsung Medison). ...........71
Figure 6.4 Functional block diagram of color Doppler signal processing (I, in-phase
components of echo signal; Q, quadrature components of echo signal). ...........................72
Figure 6.5 (a) Ultrasound beam sequences for color Doppler imaging. (b) The 3-D
data matrix for color Doppler signal processing. (N
L
, the number of scanlines; N
R
, is
the number of range samples in a scanline; N
F
, the number of firing required for flow
estimation)..........................................................................................................................73
xiv

Figure 6.6 The block diagram of the quadrature demodulation.........................................74
Figure 6.7 Illustration of clutter filtering. ..........................................................................75
Figure 6.8 Position of a rotating signal vector during two successive samples i-1 and i,
showing the in-phase components I(i-1) and I(i) and quadrature components Q(i-1)
and Q(i). .............................................................................................................................77
Figure 6.9 Color map for color Doppler imaging. .............................................................80
Figure 6.10 Flow phantom for color Doppler imaging. .....................................................81
Figure 6.11 (a) Experiment setup of color Doppler imaging for zebrafish heart. (b)
Color Doppler window was positioned on the zebrafish heart for monitoring the blood
flows between heart chambers. ..........................................................................................82
Figure 6.12 Color Doppler imaging results from the flow phantom. (a) Flow away
from the array is shown in shades of blue and (b) flow towards the array is shown in
shades of red. .....................................................................................................................83
Figure 6.13 Color Doppler imaging results from adult zebrafish heart. (a) Blood flow
from the atrium to the ventricle in the phase of atrium contraction (bottom to top) is
shown in shades of red. (b) Blood flow from the ventricle to the bulbus arteriosus in
the phase of ventricle contraction (top to bottom) is shown in shades of blue. .................84

xv

ABSTRACT
High frequency ultrasound imaging, capable of achieving superior spatial
resolution in real-time, has been shown to be useful for imaging and visualizing blood
flow in ophthalmology, dermatology, and small animal research. The utilization of high
frequency array-based imaging system can alleviate the limitations of the systems with
single element transducers. This dissertation presents an investigation of high frequency
array-based imaging system and its potential biomedical applications. The system is
capable of B-mode imaging, PW-Doppler, color Doppler imaging, and RF data
acquisition. Three different types of high frequency (30 MHz 256-element linear, 20
MHz 192-element convex, and 20 MHz 48-element phased) array transducers were
implemented on the array-based imaging system. The system was also utilized for
ophthalmic imaging: 30 MHz linear array for anterior segment and 20 MHz convex array
for both anterior and posterior segments imaging of the eye. Anatomical structures, such
as cornea, iris, ciliary body, lens, and retina, choroid, and sclera layers were identified.
The high frequency PW Doppler and micro-ECG were integrated to assess the ventricular
diastolic function during heart regeneration of the adult zebrafish. Synchronized PW
Doppler with ECG signals confirmed the A-wave in response to atrial contraction (P
wave in ECG), E-wave in response to ventricular relaxation (T wave in ECG), and
ventricular outflow in response to ventricular contraction (QRS complex in ECG). The
E/A ratio is less than 1 in zebrafish at baseline, reflecting a higher active filling (A-wave)
than passive filling (E-wave) velocities in the two-chamber heart system. High frequency
dual mode pulsed-wave Doppler imaging, which provides both tissue Doppler and
xvi

Doppler flow in a same cardiac cycle, was implemented on the array-based imaging
system for monitoring the functional regeneration of adult zebrafish hearts. In the in vivo
study of zebrafish, both tissue Doppler and flow Doppler signals were simultaneously
obtained and the synchronized valve motions with the blood flow were identified. In the
longitudinal study on the zebrafish heart regeneration, the parameters for diagnosing the
diastolic dysfunction were measured, and the type of diastolic dysfunction caused by the
amputation was found to be similar to the restrictive filling. The diastolic function was
fully recovered within four weeks post-amputation. High frequency color Doppler
imaging was implemented on the array-based imaging system and evaluated by the flow
phantom and adult zebrafish in vivo studies. In the flow phantom study, constant velocity
with opposite flow directions was detected utilizing color Doppler imaging. Also, color
Doppler imaging could be used to monitor blood flows inside adult zebrafish heart and
flow directions were clearly identified by the color-coded images.

1

CHAPTER 1 Introduction
1.1 Medical Ultrasound Imaging
Ultrasound is one of the most widely used medical imaging modalities due to its
safety, portability, cost effectiveness and real-time capability. Conventional medical
ultrasound imaging systems use frequency ranges from 2 to 15 MHz, and the spatial
resolution is on the order of a few millimeters. They have been used as valuable
diagnostic tool in such medical disciplines as cardiology, obstetrics, gynecology, surgery,
pediatrics, radiology, and neurology.
Ultrasound imaging systems require an ultrasonic transducer which converts
electrical energy into acoustic energy and vice versa due to the piezoelectric effect. The
transducer transmits acoustic waves to a medium such as tissue, liquids or solid structure,
and receives reflected and scattered acoustic waves due to the inhomogeneity in a
medium. The returned acoustic waves are converted into corresponding electrical signals,
which are amplified and processed to form interpretable images.
In the earliest ultrasound systems, useful information was obtained by displaying
the amplitude of echoes as a function of time-of-flight. This is the A-mode (amplitude-
mode) ultrasound system, which display 1-D scanline. The acoustic beam of a transducer
needs to be scanned over a certain region, and multiple A-mode scanlines are obtained to
construct 2-D image. Echo amplitude in the scanlines is mapped to the brightness or gray
level of the pixel. These images are called as B-mode (brightness-mode) images.
2

Figure 1.1 Ultrasound transducers: (a) single element transducer and (b) array transducer.

Both single element transducers and array transducers are used in ultrasound
systems to perform 2-D imaging. Ultrasound imaging systems using single element
transducers require mechanical scanning to obtain 2-D images as illustrated in Figure
1.2(a) and 1.2(b). Mechanical scanning with single element transducers is the most
common method since it is relatively easy to build transducers and systems compared to
array transducers and array-based imaging systems. However, a single element transducer
has a fixed focus and therefore the image quality out of the focal zone dramatically
deteriorates. Mechanical scanning also limits its frame rate. Better image quality and
higher frame rates can be achieved by utilizing array transducers to scan and focus the
acoustic beam electronically as illustrated in Figure 1.2(c). A group of elements in an
array transducer forms a sub-aperture and it moves electronically from left to right to
form 2-D images. In transmit, the active elements in the sub-aperture are excited with
time delays in order to focus ultrasound beam at a desired focal depth. All received echo
(a) (b)
3

signals in the sub-aperture elements are dynamically focused by delay-sum beamforming
in the azimuth direction obtain one scanline of 2-D images.

Figure 1.2 Diagrams of mechanical and electronic scanning: (a) single element transducer
with mechanical linear scanning, (b) single element transducer with mechanical sector
scanning, and (c) array transducer with electronic scanning.

In addition to B-mode imaging, most clinical ultrasound imaging systems include
Doppler mode, which is based on the Doppler effect. Upon insonification by an
(a) (b)
(c)
4

ultrasound beam, the echoes scattered by blood carry information about the velocity of
blood flow. If a wave is emitted from a source moving away from an observer, its
wavelength increase, and vice versa. The frequency difference of the transmitted pulses
and received echoes is the Doppler shift frequency which can be used to calculate the
velocities of the moving objects (Shung, 2005):

0
2 cos
f
vc
f 

 (1.1)
where Δf is the Doppler shift frequency, f
0
is the center frequency of the transmitted
pulses, c is the sound velocity in a medium, and θ is the angle between the ultrasound
beam and the moving objects.
Ultrasound Doppler has been used in medical applications since the late 1950s.
Currently ultrasound Doppler is used not only to evaluate blood flows, but also to study
tissue movements. Several Doppler techniques were developed, including continuous-
wave (CW) Doppler, pulsed-wave (PW) Doppler and color Doppler imaging (CDI).

5

1.2 High-Frequency Ultrasound
1.2.1 High-Frequency B-mode Imaging
Conventional ultrasound imaging systems as mentioned above use frequencies
from 2 to 15 MHz with a resolution of the millimeter range. Spatial resolutions can be
improved by increasing center frequency of an ultrasonic transducer since the lateral (R
L
)
and axial (R
A
) resolutions can be calculated through the following equations:

##
0
L
c
R f f
f
  (1.2)

6
2
A
dB
c
R
BW

 (1.3)
where c is the sound velocity, f
0
is the center frequency of the transducer, f
#
is the f-
number defined as the focal distance to the aperture size of transducer (f
#
= Z
f
/ D, Z
f
: the
focal distance, D : the aperture size of transducer), λ is the wavelength defined as the ratio
of the sound velocity to the center frequency of transducer (c / f
0
), and BW
-6dB
is a -6 dB
bandwidth of the transducer (Foster et al., 2000). Therefore, both the lateral and axial
resolutions are proportional to the center frequency of a transducer. However, the depth
of penetration would be limited due to the high attenuation as increasing the operational
frequency of a transducer (Shung, 2005). Therefore, the trade-off should be considered
between the desired spatial resolution and depth of penetration in designing imaging
systems and transducers.

6

As a result, high-frequency ultrasound is more suitable in application requiring
high resolution but less penetration. Many clinical applications for high frequency B-
mode imaging were reported (Lockwood et al., 1996). In ophthalmology, high frequency
ultrasound scanners have been used to assess anterior segment tumors, segment lesions,
and types of glaucoma (Marigo et al., 2000; Ritch and Liebmann, 1998; Trope et al.,
1994). In dermatology, applications of high frequency ultrasound include tumor
assessments and dynamic studies of structures in the skin (Lassau et al., 1997). High
frequency B-mode imaging has also been used in studies of small animals such as mice,
rats and adult zebrafish (Foster et al., 2002; Sun et al., 2008a).

1.2.2 High-Frequency Pulsed-wave and Color Doppler Imaging
Similar to B-mode imaging, the detection limit of conventional ultrasound
Doppler extends to only the level of arterioles. Both the spatial and velocity resolutions
of conventional Doppler systems remain inadequate for studying microcirculations.
Recent studies have shown that high-frequency Doppler systems are capable of detecting
the blood velocities in capillaries (0.5 mm/s) and arterioles (5 mm/s) (Christopher et al.,
1996; Christopher et al., 1997). Therefore, developing both high-frequency B-mode
imaging and high-frequency pulsed-wave and color Doppler imaging can significantly
improve image quality and provide more information for clinical and pre-clinical studies.

7

1.3 Objective of Research
The goal of this research is to develop a high-frequency array-based imaging
system capable of B-mode, PW Doppler, color Doppler features and its application on
biomedical research. This thesis consists of seven chapters. Chapter 1 introduces general
background of a high-frequency ultrasound imaging. Chapter 2 describes the high-
frequency ultrasound array-based imaging system and implementation results of three
different types of high-frequency array transducers (linear, convex, and phased) on the
imaging system. Chapter 3 describes ophthalmic imaging using high-frequency linear and
convex array transducers for anterior and posterior segments imaging of the eye. Chapter
4 introduces an integration of high-frequency pulsed-wave Doppler and micro ECG to
assess cardiac functions in an adult zebrafish model of injury and regeneration. Chapter 5
describes a high-frequency dual mode Doppler imaging for monitoring the functional
regeneration of adult zebrafish heart. Chapter 6 presents high-frequency color Doppler
imaging for monitoring blood flow in adult zebrafish heart. Chapter 7 summarizes all
results in this research and discusses potential future works.

8

CHAPTER 2 High Frequency Ultrasound Array-Based Imaging
System
2.1 Introduction
High frequency (> 20 MHz) ultrasound provides a non-invasive imaging method
for many clinical, pre-clinical and research applications requiring superior spatial
resolution. Commercial high frequency ultrasonic biomicroscopes (UBMs) utilizing
single element transducers can obtain a spatial resolution better than 15 µm (Hozumi et
al., 2004) and detect blood velocities less than 0.5 mm/s in capillaries as small as 20 µm
in diameter (Christopher et al., 1997). While most of the high frequency ultrasound
systems use single element transducers mounted on a mechanical translation system to
form 2-D images, a number of high frequency array-based imaging systems have been
reported (Hu et al., 2011; Zhang et al., 2010). High frequency array-based imaging
systems allow dynamic focusing for transmission and reception to improve the lateral
resolution throughout the imaging depth, and its electronic scanning provides higher
frame rate. Recently, high frequency array-based ultrasound imaging systems have
become commercially available (Vevo 2100 and Vevo 3100, Visualsonics Inc., Toronto,
Canada). However, only linear array transducers are commercially available in the
market.
Significant progress in the development of high frequency linear array transducers
has been achieved in the past few years (Brown et al., 2007; Cannata et al., 2011;
Cannata et al., 2006; Lukacs et al., 2006; Ritter et al., 2002). In addition to linear array
9

transducers, high frequency convex and phased array transducers have been reported in
our lab (Chen et al., 2014; Chiu et al., 2014; Kim et al., 2009; Kim et al., 2010), and it is
required to have a high frequency array-based imaging system which can utilize these
types of array transducers.
This chapter introduces the high frequency array-based imaging system and
describes implementation results of three different types of high frequency array
transducers (linear, convex, phased) on the array-based imaging system. Details of the
imaging system are first described, followed by a discussion on phantom images acquired
using these transducers to assess the B-mode imaging performance.

2.2 High Frequency Array-Based Imaging System
2.2.1 Overall System Description
The overall system architecture of the high frequency ultrasound array-based
imaging system is illustrated in Figure 2.1. The system is composed of four main blocks:
1) transmit beamformer, 2) digital receive beamformer, 3) control, and 4) PC. Figure 2.2
shows the photograph and simplified illustration of the system.

10

Figure 2.1 Overall block diagram of the high frequency array-based imaging system. The
system is composed of four main blocks: transmit beamformer, digital receive
beamformer, control and PC.

Figure 2.2 (a) Photograph of the high frequency array-based imaging system. (b)
Simplified illustration of the system. The system is composed of eight transmit
beamformer boards, two digital receive beamformer boards, one control and backplane
board.
(a) (b)
11

The system is implemented in a programmable way that it could be reconfigured
via VHSIC Hardware Description Language (VHDL) for hardware controls and C++ for
software controls. The imaging process is started by first sending an initial trigger from
the PC to field-programmable gate array (FPGA) in control board, and the FPGA
generates and distributes control/trigger signals to other FPGAs in the transmit and the
receive beamformer boards. The FPGAs in the transmit beamformer boards generate
delayed triggers for transmit beamforming, and the FPGAs in the receive beamformer
boards store digitized RF data and perform delay-sum receive beamforming.
Beamformed RF data is fed to the FPGA in control board and transferred to the PC via
PCIe express. Finally, the image post-processing will be carried out and the resulted
images are displayed on screen in real-time or stored in the PC for further offline analysis.

2.2.2 Transmit Beamformer Board
The transmit beamformer consists of eight boards and each board has 32 channels
of pulse generator, transmit/receive (T/R) switch, low-noise amplifier (LNA) and variable
gain amplifier (VGA), and one FPGA for transmit beamforming as shown in Figure 2.2(b)
and 2.3. Trigger signals generated from the FPGA (XC3S250E, Xilinx Inc.) pass through
1-to-4 demultiplexers (SN74CB3T3253, Texas Instruments Inc.) so that eight adjacent
elements are chosen from each board. Therefore, a total 64 adjacent elements are selected
to transmit bipolar pulses. Immediately following the T/R switch, LNAs and VGAs
(AD8334, Analog Devices Inc.) are used to provide 19 and 48 dB gain respectively along
12

the signal path. Followed by the VGAs, 4-to-1 multiplexers (AD8184, Analog Devices
Inc.) are used to select the activated 64 elements out of 256 elements. The demultiplexers
and multiplexers are operated by the same control triggers generated from the FPGA to
maintain synchronization. Transmit focusing is implemented by delaying trigger signals
used for pulse generator. The time interval between trigger signals is achieved with the
delay values stored in the memory of the FPGA.

Figure 2.3 Photograph of the transmit beamformer board. Transmit beamformer board is
composed of 32 channels of pulse generator, transmit/receive (T/R) switch, low-noise
amplifier (LNA) and variable gain amplifier (VGA), and one FPGA.

13

2.2.3 Digital Receive Beamformer Board
The digital receive beamformer consists of two boards and each board has 32
channels of bandpass filter (BPF), low-noise amplifiers (LNA) and variable gain
amplifiers (VGA), analog-to-digital converter (ADC) and one FPGA as shown in Figure
2.2(b) and 2.4.

Figure 2.4 Photograph of the digital receive beamformer board. Receive beamformer
board is composed of 32 channels of bandpass filter (BPF), low-noise amplifier (LNA)
and variable gain amplifier (VGA), analog-to-digital converter (ADC) and one FPGA.

Therefore, the digital receive beamformer contains a total 64 channels. After
multiplexers from the transmit beamformer boards, passive bandpass filters (PBP-35W,
14

Mini-Circuits Inc.) are used as anti-aliasing filter to restrict the bandwidth of the input
signal, and additional LNAs and VGAs (AD8334, Analog Devices Inc.) are used to
provide another 10-30 dB gain to the filtered echo signals. Amplified signals are fed into
the analog-to-digital converters (AD9627, Analog Devices Inc.) with 12-bit resolution
and a maximum sampling frequency up to 150 MHz. Digitized echo signals from each
ADC are then fed into the FPGA (XC5V110, Xilinx, Inc.) for receive beamforming.

2.2.4 Control Board
The control board has a PCIe connector for a digital acquisition board (NI PCIe-
6537, National Instrument Inc.), clock generator/buffers and one FPGA as shown in
Figure 2.5. The FPGA (XC3S1200E, Xilinx, Inc.) generates and distributes control
signals (frame trigger, scanline trigger, mode selection trigger, and pulse repetition
frequency (PRF) trigger) to other FPGAs in the transmit and receive beamformer boards.
It also acquires beamformed RF data from two digital beamformer boards, and then
performs post-processing such as envelope detection and filtering. Processed data is
transferred to the PC via PCIe bus.

15

Figure 2.5 Photograph of the control board. Control board has a PCIe connector for a
digital acquisition board, clock generator/buffers and one FPGA.

2.2.5 Backplane Board
The backplane board has an array connector, power supply connectors, and 10
board-to-board connectors to mount eight transmit beamformer boards and two receive
beamformer boards as shown in Figure 2.2(a) and 2.2(b).

2.2.6 Graphic User Interface in PC
For real-time image display, the application software for a graphical user interface
(GUI) is written using Microsoft MFC/C++. Through the GUI as shown in Figure 2.6,
16

users can select imaging modes (B-mode and PW Doppler mode), cine function, and
apply/control digital time gain compensation (TGC). Additional post-processing for B-
mode images (log compression, scan conversion and filtering) and pulsed-wave Doppler
spectrums (filtering and fast Fourier transform) are also implemented for real-time
display.

Figure 2.6 A screen shot of graphical user interface (GUI) in PC for real-time display.

2.3 System Evaluation
Three different types of high frequency ultrasound array transducers were paired
on the array-based imaging system to evaluate the B-mode imaging performance. The
characteristics of the each array transducer are listed in Table 2.1, and Figure 2.7 shows
17

photographs of 30 MHz 256-element linear, 20 MHz 192-element convex, 20 MHz 48-
element phased array transducers.
Table 2.1 Characteristics of the ultrasound array transducers
Characteristic Linear Array Convex Array Phased Array
Number of Elements 256 192 48
Center Frequency 28 MHz 19.6 MHz 18.5 MHz
-6 dB Bandwidth 61 % 69.2 % 61 %
Element Pitch 50 µm 111 µm 37 µm

Figure 2.7 Photographs of (a) 30 MHz linear array, (b) 20 MHz convex array, and (c) 20
MHz phased array transducers.

First, the linear array transducer (Figure 2.7(a)) forms a rectangular shape of 2-D
image as shown in Figure 2.8(a). Second, the convex array transducer (Figure 2.7(b))
which is curved in a convex shape along the azimuth direction give a wider field of view
compared to linear array transducers due to the curved aperture as shown in Figure 2.8(b).
Last, the phased array transducer (Figure 2.7(c)) which has a small footprint generates
triangular-shaped images by steering beam and therefore can form a wide field of view
with a small aperture as illustrated in Figure 2.8(c).
(a) (b) (c)
18

Figure 2.8 Field of view of 2-D images corresponding to (a) linear array, (b) convex array,
and (c) phased array transducers.

2.3.1 30 MHz 256-element Linear Array Transducer
30 MHz 256-element linear array transducer with 50 µm pitch (Cannata et al.,
2011) was utilized to evaluate the B-mode imaging performance of the array-based
system. The beam was electronically focused at 6.4 mm for transmission, and
dynamically focused for reception. The echo signals were sampled with a sampling
frequency of 120 MHz. The field of view was 9.6 mm and 12.8 mm in the lateral and
axial directions, respectively. A wire phantom consisted of five 20 µm diameter tungsten
wires (California Fine Wire Co., Grover Beach, CA) was used to assess the spatial
resolution of the imaging system. Figure 2.9(a) shows the B-mode image of the wire
phantom, and Figure 2.9(b) and 2.9(c) show the lateral and axial beam profiles,
respectively. The measured -6 dB lateral and axial resolutions at the transmit focus were
118.4 µm and 73.2 µm, respectively.
(a) (b) (c)
19

Figure 2.9 (a) B-mode image of 20 µm tungsten wire phantom acquired using a 30 MHz
linear array transducer. (b) Lateral and (c) axial beam profile at the transmit focus at 6.4
mm.

Figure 2.10 shows B-mode images of a tissue-mimicking phantom. The phantom
is composed of eight blocks of tissue-mimicking material and each block had a different
mean cyst diameter ranging from 100 µm to 1090 µm. The images obtained from the
blocks with the 1090, 825, 530, and 400 µm cysts are shown in Figure 2.10(a), 2.10(b),
2.10(c), and 2.10(d), respectively.
(a) (b)
(c)
20

Figure 2.10 B-mode images of an anechoic sphere phantom with (a) 1090 µm, (b) 825
µm, (c) 530 µm, and (d) 400 µm spheres in diameter.
(a) (b)
(c) (d)
21

2.3.2 20 MHz 192-element Convex Array Transducer
20 MHz 192-element convex array transducer with 111 µm pitch (Kim et al.,
2009; Kim et al., 2010) was used to evaluate the B-mode imaging performance. The
beam was electronically focused at 20 mm for transmission, and dynamically focused for
reception. The echo signals were sampled with a sampling frequency of 100 MHz. The
field of view was 32 mm and 31 mm in lateral and axial directions, respectively. The wire
phantom image is shown in Figure 2.11(a), and Figure 2.11(b) and 2.11(c) show the
lateral and axial beam profiles, respectively. The measured -6 dB lateral and axial
resolutions at the transmit focus were 165 µm and 75 µm, respectively.

Figure 2.11(a) B-mode image of 20 µm tungsten wire phantom acquired using a 20 MHz
convex array transducer. (b) Lateral and (c) axial beam profile at the transmit focus at 20
mm.
(a)
(b)
(c)
22

Figure 2.12 shows B-mode images of a tissue mimicking phantom. The images
obtained from the blocks with the 1090 and 825 µm cyst are shown in Figure 2.12(a) and
2.12(b), respectively. Figure 2.12(c) and 2.12(d) shows images obtained from a custom-
built wall-less tube tissue mimicking phantom with 2 and 4 mm in diameter.

Figure 2.12 B-mode images of an anechoic sphere phantom with (a) 1090 µm, (b) 825
µm spheres in diameter. (c) Cross-sectional and (d) longitudinal images of wall-less tube
tissue mimicking phantom with 2 mm and 4 mm in diameter.

(a) (b)
(c) (d)
23

2.3.3 20 MHz 48-element Phased Array Transducer
20 MHz 48-element phased array transducer with 37 µm pitch (Chiu et al., 2014)
was utilized to evaluate the B-mode imaging performance. The beam was electronically
focused at 6 mm for transmission, and dynamically focused for reception. The echo
signals were sampled with a sampling frequency of 120 MHz. The field of view was 18
mm and 13 mm in lateral and axial directions, respectively. The wire phantom image is
shown in Figure 2.13(a) and Figure 2.13(b) and 2.13(c) show the lateral and axial beam
profiles, respectively. The measured -6 dB lateral and axial resolutions at the transmit
focus were 210 µm and 79.7 µm, respectively.

Figure 2.13 (a) B-mode image of 20 µm tungsten wire phantom acquired using a 20 MHz
phased array transducer. (b) Lateral and (c) axial beam profile at the transmit focus at 6
mm.
(a)
(b)
(c)
24

2.4 Summary
The high frequency array-based imaging system paired with three different types
of high frequency array transducers (linear, convex, phased) was described in this chapter.
The four main system blocks of transmit beamformer, receive beamformer, control, and
PC were introduced and the functions of each block were briefly described. In order to
support different types of array transducers, the hardware programming in FPGAs for
transmit/receive beamforming and system control, and the software programming in PC
for image display were designed and implemented accordingly.
The imaging performances of each array transducer were evaluated using the wire
phantom. The -6 dB lateral and axial resolution was determined to be 118.4 µm and 73.2
µm for 30 MHz 256-element linear array, 165 µm and 75 µm for 20 MHz 192-element
convex array, and 210 µm and 79.7 µm for 20 MHz 48-element phased array transducer,
respectively. Also, anechoic sphere phantom and tissue mimicking phantom images
demonstrated its capability to detect small anechoic spheres in a tissue-mimicking
background.

25

CHAPTER 3 High Frequency Ultrasound Ophthalmic Imaging
3.1 Introduction
Ultrasound ophthalmic imaging allows non-invasive and real-time visualization of
ocular anatomy and pathology. The main advantage of ultrasound over optical coherence
tomography (OCT) is to provide real-time cross-sectional images of the inner structure of
the eye even in the presence of optical opacities (Silverman, 2009) and better depth of
penetration. High frequency ultrasound biomicroscopy (UBM) systems have been used
for imaging and characterization of the cornea (Reinstein et al., 1993; Reinstein et al.,
2000; Reinstein et al., 1994a; Reinstein et al., 1994b), glaucoma diagnosis (Ritch and
Liebmann, 1998; Trope et al., 1994), visualization of lens implants (Garcí a-Feijoó et al.,
2003; Kim et al., 1998), and diagnosis of tumors (Marigo et al., 2000), cysts (Marigo et
al., 1999), and foreign bodies (Deramo et al., 1999). These systems employ mechanically
scanned, fixed focus single-element transducers.
Array transducers are composed of a series of independent elements. Array
transducers can focus ultrasound beam electronically, unlike single-element transducers
which are constrained to focus at a fixed point. Annular arrays, in which independent
transducer elements are arranged in concentric rings, can focus ultrasound beam
electronically by applying appropriate time delays to the excitation pulses, but
mechanical scanning is still needed to form 2-D images.
While most of the current ophthalmic ultrasound systems use mechanically
scanned single-element transducers, array-based ultrasound probes are the dominant
26

technology in other clinical applications. By controlling pulse emission timing of the
many elements and adding appropriate time delays to echo data received by each element,
not only can mechanical scanning be done away with, but dynamic focusing can also be
achieved, with a resultant improvement in lateral resolutions.

Figure 3.1 Clinical images of the eye: (a) choroidal tumor and retinal attachment, (b)
retinal detachment, (c) iris crypt, and (d) accommodative lens movement (Courtesy of
Sonomed, Inc.)

Ophthalmic imaging can be separated into two categories: anterior segment
imaging and posterior segment imaging of the eye. Currently available commercial
ultrasonic biomicroscopy (UBM) systems use 35 to 100 MHz single-element transducers
for imaging the anterior segment consisting of the cornea, iris, ciliary body and anterior
27

lens, whereas 7 to 20 MHz transducers are used for imaging the posterior segment
consisting of retina, sclera and optic nerve. Figure 3.1 shows examples of clinical images
of the eye obtained by a commercial ophthalmic imaging system.
In this chapter, we present ophthalmic imaging using two types of high frequency
array transducers: anterior segments imaging with 30 MHz 256-element linear array and
posterior segments imaging with 20 MHz 192-element convex array transducer. Excised
bovine, porcine and rabbit eyes were prepared for imaging experiments.

3.2 Experimental Arrangement
Two different types of array transducers described in Chapter 2 were utilized for
high frequency ultrasound ophthalmic imaging: a 30 MHz linear array transducer with
256 elements (Cannata et al., 2011) and a 20 MHz convex array transducer with 192
elements (Kim et al., 2009; Kim et al., 2010). Excised bovine, porcine and rabbit eyes
(Sierra for Medical Science, Whittier, CA) were prepared for imaging experiments. The
size of the excised bovine, porcine and rabbit were around 5, 3, and 2 cm in diameter,
respectively.
For the anterior segment imaging of the eye, 30 MHz linear array was used since
the field of view of the linear array is 9.6 mm and 12.8 mm in lateral and axial directions,
respectively. Figure 3.2(a) shows a structure of the eye and a red-dashed box indicates an
expected imaging plane with the linear array transducer.
28

For the posterior segment imaging of the eye, 20 MHz convex array was used
because of the wider field of view (46 mm and 41 mm in lateral and axial directions,
respectively) compared to the linear array transducer. Figure 3.3(a) shows a structure of
the eye and a red-dashed box indicates an expected imaging plane with the convex array
transducer.
Excised eye was placed on a plastic holder in DI water tank, and the linear array
and convex array transducer was placed above the eyes as shown in Figure 3.2(b) and
3.3(b), respectively. Note that the convex array for posterior segment imaging was
positioned over ciliary body to avoid the strong reflection from the lens.

Figure 3.2 Anterior segment imaging of the eye using a 30 MHz 256-element linear array
transducer: (a) the linear array transducer is placed over cornea for anterior segment
imaging. Red-dashed box indicates an expected imaging plane. (b) Picture of the
experimental setup for the excised bovine eye.
(a) (b)
29

Figure 3.3 Posterior segment imaging of the eye using a 20 MHz convex array transducer:
(a) the convex array is placed over ciliary body for posterior segment imaging. (b) Picture
of the experimental setup for the excised bovine eye.

3.3 Results
3.3.1 Anterior Segment Imaging using 30 MHz Linear Array Transducer
Figure 3.4 shows cross-sectional images of anterior segment of eyes: (a) bovine,
(b) porcine, and (c) rabbit eye. The anatomical details, such as cornea, iris, ciliary body
and lens, are clearly visible. Since tumors within the iris is cyst type and changes the
thickness of the iris, the system may used to diagnose tumors in the iris and evaluate the
depth of an iris tumor. Also, the system can be used to measure the anterior chamber
angle and diagnose the potential disease in the iris.
(a) (b)
30

Figure 3.4 B-mode images of anterior segments of excised (a) bovine, (b) porcine, and (c)
rabbit eye.
(b)
(c)
(a)
31

3.3.2 Anterior and Posterior Segments Imaging using 20 MHz Convex Array
Transducer
Figure 3.5(a) and 3.5(b) show cross-sectional images of anterior and posterior
segments of bovine eye, respectively. The anatomical details of anterior segment such as
cornea, iris, and lens, and posterior segment such as retina/choroid/sclera layers, are
visible. Note that 20 MHz convex array has a wider field of view compare to 30 MHz
linear array as shown in 3.4(a) and 3.5(a).

Figure 3.5 B-mode images of (a) anterior and (b) posterior segments of excised bovine
eye.

3.4 Summary
Conventional high frequency ultrasound biomicroscopy (UBM) systems for
ophthalmic imaging utilize mechanically scanned, focused single-element transducers. In
this chapter, high-frequency linear and convex array transducer for ophthalmic imaging,
which does not require mechanical scanning, were described. Detailed structures of
(a) (b)
32

anterior segment of the excised eyes (bovine, porcine, and rabbit) were clearly identified
with 30 MHz linear array transducer. The anatomical details, such as cornea, iris, ciliary
body and lens, are clearly visible. Also, both anterior and posterior segments of the
excised bovine eye were identified with 20 MHz convex array transducer which can
achieve a wider field of view and deeper penetration depth compared to the linear array
transducer. The anatomical details, such as cornea, iris, lens, and retina/choroid/sclera
layers are clearly visible. High frequency ultrasound ophthalmic imaging may be useful
for functional anatomic studies related to the examination of the cornea, ciliary body and
angle structures by imaging of the anterior segment of the eye, and retina, choroid and
sclera layers by imaging of the posterior segment of the eye.

33

CHAPTER 4 Interfacing High Frequency Ultrasound Pulsed-
wave Doppler and Micro-Electrocardiogram to Assess Ventricular
Function in a Zebrafish Model of Injury and Regeneration
4.1 Introduction
Adult mammalian ventricular cardiomyocytes have a limited capacity to
regenerate from the significant loss of myocardium (Bergmann et al., 2009; Bersell et al.,
2009; Hsieh et al., 2007). Injured human hearts heal by forming scar tissue, which lack
contractile phenotype and constitute a substrate for arrhythmia and ventricular
remodeling (Hahn and Schwartz, 2008). However, non-mammalian vertebrates, such as
Zebrafish (Danio rerio), are capable of removing scar tissue during heart regeneration,
thus providing a genetically tractable model in identification of barriers to sufficient
cardiac regeneration in mammals (Chablais et al., 2011; González-Rosa et al., 2011; Poss
et al., 2002).
High-frequency ultrasound has provided a non-invasive approach to interrogate
the intracardiac structures and hemodynamics in small animals. The high-frequency
ultrasound system capable of 75 MHz B-mode imaging and 45 MHz pulsed-wave (PW)
Doppler measurements has allowed for assessing ventricular filling and diastolic flow
reversal in the zebrafish heart (Sun et al., 2008a). The development of a high-frame rate
duplex ultrasound array imaging system has further allowed for both B-mode imaging
and PW Doppler measurements of the mouse heart (Zhang et al., 2010). Thus, high-
34

frequency PW Doppler provides opportunity to assess passive filling of the ventricle and
active filling during atrial systole.
Despite having a two-chambered heart and lacking a pulmonary vasculature, the
zebrafish heart action potential (AP) shape and electrocardiogram (ECG) patterns are
remarkably similar to those of humans in P waves, QRS complexes, and T waves (Milan
et al., 2006; Sedmera et al., 2003). By using the microelectrodes, the dynamic changes in
corrected QT (QTc) intervals in response to ventricular amputation were demonstrated
(Yu et al., 2010). Despite histological evidence of gap junctions such as CX43 in the
regenerated cardiomyocytes, ECG repolarization (QTc intervals) remained prolonged
when compared to the sham at 60 days (Yu et al., 2010), implicating the delayed rectifier
potassium current (I
kr
) (Verkerk and Remme, 2012). Thus, micro-ECG (µECG) offers a
non-invasive approach to assess electrical rhythms during cardiac repair.
In this chapter, integrating PW Doppler with surface µECG signals to interrogate
the ventricular diastolic function during heart regeneration was described. Synchronous
PW Doppler with µECG signals allowed for identification of passive filling (E-wave) and
active filling (A-wave) of the ventricle. Unlike that of human hearts, the A-wave is
greater than the E-wave in zebrafish, and the E/A ratio is less than 1 at baseline. E/A
ratios increased at 3 days post injury (dpi) due to an increase in E-waves. The E/A ratios
and E-waves gradually decreased at 35 dpi and 65 dpi toward the baseline. PR and RR
intervals remained unchanged during cardiac regeneration; however, QTc intervals
remained prolonged. These findings demonstrate that integrating PW Doppler and µECG
35

provides a novel strategy to elucidate changes in hemodynamics, cardiac rhythm, and
ventricular function during cardiac repair. Distinct from humans, the E/A ratio is less
than 1 at the baseline level and passive filling (E-wave) increased in response to injury in
a two-chamber system, in which pressure gradient across the atrioventricular (AV) valve
is higher than compared with the ventriculobulbar (VB) valve.

4.2 Designs and Methods
Zebrafish experiments were performed in compliance with the Institutional
Animal Care and Use Committees (IACUC) at the University of Southern California.
Animals were euthanized for signs of suffering in compliance with the Guide for the Care
and Use of Laboratory Animals of the National Institutes of Health. Adult zebrafish (>1
year old), 3-4 cm in length (Tong’s Tropical Fish and Supplies), were maintained in a
recirculating aquarium system (Aquaneering, Inc.) that provides a physiological
environment for zebrafish habitat, including automatic light cycle, temperature control at
28°C, and pH monitoring.
4.2.1 PW Doppler Acquisition
Blood flow velocities in the zebrafish heart were measured using a high frequency
ultrasound array imaging system (Hu et al., 2011) with a 30 MHz 256-element linear
array transducer (Cannata et al., 2011). The sedated zebrafish was placed on a test bed
with its ventral side facing upward. The array transducer mounted on a mechanical
positioner placed above the ventral side of the zebrafish. Under the guidance of B-mode
36

imaging, the Doppler gate was positioned inside the ventricle to measure inflow
velocities from the atrium as shown in Figure 4.1(a). The pulse repetition frequency (PRF)
for PW Doppler was set to be 9.5 kHz and the estimated Doppler angle was 0°, since the
blood flow of the zebrafish cardiac chambers was in the dorsal–ventral direction. PW
Doppler signals for the peak early diastolic velocity (E-wave) and the peak late diastolic
velocity (A-wave) were recorded for the control (sham) and the injury groups for 3
seconds and were stored for further offline analysis using Matlab.
The signal processing of PW Doppler was based on in-phase and quadrature (IQ)
demodulation and complex Fast Fourier Transform (cFFT) (Aydin et al., 1994). The
Doppler signals were first IQ demodulated and then low-pass filtered to remove
harmonics and to reduce noise. A wall filter was also used to remove clutter signals.
Doppler shift frequency was obtained by processing the IQ demodulated Doppler signals
using cFFT to generate Doppler spectrum. The Doppler shift frequency was converted to
velocity using the equation (Shung, 2005):

2 cos
d
f
vc
f 
 (4.1)
where f
d
is the measured Doppler shift frequency, f is the center frequency of the
transducer, c is the sound velocity in blood (1540 m/s), and θ is the angle between the
ultrasound beam and the direction of the flow.

37

4.2.2 ECG Acquisition
Before measurement, an open-chest procedure was performed and the silver
lining layer underneath the fish skin was removed to allow for detection of ECG signals
through the microelectrode. The sedated fish (in 0.04% Tricaine methanesulfonate–
Tricaine) were first placed in a damp sponge, ventral side up, and then the open-chest
surgery was carried out (Sun et al., 2009; Yu et al., 2010). For ECG acquisition, the
working electrode was positioned closely above the ventricle between the gills, while the
corresponding reference electrode was placed close to the tail.
The signals were amplified by 10,000-fold and filtered between 0.1 and 500 Hz at
a cutoff frequency of 60 Hz (notch). Wavelet transform and thresholding techniques were
used to enhance signal-to-noise ratios for the individual ECG recordings (Sun et al.,
2009).
ECG signals were analyzed for P waves, QRS complexes, QT, and RR intervals.
QT intervals were corrected for heart rate variability due to the use of sedative agent
(Tricaine) as

c
QT
QT
RR
 (4.2)

4.2.3 Simultaneous Acquisition of PW Doppler and ECG
To perform ultrasound PW Doppler and ECG measurements simultaneously, the
sedated fish was secured on a test-bed immersed in diluted Tricaine (0.02%) inside a
38

container. The aquatic environment was necessary to propagate and receive ultrasound
signals at a distance, while the low concentration of Tricaine helped to keep the fish
sedated for 10-15 minutes during the experiment. The ultrasound array transducer was
placed vertically above the ventral side of the fish at a distance of about 6 mm, while the
two ECG electrodes were introduced laterally as shown in Figure 4.1(b). The ECG
electrodes were customized to give free access to the array transducer. Experiments were
initially performed independently to precisely locate the array transducer and the ECG
electrodes, followed by simultaneous measurement. The ultrasound system sent a trigger
signal to the ECG recording system when PW Doppler recording started to synchronize
both PW Doppler and ECG recordings.

Figure 4.1 (a) The schematic diagram of PW Doppler and ECG systems. (b) Picture of
the experiment setup for simultaneous measurement of PW Doppler and ECG.

(a) (b)
39

4.3 Results
4.3.1 Synchronization of PW Doppler and ECG signals
Synchronized PW Doppler and ECG recording confirmed the A-wave in
response to atrial contraction (P wave in ECG) as indicated by the red dashed line and E-
wave in response to ventricular relaxation (T wave in ECG) by the yellow dashed line as
shown in Figure 4.2. PW Doppler signals for ventricular outflow were also detected,
following the QRS complex.

Figure 4.2 Synchronized Doppler and ECG recording allowed for identification of A-
wave in response to atrial contraction (P wave in ECG) as indicated by the red dashed
line, and E-wave to ventricular relaxation (T wave in ECG) by the yellow dashed line.

40

Thus, synchronized ECG signals validated the hemodynamics events as
demonstrated by PW Doppler: the P wave (atrial contraction) corresponded to the A-
wave, the T wave followed ventricular relaxation corresponded to the E-wave, and QT
intervals corresponded to ventricular outflow.

4.3.2 The Implication of E/A Ratio for Diastolic Function
In humans, the E/A ratio is greater than 1 for the normal ventricular diastolic
function. In adult zebrafish, A-wave velocity is greater compared with the E-wave as
shown in Figure 4.3, and the E/A ratio is less than 1, suggesting a distinct cardiac
physiology in the two-chamber system (Grego-Bessa et al., 2007). In response to injury,
the E/A ratios increased due to an increase in the E-wave at 3 dpi, while they remained
unchanged in sham fish. Starting at 35 dpi, E/A ratios gradually normalized to the
baseline level as shown in Figure 4.3 and 4.4(c).

4.3.3 Cardiac Rhythms in Response to Injury
While PR and RR intervals remained unchanged, the QTc intervals remained
prolonged at 65 dpi as shown in Figure 4.5. Synchronizing P waves and QT intervals
with A- and E-waves offered a real-time and noninvasive approach to couple
hemodynamics with electromechanical coupling during cardiac repair.

41

Figure 4.3 Representative coregistration of PW Doppler signals with ECG signals from 0
days post injury (dpi) to 3, 35, and 65 dpi. The baseline PW Doppler and ECG signals
were established on 0 dpi. E-wave velocity increased at 3 dpi and gradually decreased
toward the baseline.

42

Figure 4.4 Injury induced hemodynamics changes. (a) Injury of the zebrafish ventricle
significantly increased E-wave velocities at 3 dpi, which regressed toward the baseline
levels at 35 dpi in comparison with the sham. (b) A-wave velocities decreased at 35 and
65 dpi in comparison with the sham. (c) Injury of the zebrafish ventricle significantly
increased E/A ratios at 3 and 35 dpi, which regressed to the baseline levels at 65 dpi. In
humans, the E/A ratio is clinically assessed for ventricular compliance and it is greater
than 1 for the normal ventricular diastolic function. In zebrafish, the E/A ratio is less than
1 at baseline.

Figure 4.5 Injury induced electrophysiological changes. (a) PR intervals and (b) RR
intervals remained unchanged between the injury and sham. (c) The QTc intervals were
prolonged in response to injury and did not recover.

(a) (b) (c)
(a) (b) (c)
43

4.4 Discussions
This study elucidates hemodynamics and electromechanical coupling of
ventricular function in a zebrafish model of heart regeneration. Coregistration of P and T
waves in ECG validated the direction and magnitude of velocity profiles across the AV
valves in PW Doppler, as expressed by E/A ratios for ventricular diastolic function.
Unlike humans, the E/A ratio is less than 1 in zebrafish at baseline, reflecting a higher
active filling (A-wave) than passive filling (E-wave) velocities during diastole in the two-
chamber heart system. The dynamic changes in E/A ratios in response to injury
implicated restoration of the diastolic function. While zebrafish has been a well-
recognized vertebrate model for regenerative medicine, its small size and aquatic nature
poses a bioengineering challenge to interrogate cardiac hemodynamics. The increase in
the E-wave or E/A ratios at 3 dpi and subsequent normalization to the baseline levels at
65 dpi seemed to be in parallel with scar regression (González-Rosa et al., 2011). The
dense trabecular network in adult zebrafish may be implicated in the E/A ratios < 1.
Assessing the T wave in ECG was challenging due to mechanical interference
from low-frequency components. In ECG signals, T waves remain in the low-frequency
range and are usually indistinguishable with the mechanical noises from cardiac
contraction and gill respiration. The coregistration of PW Doppler with ECG signals
enables unequivocal identification of T wave signals during cardiac regeneration. Thus,
electrical and mechanical coupling can be noninvasively interrogated in real-time by
ECG and E/A ratios. Overall, synchronizing PW Doppler with ECG signals is synergistic
to study zebrafish hemodynamics and ventricular function. The presence of T wave and P
44

wave were coregistered with the PW Doppler E- and A-waves to assess the inflow
profiles from the atrium to the ventricle. In zebrafish, E/A <1 at baseline is observed,
suggesting a distinct physiology in the two-chamber system, in which atrial systole
generates high ventricular filling pressure in the setting of a highly trabeculated ventricle.
Our integrated approach opens a new avenue to monitor hemodynamics and ventricular
function with translational implication to assess small animal models of arrhythmias and
cardiomyopathy.

45

CHAPTER 5 High Frequency Dual Mode Pulsed-Wave Doppler
Imaging for Monitoring the Functional Regeneration of Adult
Zebrafish Hearts
5.1 Introduction
Zebrafish has been used as a small animal model to study human heart diseases
due to its fully sequenced genome (Bakkers, 2011; Thisse and Zon, 2002) and
regenerative capability (Poss et al., 2002). After 20% of its ventricular apex is amputated,
fibrin clots are formed to block the hemorrhage followed by regeneration of the damaged
myocardium (Lien et al., 2012). Those morphological recoveries are well identified
through the histology of sacrificed fish hearts.
Functional recoveries were investigated by measuring either the electrical
conduction of myocardium or the hemodynamics of the fish hearts. A recent study that
used optical voltage mapping technique to measure the surface potential distributions of
the injured zebrafish hearts found that the repolarization on the wound site was recovered
between two and four weeks post-injury (Kikuchi et al., 2010). However, this approach
requires isolation of the heart from the sacrificed fish, which limits further follow-up. In a
non-invasive method, a novel zebrafish electrocardiogram (ECG) was developed to
assess the extension of drug-induced QT intervals, which further implied changes in
ventricular repolarization (Milan et al., 2006). During the measurement, ECG recordings
were conducted outside of the aqueous environment requiring a perfusion system for
preventing hypoxia, and the zebrafish was paralyzed with a sodium channel blocker to
46

suppress gill motion. However, this method is limited in that it is unclear whether the
findings are the result of the injury or from the side effects caused by the gill-motion
suppression treatments. In other studies, Doppler echocardiography has been employed
for non-invasive measurement of parameters directly related to hemodynamics. Blood
flow in zebrafish hearts was investigated with a low-frequency (7 and 8.5 MHz)
ultrasound array imaging system. Its diastolic functions were assessed by measuring the
slopes of the rising or falling edge of the Doppler waveforms, generated by the early
diastolic blood flow under varying ambient temperature (Ho et al., 2002). However, the
size of the Doppler gate was too large (greater than 400 µm) relative to that of the fish
heart (approx. 1 mm), rendering it very difficult to measure flow signals from a specific
location within the zebrafish heart. In another study using a high-frequency (45 MHz)
ultrasound imaging system, flow signals in specific regions such as bulbus arteriosus,
ventricle and atrium visualized were detected; however, the measurement of flow itself
did not provide adequate information for assessing the functional recovery of the fish
hearts (Sun et al., 2008b).
In medical ultrasound imaging, both tissue Doppler (TD) and Doppler flow modes
have been employed for diagnosing human cardiac dysfunctions (Anderson, 2007). While
ventricular systolic dysfunction can be assessed by measuring the stroke volume and
myocardial performance index (MPI), diastolic dysfunction can be assessed by measuring
the ratio (E/A) of the peak velocities of early and late diastolic flow (E and A,
respectively), the ratio (E/Em or E/E′) of E and the peak velocities of early diastolic
myocardial relaxation velocity (Em or E′) (Nagueh et al., 2009). Note that the lower-
47

case ′m′ for myocardial (Em) and the superscripted prime symbol (E′) are used to
differentiate TD from Doppler flow. The zebrafish heart diastolic dysfunction, resulted
from heart injuries, may also be diagnosed with the same parameters used for human
hearts. However, TD of zebrafish hearts has not been reported to the best of our
knowledge, and the synchronization between TD and Doppler flow is challenging for
investigating heart dysfunctions with arrhythmia.
In this chapter, we present a novel method of dual mode pulsed wave Doppler
(PWD) imaging, which acquires both TD and Doppler flow signals at the same time. The
proposed method is developed and implemented in a high-frequency (30 MHz) linear
array imaging system. TD beams, transmitted at lower pulse repetition frequency (PRF)
than that of Doppler flow, are interspersed among the Doppler flow beam sequences. The
performance of the dual mode PWD was validated using flow and moving wire phantoms
which were designed to generate the regulated flow and the motion patterns. Adult
zebrafish with amputated hearts was prepared, and longitudinal studies were conducted to
observe the functional recoveries during heart regeneration. The nature of diastolic
dysfunction was diagnosed by analyzing the parameters associated with both Doppler
flow and TD signals, and the functional recoveries of the amputated zebrafish hearts were
observed.

48

5.2 Principles and Implementation
5.2.1 Single mode pulsed wave Doppler
In single mode PWD, blood flow signals are detected by transmitting multi-cycled
bursts at a PRF to where the Doppler gate is located. Here, PRF is decided by the target’s
maximum velocity, calculated with the following equation

max 0
max
4 cos vf
PRF
c

 (5.1)
where v
max
is the maximum velocity of imaging targets, f
0
is the center frequency of
transmit, θ is the angle between the flow and the ultrasound beam, and c is the speed of
sound (1540 m/s). Figure 5.1(a) depicts the implemented Doppler sequences at 9.5 kHz
PRF. The received echo signals are demodulated into in-phase (I) and quadrature (Q)
signals, and wall filters are applied to remove tissue clutters. The filtered signals are
Fourier transformed, and the result forms a Doppler scanline (Aydin et al., 1994). Note
that the Doppler shift frequency is converted into velocity using the following equation
(Jensen, 1996)

0
2 cos
f
vc
f 

 (5.2)
where Δf is the measured Doppler shift frequency and f
0
is the center frequency of the
transducer.

49

5.2.2 Dual mode pulsed wave Doppler
The proposed dual mode PWD has two gates that can be located at different
locations within the B-mode field of view. One gate is used to detect the blood flow
signals and the other for tissue movements. Because the velocity of blood flow is faster
than that of tissue movements, PRF for Doppler flow (FD) is set 10 times higher than that
of TD. Dual mode PWD is implemented by interleaving TD with FD sequences as shown
in Figure 5.1(b), where TD sequence with a lower PRF replaces FD sequences.

Figure 5.1 Beam sequences of implemented PWD: (a) Single mode PWD and (b) dual
mode PWD. The location of the gates for the dual mode PWD can be located at different
lateral and axial positions from each other. FD is Doppler flow and TD is tissue Doppler.

The missing flow vectors, caused by interleaved TD sequences, are estimated by
averaging the neighboring echoes before and after the missing vector. As illustrated in
Figure 5.1(b), the missing flow vector in Nth sequence is estimated by averaging the
echoes corresponding to the sequences of N-2, N-1, N+1 and N+2. The echo signals
corresponding to the FD and the TD are separated from the acquired data for each
Doppler processing.
(a) (b)
50

5.3 Experimental Arrangement
5.3.1 System Setup
Dual mode PWD was implemented with a custom-designed 64-channel high-
frequency ultrasound imaging system (Hu et al., 2011) operating a 30 MHz linear array
transducer with 256 elements (Cannata et al., 2011). Electronically focused beams were
transmitted to the Doppler gate, and the returned echo signals were digitized with a
sampling frequency of 120 MHz. The digitized data were beamformed and stored for
further offline Doppler processing using a custom-made Matlab (Matlab 2011b,
MathWorks, MA) program.

5.3.2 Phantom Study
For the quantitative evaluation of the implemented dual mode PWD, studies on
flow and moving wire phantoms were performed. The flow phantom having a polyimide
tube with an inner diameter of 510 µm was fabricated to evaluate the performance of
measuring flow velocities. The blood-mimicking fluid prepared by mixing silicon dioxide
particles in DI water was injected into the tube, and the flow velocity was controlled by a
syringe pump (NE-1000 Multi-PhaserTM, New Era Pump System Inc., NY). Under the
guidance of B-mode imaging, the gate for Doppler flow measurement was placed inside
the tube, and the TD gate was placed at the wall of the polyimide tube as illustrated in
Figure 5.2(a). The PRFs of flow and tissue PWD were set to be 9.5 kHz and 950 Hz
which could detect the maximum velocities of 25.5 and 2.55 cm/s with the measured
51

Doppler angle of 61.4°, respectively. Four different flow velocities, 3, 5, 10, and 15 cm/s,
were generated using the syringe pump.

Figure 5.2 Experimental setup for (a) flow phantom and (b) moving wire phantom. The
flow phantom is composed of a polyimide tube with an inner diameter of 510 µm, and
flow velocity is controlled by a syringe pump. The moving wire phantom is composed of
two tungsten wires of 20 µm in diameter. Black dots within the Doppler gates are
representing the cross sections of wire targets.

The same flow phantom was used to simulate the Doppler aliasing artifact caused
by the flow speed exceeding the upper detectable velocity. While constant flow was
generated and flowed through the tube, one side of the tube was clamped and released by
a clip manually to disturb the flow so as to mimic pulsatile stream. For this experiment,
single mode PWD was used to acquire Doppler signals, and the echo signals
corresponding to TD sequences were replaced with a vector calculated by averaging the
neighboring echoes before and after the TD sequences.
The performance of TD was evaluated by using a custom-designed moving wire
phantom. The phantom having two tungsten wires of 20 µm in diameter was placed in a
container filled with DI water. The transducer was mounted on a motorized three-axis
stage (SGSP 20, Sigma KOKI Co., Japan), and its surface was positioned above the wire
(a) (b)
52

targets as shown in Figure 5.2(b), where the black dots within the Doppler gates denote
the cross sections of wire targets. The locations of each Doppler gate in depth were fixed
at the transducer's transmit focal point of 6.4 mm, and the distance between two Doppler
gates in lateral direction was set at 500 µm, equal to the distance between two wires. The
transducer was translated up and down at a speed of 1 mm/s to make the Doppler gates
move across the wire targets instead of moving the wires. The PRFs for Doppler flow and
TD were set to be 9.5 kHz and 950 Hz, respectively.

5.3.3 Adult Zebrafish Heart Doppler Imaging
All adult zebrafish experiments were preformed in accordance with protocols
approved by the Institutional Animal Care and Use Committee (IACUC) at the
University of Southern California. Zebrafish heart Doppler imaging was performed one
week prior to ventricular amputation and 3, 7, 14, 21 and 32 days post amputation (dpa)
to monitor functional changes of the heart during regeneration process. A total of five
adult zebrafish were studied and their mean body size (length) was 40.8 ± 3.6 mm (mean
± s.d.). The zebrafish was anesthetized for 30 seconds by submerging it in 0.08% tricaine
solution (MS-222, Sigma-Aldrich, MO) followed by removing scales around the
zebrafish heart. The fish was then put into a chasm on one side of a soft sponge to fix its
position of ventral side facing upwards as shown in Figure 5.3(a) and 5.3(b), whereas the
other side was attached to the bottom of a water chamber with a double-sided tape. The
chamber was filled with 0.04% tricaine solution to perform ultrasound imaging under
53

anesthesia at room temperature of 26º C. Using B-mode imaging to display the fish’s
sagittal plane of the heart which shows the largest cross section, the fish was repositioned
to place one Doppler gate at the entrance of bulbus arteriosus in between the ventricular
outflow tract (VOT) and the atrioventricular valve for detecting the flow and TD signals,
respectively. The position of the zebrafish heart was adjusted to make the direction of
atrioventricular blood flow perpendicular to the transducer’s surface which was parallel
to the valve as illustrated in Figure 5.3(c). Therefore, the estimated Doppler angle for
detecting the atrioventricular flow was 0°. PRFs for flow and tissue PWD were set as 9.5
kHz and 950 Hz, respectively. After the gates were located, the B-mode was frozen and
Doppler data acquired in a real time and post-processed by custom-designed Matlab
software.

54

Figure 5.3 (a) The picture and (b) the diagram of the experimental setup for zebrafish
heart imaging. The adult zebrafish was sedated and placed on a chasm with the ventral
side facing upwards and the ultrasound array was positioned above the heart. (c)
Simplified schematic diagram of the zebrafish heart illustrates the atrium, ventricle and
bulbus arteriosus. The red-dashed arrows indicate the direction of blood flow and the
blue-solid arrow indicates the direction of tissue movement.

5.3.4 Parameters for Assessing Diastolic Dysfunction
Zebrafish hearts, like the human’s, circulate blood with cyclic systolic and
diastolic phases which are performed by the contractions and relaxations of heart muscles.
In human myocardial injuries or diseases, abnormalities on the heart cycles have been
observed by using parametric analysis of ultrasonic Doppler imaging method. The
zebrafish diastolic dysfunction caused by the ventricular amputation may also be
diagnosed and classified as one of subtypes of the diastolic dysfunction, for example,
impaired relaxation, pseudo-normal and restrictive filling by using the parameters of
(a)
(b)
(c)
55

Doppler flow and TD echocardiography (Anderson, 2007). To assess overall performance,
MPI, defined by the equation below, is employed (Tei et al., 1995 ):

IVCT IVRT
MPI
ET

 (5.3)
where ET is the ejection time during the systolic phase, IVCT is the isovolumic
contraction time for ventricular muscles to prepare for the flow ejection to the aorta and
IVRT is the isovolumic relaxation time for reducing the ventricular pressure, which is
caused by early passive filling blood flow (E-flow) from the atrium. Here, IVRT is
variable depending on the compliance of the ventricular wall and affected by the
damaged ventricle which causes changes in its stiffness and diastolic functions. In
monitoring the velocity of heart dynamics, E, A and E/A are used to assess blood flow
circulation and Em for monitoring tissue motion at atrioventricular valve. Em is reported
to be related to the ventricular relaxation time, and E/Em represents the pressure gradient
between the atrium and the ventricle. In previous studies on zebrafish echocardiography
(Ho et al., 2002), E-flow, A-flow and ejection flow were identified, and the sequences of
these flows were shown to be similar to the flow patterns observed in the human heart,
although the range of these parametric values between human and zebrafish are different
due to the structural differences of the hearts, for example, number of chambers and size.
In addition, the patterns of zebrafish electrocardiography exhibit the same patterns of P
wave, QRS complex, T wave as those of the human heart, indicating that both types of
hearts have comparable contractional and relaxational operations. Therefore, parameter
change patterns caused by the damages and recoveries of the zebrafish hearts may be
56

similar to those of human hearts. Based on this assumption, the Doppler parameters used
to diagnose human hearts were used to evaluate the functional recovery of the amputated
zebrafish heart. These parameters were measured in zebrafish hearts for 32 dpa. The
relevance of comparisons between the data before and after the amputation was evaluated
by the two-sided paired t-test, with the level of significance set at the p-value ≤ 0.05.

5.4 Results
5.4.1 Phantom Study Results
Figure 5.4(a-d) shows Doppler flow waveforms of dual mode PWD acquired from
the flow phantom with the pre-set flow velocity of 3, 5, 10, and 15 cm/s. The yellow-
solid lines on the boundary of each Doppler flow image indicate the maximum velocity at
each moment. The averaged velocities of each setting over 3 seconds are  2.9 ± 0.37, 
4.9 ± 0.47,  9.9 ± 0.72, and  14.9 ± 0.77 cm/s, respectively. Note that the negative
velocity indicates that the direction of the flow is away from the transducer. The
maximum detectable velocity is 25.5 cm/s calculated with the PRF of 9.5 kHz and the
Doppler angle of 61.4°.

57

Figure 5.4 Doppler flow waveforms of the dual mode PWD acquired from the flow
phantom with the pre-set flow velocities of (a) 3 cm/s, (b) 5 cm/s, (c) 10 cm/s and (d) 15
cm/s. The measured mean peak velocities are (a) 2.9 ± 0.37 cm/s, (b) 4.9 ± 0.47 cm/s, (c)
9.9 ± 0.72 cm/s and (d) 14.9 ± 0.77 cm/s. The yellow-solid lines indicate the maximum
velocity at each moment.

Figure 5.5 shows the flow signals containing aliasing artifacts and compares
Doppler waveforms acquired with the single mode PWD and the dual mode PWD in
Figure 5.5(a) and 5.5(b), respectively. The signal, sharply decreasing to less than  25.5
cm/s, is aliased over the positive signal region for the single mode PWD as shown in
Figure 5.5(a), whereas the aliased signal in the dual mode PWD causes saturation over
the whole velocity range as shown in Figure 5.5(b). The saturation artifacts are caused by
(a) (b)
(c) (d)
58

the reconstruction of the missing Doppler flow vector with the aliased signals. Figure
5.5(c)-(d) shows raw echo signals in the range of non-aliased and aliased region, shown
in blue-dotted and red-dashed boxes in Figure 5.5(a), respectively. In Figure 5.5(c)-(d),
black-solid lines represent the echo signals acquired with the single mode PWD, and
blue-dotted and red-dashed lines indicate the interpolated signals reconstructed by
averaging the neighboring echo signals. When the signals are aliased, the neighbored
vectors are decorrelated, and the original signals shown in block solid lines are not
recovered with the linear interpolation method. Note that the zero lag cross-correlation
coefficients between the original and the reconstructed echo signal, which represents the
similarity of two signals, are 0.963 in the non-aliased region and 0.6804 in the aliased
region.
59

Figure 5.5 Doppler flow waveforms with aliasing artifacts. Doppler waveform generated
by (a) single mode PWD and (b) dual mode PWD. Raw echo signals in the range of (c)
non-aliased and (d) aliased region, which are represented as a blue-dotted and red-dashed
box, respectively. Black-solid lines represent the raw echo signals acquired by the single
mode PWD. Red-dashed and blue-dotted lines represent the reconstructed signals of the
aliased and the non-aliased calculated by interpolating the neighboring vectors.

Figure 5.6(a)-(b) shows Doppler flow and TD waveforms of the dual mode PWD
acquired from the moving wire targets at a speed of 1 mm/s, respectively. Figure 5.6(c)-
(d) shows the intensity profiles as a function of velocity of the Doppler flow and TD
signals, respectively. The center velocities of both Doppler methods are measured at 1
mm/s, equal to the speed of the wire target movement. Note that the velocity range of the
(a) (b)
(c) (d)
60

wire target movement in Doppler flow is broader than the TD signal, because the same
number of Doppler sample is used for both methods, whereas the resolution, pixels per
unite velocity, of the Doppler flow is reduced by 10 times in comparison to the TD.

Figure 5.6 Doppler waveforms acquired from the moving wire phantom using the dual
mode PWD: (a) Doppler flow image, (b) tissue Doppler image. Doppler intensity profiles
as a function of velocities of (c) Doppler flow and (d) tissue Doppler signals. Note that
red-dotted and black-solid lines in (c) and (d) indicate the velocity profile of wires
moving toward and away the transducer, respectively.

(a) (b)
(c) (d)
61

5.4.2 Zebrafish Heart Results
Figure 5.7(a) is the B-mode image of an adult zebrafish in the sagittal plane
visualizing the whole heart, from which the structures of the heart can be identified.
Under the guidance of B-mode imaging, the Doppler gates of the dual mode PWD are
placed at the entrance of bulbus arteriosus and at the atrioventricular valve as marked
with the red dots for detecting flow and tissue signals, respectively. Figure 5.7(b) shows
dual mode PWD signals acquired from an adult zebrafish heart showing both blood flows
and tissue movements. The peak velocity of A-flow which is greater than the maximum
detectable range causes the aliasing artifact, similar to the result demonstrated in the
phantom study. In the presence of A-flow aliasing, the peak is estimated by drawing the
lines along the outer boundaries on either side of A-flow Doppler signal and
extrapolating (Anderson, 2007). The shape of TD pattern is also similar to that of the
human heart except for the reversed velocity level of Em and Am, also evidenced in the
Doppler flow pattern. The measured MPI, E, A, Em, E/A and E/Em values for five
normal zebrafish are 1.07 ± 0.10, 1.87 ± 0.69 cm/s, 15.21 ± 2.94 cm/s, 2.4 ± 0.77 mm/s,
0.12 ± 0.04 and 8.8 ± 3.6, respectively, whereas the values for humans are 0.42 ± 0.09, 69
± 12 cm/s, 51 ± 11 cm/s, 10 ± 3 cm/s, 1.40 ± 0.36 and 5.61 ± 1.38, respectively
(Anderson, 2007). The notable differences in zebrafish parameters compared with those
of humans are E/A, which is lower than 1 and MPI, which is higher than 0.5. The
increased MPI, caused by the prolongation of IVRT, and reduced E/A are expressed in
patients with impaired relaxation of diastolic dysfunction caused by lowered left
ventricular compliance. Based on the observation from this study, the compliance of
62

zebrafish heart ventricle may be lower than that of human hearts, but further
investigations are required.

Figure 5.7 B-mode image and Doppler waveforms acquired with the dual mode PWD
from a wild-type zebrafish before the heart amputation: (a) B-mode image of zebrafish in
sagittal plane, (b) Doppler flow and tissue Doppler waveforms and (c) the magnified
Doppler signals. The scales of the velocity are cm/s and mm/s for the Doppler flow and
the TD signals, respectively. Red dots in (a) indicate the location of Doppler gates of the
dual mode PWD. A-flow, E-flow and outflow in Doppler flow and the respective pairs of
Am, Em and Sm in TD are identified at the same moments and indicated by red-dotted
lines. The time duration between the red-dashed lines of ′5′ and ′1′ represents for
IVRT, ′3′ and ′4′ for IVCT, and ′4′ and ′5′ is for ET.

(a)
(c)
(b)
63

Using the dual mode Doppler waveforms acquired from five zebrafish, the
parameters for diagnosing diastolic dysfunction are measured. The values measured on
the day before amputation, 3, 7, 14, 21 and 32 dpa are indicated by diamond markers in
the plots shown in Figure 5.8 and Figure 5.9, where error bars represent standard
deviations. In Figure 5.8, MPI, IVRT and IVCT are plotted. The MPI before amputation
is 1.07 and decreases to 0.92 at 3 dpa which is significantly different (p-value =
0.01<0.05) from the original value, whereas the MPI returns to the value before
amputation by 14 dpa (p-value = 0.66>0.05). In addition, IVRT decreases from 0.10 to
0.085 at 3 dpa (p-value = 0.01<0.05) and returned to 0.10 at 14 dpa (p-value = 0.6>0.05),
whereas IVCT does not show significant changes caused by the amputation (p-value =
0.26>0.05) on the day of or thereafter.
64

Figure 5.8 Amputation injury induced changes in parameter of (a) MPI, (b) IVRT and (c)
IVCT measured in the longitudinal study. (a) MPI decreased at 3 dpa in comparison with
MPI at 0 dpa (p = 0.01<0.05). (b) IVRT also decreased from 0.10 to 0.085 at 3 dpa (p =
0.01<0.05) and then returns to 0.10 at 14 dpa. (c) IVCT does not change significantly.

Figure 5.9 shows the parameters related to the tissue and blood flow dynamics.
The average value of Em is significantly decreased from 2.4 to 1.6 mm/s (p-value =
0.03<0.05) and recovers at 7 dpa (p-value = 0.33>0.05). The mean value of A decreases
from 15.21 to 13.2 cm/s (p-value = 0.03<0.05) and recovers at 7 dpa (p-value =
0.85>0.05). The mean value of E increases from 1.87 to 3.28 cm/s (p-value = 0.06>0.05)
and returns almost to the original value at 7 dpa (p-value = 0.56>0.05). As a result, both
E/A (p-value=0.04<0.05) and E/Em (p-value = 0.04<0.05) increase at 3 dpa and recover
to the pre-amputation values by 14 dpa (p-value = 0.53>0.05) and 7 dpa (p-value =
0.58>0.05), respectively.
(a) (b)
(c)
65

Figure 5.9 Amputation injury induced changes in parameters related to flow and tissue
velocities: (a) Em, (b) A, (c) E, (d) E/A, (e) E/Em measured in the longitudinal study.
Both E/A and E/Em increased at 3 dpa and recover to the value before amputation at 21
and 32 dpa, respectively.

5.5 Discussion
Conventional Doppler technique using focused ultrasound beams use a single gate
for detecting flow or tissue movement velocities independently. It is impossible to
measure both tissue Doppler and Doppler flow signals of a diseased heart in the same
cardiac cycle using this method. In this study, it is demonstrated that the dual mode
Doppler technique is capable of overcoming such a limitation. A-flow and E-flow
waveforms in zebrafish hearts can be better identified with the dual mode Doppler under
(a) (b)
(c) (d)
(e)
66

the guidance of TD than with the single gate PWD because of the synchronized flow and
tissue Doppler signals. For example, the E-flow within the last heart beat in Figure 5.7(b)
may be confused with the another peak in the white circle followed by the end of VOT
ejection due to their similarity of shapes and short separation with A-flow. However, TD
shows Em placed in between IVRT and Am can help discriminate E-flow from others.
Based on the comparison with the human Doppler flow signal, the peak after VOT
ejection may be caused by the VOT valve closure; however, further investigations are
needed to ascertain this hypothesis.
The performance of dual mode PWD was evaluated by phantom studies. It was
shown that the dual mode PWD could measure the flow velocity as precise as single
mode PWD. In the phantom study shown in Figure 5.4, it was found that the velocity
ranging from 3 to 15 cm/s could be measured in Doppler flow mode and that the
measured values were close to the pre-set flow speed (p-value = 0.974, t-test, double-
sided) of the phantom. In Figure 5.6, Doppler flow and tissue Doppler measurements
from a moving wire target obtained the same results as the pre-set velocity of 1 mm/s in
the phantom. However, the aliased signal in Figure 5.5(b) could not be recovered by
interpolations with neighboring vectors within red-dashed line box due to the
decorrelation between the vectors shown in Figure 5.5(d). To mitigate this problem, the
PRF should be increased to avoid saturation caused by aliasing in dual mode PWD. PRF
used in this study is limited to 9.5 kHz, which is the maximum PRF of the custom-
designed ultrasound imaging system. In the aliased flow signal, caused by squeezing the
67

tube for simulating A-flow, the peak velocity can be estimated by extrapolating the trace
shown with the red solid lines in Figure 5.5(b).
In the longitudinal study on zebrafish heart with the dual mode PWD, the
functional recovery of the amputated heart is investigated. In Figure 5.8(a), MPI
indicating both diastolic and systolic performance sharply decreases at 3 dpa. The
decrease of MPI is caused by the shortened IVRT, without significant changes in IVCT
shown in Figure 5.8(b) and 5.8(c). This indicates that the ventricular pressure equalizes to
the atrium pressure earlier than the normal heart during the early diastolic phase. In
addition, the decrease of Em in Figure 5.9(a) indicates the prolongation of ventricular
relaxation time, which is interpreted as the increase of stiffness, resulting in slow
decrease in ventricular pressure and sharp increase in atrium pressure. Note that the
increase of E/Em at 3 dpa, shown in Figure 5.9(e), indicates that the ventricular filling
pressure is increased. Due to the increased pressure gradient between the heart chambers,
the increase of E and the decrease of A result in the increase of the E/A ratio shown in
Figure 5.9(d). Although the increase of E is not statistically significant, the p-value of the
paired difference test at 3 dpa approaches the significance level (0.05). Therefore,
replicating this experiment with a larger sample size may minimize the measurement
errors and subsequently reduce the p-value to achieve statistical significance. These
parametric changes in the amputated zebrafish hearts are similar to patterns exhibited in
human hearts suffering from diastolic dysfunction of restrictive filling caused by
significant reduction in ventricular compliance. All parametric changes indicating
dysfunction are recovered to approximately 80–90% within one week, and the diastolic
68

function returns to normal condition after two to three weeks, although previous
morphology study indicates that the full recoveries of scars take longer (Poss et al., 2002).
The standard deviation of peak velocity of A-flow in Figure 5.9(b), acquired by
extrapolation, is relatively larger than the other parameters, whereas f-test (p-value > 0.4)
indicates that the standard deviations of other values over all dpa are fairly uniform.
Therefore, the errors from extrapolation may be the cause of the larger standard deviation
in A-flow compared with those of other parameters that are directly measured.

5.6 Conclusion
High-frequency dual mode PWD imaging is implemented to acquire flow and
tissue Doppler signals from different positions. The two types of Doppler signals
acquired from zebrafish hearts were synchronized in time domain and given in the same
heart cycle. In the longitudinal study of functional regenerations of zebrafish hearts, both
flow and tissue Doppler signals were employed to diagnose the diastolic dysfunction of
restrictive filling non-invasively. Parametric changes assessed by the dual mode PWD
were observed to be in agreement with previous studies using invasive methods,
indicating that the functional recovery was mostly accomplished within one week,
whereas full recovery from the diastolic dysfunction was exhibited between two to four
weeks post-amputation.
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CHAPTER 6 High-Frequency Color Doppler Imaging using
Array-Based Ultrasound Imaging System
6.1 Introduction
Color Doppler imaging is one of the ultrasound imaging techniques that combines
anatomical information obtained by B-mode imaging with velocity information derived
using Doppler techniques to generate color-coded images. Color-coded velocity
information is superimposed on gray-scale images of anatomy. B-mode imaging utilizing
ultrasound pulse-echo technique generates anatomical cross-sectional images as show in
Figure 6.1(a). In color Doppler imaging, the color-coded velocity information depicting
blood flow is superimposed on the B-mode image as shown in Figure 6.1(b). Figure 6.1(a)
and 6.1(b) shows the B-mode and color Doppler images of the fetal abdomen,
respectively.
Color Doppler imaging technique makes use of the phase shift or time delays
between returning echoes from the same sample volume during subsequent pulses, while
pulsed-wave spectral Doppler technique utilizes the Doppler shift of the returning echo
on each transmitted pulse. Pulsed-wave spectral Doppler mentioned in chapter 4 and 5
allows velocity estimation from a single sample volume within the B-mode image,
whereas color Doppler allows velocity estimation from a multiple sample volume as
shown in Figure 6.2(a) and 6.2(b), respectively.

70

Figure 6.1 (a) B-mode image of the fetal abdomen. B-mode image shows the structural
information. (b) Color Doppler image obtained by superimposing Doppler information on
the B-mode image. Velocity information is represented as colors (courtesy of Samsung
Medison).

Figure 6.2 (a) Pulsed-wave spectral Doppler and (b) color Doppler imaging from the
hepatic vein (courtesy of Samsung Medison).
(a) (b)
(a) (b)
71

Color Doppler imaging allows velocities to be imaged over a region of interest,
allowing the rapid identification of the presence and direction of flow. Therefore, color
Doppler imaging is used to identify specific areas from which spectral Doppler
measurements can be made as shown in Figure 6.3.

Figure 6.3 Ultrasound image of common carotid artery combined B-mode, color Doppler
mode and pulsed-wave Doppler mode (courtesy of Samsung Medison).

In this chapter, we present the implementation of color Doppler imaging for high-
frequency ultrasound array-based system utilizing 30 MHz linear array transducer. An
overview of color Doppler signal processing and implementation results will be provided.

72

6.2 Methods
6.2.1 Functional Block Diagram of Color Doppler Signal Processing
Figure 6.4 illustrates the functional block diagram of color Doppler signal
processing. Post-beamformed data are quadrature-demodulated to generate the in-phase (I)
and quadrature (Q) components of the Doppler signal, and clutter filters are applied to
suppress signals from stationary or slow moving objects such as tissue or tissue motion.
Velocity estimator based on autocorrelation method is utilized to estimate velocity from
the filtered signals, and color Doppler images are obtained using an appropriate color-
mapping table. Finally, the color Doppler images are superimposed onto the B-mode
images. The details of each functional block are described in this chapter.

Figure 6.4 Functional block diagram of color Doppler signal processing (I, in-phase
components of echo signal; Q, quadrature components of echo signal).

6.2.2 Data Acquisition
Figure 6.5(a) illustrates the ultrasound beam sequences for color Doppler imaging.
At each position, an ensemble of N
F
traces is acquired by transmitting N
F
pulses and
73

receiving the corresponding echoes at the rate of PRF. N
F
is often referred as ensemble
length, number of Doppler pulses per scanline. Increase in ensemble length allows higher
sensitivity to lower velocities but also decrease the frame rate. Typically, 8 or 16 of
ensemble length are utilized to achieve adequate frame rates in color Doppler imaging.
The resulting 3-D data matrix for color Doppler imaging is illustrated in Figure 6.5(b).
The matrix can be viewed as an N
L
 N
R
 N
F
where N
L
is the number of scanlines, N
R
is
the number of range samples in a scanline, and N
F
is the number of firing required for
flow estimation (i.e., the ensemble length).

Figure 6.5 (a) Ultrasound beam sequences for color Doppler imaging. (b) The 3-D data
matrix for color Doppler signal processing. (N
L
, the number of scanlines; N
R
, is the
number of range samples in a scanline; N
F
, the number of firing required for flow
estimation)

(a) (b)
74

6.2.3 Quadrature Demodulation
Quadrature demodulation technique generates the baseband in-phase (I) and
quadrature (Q) components of received echo signals by mixing with sine and cosine
waveforms and carrying out low pass filtering as shown in Figure 6.6 (Aydin et al., 1994;
Song and Park, 1990).

Figure 6.6 The block diagram of the quadrature demodulation.

The generated complex baseband components can be expressed as:
          cos cos
2
o s s n
LPF
K
I n r n n T A nT       

(6.1)
          sin sin
2
o s s n
LPF
K
Q n r n n T A nT       

(6.2)
where K is the gain of LPF.
The post-beamformed echo signal is quadrature-demodulated to generate the in-
phase (I) and quadrature (Q) components for further color Doppler signal processing.
75

6.2.4 Clutter Filtering
One of the most challenging aspects of color Doppler imaging is the rejection of
echoes from stationary or nearly stationary tissue, which can be much larger than those
from the blood. As shown in Figure 6.7, these low-frequency tissue signals are generally
much stronger than the high-frequency signals from fast-moving blood. The clutter filter
is a high-pass filter applied to the N
F
samples for every image point.

Figure 6.7 Illustration of clutter filtering.

For clutter signal rejection, a variety of algorithms, including the single echo
canceller, finite impulse response (FIR) filters, infinite impulse response (IIR) filters, and
regression filters, can be utilized (Tysoe and Evans, 1995). Depending on the different
clutter rejection requirements, different filters must be selected based on their
performances which are mainly due to frequency responses.
The simplest type of clutter rejection filter is the single echo canceller which is
implemented by subtracting two successive echo signals. Therefore, any echo from a
76

stationary target is cancelled, while echoes from moving targets are preserved. However,
this simple technique is not adequate in color Doppler imaging application because of its
poor roll-off characteristics and wide transition band.
More complex finite impulse response (FIR) filters can be used to provide narrow
transition band and a more uniform pass-band in the filter’s steady-state frequency
response. However, in order to achieve the sharp transition band, the high-order FIR filter
is needed which requires a large number of data samples. The frequency characteristics of
infinite impulse response (IIR) filters are considerably better than those of FIR filters.
However, IIR filters have long transient responses, which mean that unless appropriate
steps are taken to initialize them suitably, a large number of output values needed to be
discarded before the data becomes valid.

6.2.5 Velocity Estimation
There are two most commonly used algorithms to estimate flow velocities,
autocorrelation in phase domain and cross-correlation in time domain. The
autocorrelation method, a phase-domain algorithm, utilizes the in-phase (I) and
quadrature (Q) components to estimate the rate of phase changes of the received echo
signals, whereas the cross-correlation method, a time-domain algorithm, uses the echo
signals to estimate the changes in the round-trip time from the transducer to a group of
scatterers. The most widely used is the autocorrelation technique introduced by
77

Namekawa et al. (Namekawa et al., 1983). The phase-domain autocorrelation-based
velocity estimation will be utilized to estimate velocity in this chapter.
The expression for frequency estimation using this technique can be derived using
simple geometrical considerations that provide an intuitive understanding of its operation.
Figure 6.8 illustrates the position of a rotating signal vector during two adjacent samples
i-1 and i, with in-phase components I(i-1) and I(i), and quadrature components Q(i-1) and
Q(i).

Figure 6.8 Position of a rotating signal vector during two successive samples i-1 and i,
showing the in-phase components I(i-1) and I(i) and quadrature components Q(i-1) and
Q(i).

78

The angular frequency ω of the rotating vector is defined as:

    1
prf
ii
d
dt T




 (6.3)
where  is the phase shift relative to the system clock at time t, and
prf
T is the time
between two successive image lines (i.e., PRF). The tangent of the phase difference
    1 ii   may be written in terms of the ratio of the sine and cosine of the phase
difference according to

     
     
     
       
       
sin 1
tan 1
cos 1
sin cos 1 cos sin 1
cos cos 1 sin sin 1
ii
ii
ii
i i i i
i i i i



   
   

  

  

  
(6.4)
Since the sine and cosine terms are now expressed as the in-phase (I) and
quadrature (Q) magnitudes of the vectors, equation (6.4) can be derived as:
     
       
       
11
tan 1
11
Q i I i I i Q i
ii
I i I i Q i Q i

  
  
  
(6.5)
and an average frequency calculated by summing over a number of adjacent pulse pairs,
then the mean angular frequency can be written as:

       
       
1
1
11
1
arctan
11
N
i
N
prf
i
Q i I i I i Q i
T
I i I i Q i Q i




  
 
   



(6.6)
Finally, the estimated flow velocity v is:
79

       
       
1
00
1
11
2
arctan
2 cos 2 2 cos
11
N
prf
i
N
i
c
Q i I i I i Q i f
c
v
ff
I i I i Q i Q i


  



  
 
   



(6.7)
where c is the sound velocity in a medium, f
0
is the center frequency of the transducer, θ
is the Doppler angle between the ultrasound beam and flow, and f
prf
is the PRF.
The Doppler power is estimated using the following equation (Loupas et al.,
1995):
       
22 1
0
D
N
i
P I i Q i







(6.8)

6.2.6 Color Mapping
In the image-mapping block, a color Doppler image is combined with a B-mode
image. When a pixel is determined to be a valid color Doppler pixel, it replaces the B-
mode image pixel. After the velocity estimation, an appropriate color table should be
selected to indicate the flow velocities and directions. The velocity and directions are
mapped to color encoding scheme that uses colors of red, yellow to white to describe
increasing velocity toward to the transducer and blue to cyan to describe increasing
velocity away from the transducer. Color Doppler images can be obtained using the
selected color table and superimposed onto the B-mode imaging to show both flow and
anatomical information in one image. Different user-defined color tables can be used to
encode the velocities with blue shades typically indicating negative flow velocities (i.e.
moving away from the transducer) and red shades indicating positive flow velocities (i.e.
80

moving towards the transducer). The intensities of the reds or blues indicate the
magnitudes of velocities as shown in Figure 6.9.

Figure 6.9 Color map for color Doppler imaging.

6.3 Experimental Arrangement
6.3.1 Flow Phantom Study
For the evaluation of the implemented color Doppler imaging, studies on flow
phantom were performed. The flow phantom having a polyimide tube with an inner
diameter of 1.2 mm was fabricated. The blood-mimicking fluid prepared by mixing
silicon dioxide particles in DI water was injected into the tube, and the flow direction was
controlled by a syringe pump (NE-1000 Multi-Phaser, New Era Pump System Inc., NY).
Under the guidance of B-mode imaging, the range gate of the color Doppler was placed
on the tube as illustrated in Figure 6.10. B-mode image was acquired first to superimpose
onto color Doppler images. The ensemble size and color Doppler scanline were set to be
81

8 and 50, respectively. The PRF for color Doppler imaging was set to be 9.5 kHz. Two
directional flows with constant velocity were generated using the syringe pump.

Figure 6.10 Flow phantom for color Doppler imaging.

6.3.2 Adult Zebrafish Heart Study
All adult zebrafish experiments were performed in accordance with protocols
approved by the Institutional Animal Care and Use Committee at the University of
Southern California. The zebrafish was anaesthetized for 30 s by submerging it in 0.08%
tricaine solution (MS-222, Sigma-Aldrich, MO) followed by removing scales around the
zebrafish heart. The fish was then put into a chasm on one side of a soft sponge to fix its
position of ventral side facing upwards as shown in Figure 6.11(a). The chamber was
filled with 0.04% tricaine solution to perform ultrasound imaging under anesthesia. Using
B-mode imaging to display the fish’s sagittal plane of the heart which shows the largest
cross section, the fish was repositioned to place the color Doppler range gate on the heart
for detecting blood flow between heart chambers as shown in Figure 6.11(b). After the
82

range gate was located, the 50 frames of B-mode images were acquired first and then
color Doppler data were acquired. The ensemble size and color Doppler scanline were set
to be 8 and 50, respectively. The PRF for color Doppler imaging was set to be 9.5 kHz.

Figure 6.11 (a) Experiment setup of color Doppler imaging for zebrafish heart. (b) Color
Doppler window was positioned on the zebrafish heart for monitoring the blood flows
between heart chambers.

6.4 Results
6.4.1 Flow Phantom Results
Figure 6.12 shows color Doppler imaging results from the flow phantom with the
constant flow velocity with different flow directions. Flow away from the array is shown
in shades of blue as shown in Figure 6.12(a), and flow towards the array is shown in
shades of red as shown in Figure 6.12(b).
(a) (b)
83

Figure 6.12 Color Doppler imaging results from the flow phantom. (a) Flow away from
the array is shown in shades of blue and (b) flow towards the array is shown in shades of
red.

6.4.2 Zebrafish Heart Results
Figure 6.13 shows color Doppler imaging results from the adult zebrafish heart.
Figure 6.13(a) shows the blood flow from the atrium to the ventricle in the phase of
atrium contraction (bottom to top) represented as shades of red. Figure 6.13(b) shows the
blood flow from the ventricle to the bulbus arteriosus in the phase of ventricle contraction
(top to bottom) represented as shades of blue.
(a) (b)
84

Figure 6.13 Color Doppler imaging results from adult zebrafish heart. (a) Blood flow
from the atrium to the ventricle in the phase of atrium contraction (bottom to top) is
shown in shades of red. (b) Blood flow from the ventricle to the bulbus arteriosus in the
phase of ventricle contraction (top to bottom) is shown in shades of blue.

6.5 Discussion
In this chapter, we present the implementation of high-frequency color Doppler
imaging using the array-based imaging system. The data acquisition scheme and the color
Doppler signal processing algorithms were described. The high-frequency color Doppler
imaging was evaluated by the flow phantom and adult zebrafish in vivo studies. In the
flow phantom study, constant velocity with opposite flow directions was detected
utilizing color Doppler imaging. Also, color Doppler imaging was utilized to monitor
(a) (b)
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blood flows inside adult zebrafish heart and flow directions were clearly identified by the
color-coded images.

86

CHAPTER 7 Summary and Future Works
7.1 Summary
This dissertation presents the investigation of high frequency array-based imaging
system and its potential biomedical applications.
The high frequency array-based imaging system can be paired with three different
types of array transducers (30 MHz 256-element linear, 20 MHz 192-element convex,
and 20 MHz 48-element phased). The system provides B-mode imaging, PW-Doppler,
color Doppler imaging and the capability of pre-beamformed RF data acquisition. Wire
phantom images showed that the -6 dB lateral and axial resolution was 118.4 µm and
73.2 µm for 30 MHz linear array, 165 µm and 75 µm for 20 MHz convex array, and 210
µm and 79.7 µm for 20 MHz phased array, respectively.
The high frequency array-based imaging system is also used for ophthalmic
imaging. 30 MHz linear array transducer was utilized for anterior segment imaging of the
excised bovine, porcine, and rabbit eyes and anatomical details, such as cornea, iris,
ciliary body and lens, were clearly visible. Also, both anterior and posterior segments of
the excised bovine eye were identified with 20 MHz convex array transducer which can
achieve a wider field of view and deeper penetration depth compared to the linear array
transducer. The anatomical details, such as cornea, iris, lens, and retina, choroid, and
sclera layers were clearly visible.
87

The high frequency PW Doppler and micro-ECG were integrated to assess the
ventricular diastolic function during heart regeneration of the adult zebrafish.
Synchronized PW Doppler with ECG signals confirmed the A-wave in response to atrial
contraction (P wave in ECG), E-wave in response to ventricular relaxation (T wave in
ECG), and ventricular outflow in response to ventricular contraction (QRS waves in
ECG). E-wave and E/A ratios increased at 3 dpi and subsequently recovered to the
baseline levels at 65 dpi. Unlike humans, the E/A ratio is less than 1 in zebrafish at
baseline, reflecting a higher active filling (A-wave) than passive filling (E-wave)
velocities during diastole in the two-chamber heart system.
High frequency dual mode pulsed-wave Doppler imaging, which provides both
tissue Doppler and Doppler flow in a same cardiac cycle, was implemented on the array-
based imaging system for monitoring the functional regeneration of adult zebrafish hearts.
In the in vivo study of zebrafish, both tissue Doppler and Doppler flow signals were
simultaneously obtained, and the synchronized valve motions with the blood flow were
identified. In the longitudinal study on the zebrafish heart regeneration, the parameters
for diagnosing the diastolic dysfunction were measured, and the type of diastolic
dysfunction caused by the amputation was found to be similar to the restrictive filling.
The diastolic function was fully recovered within four weeks post-amputation.
High frequency color Doppler imaging was implemented on the array-based
imaging system and evaluated by the flow phantom and adult zebrafish in vivo studies. In
the flow phantom study, constant velocity with opposite flow directions was detected
88

utilizing color Doppler imaging. Also, color Doppler imaging could be used to monitor
blood flows inside adult zebrafish heart and flow directions were clearly identified by the
color-coded images.

7.2 Future Works
7.2.1 Real-Time Color Doppler Imaging
High frequency color Doppler imaging would need more complex design of
clutter filter to reject the clutter signal. Adaptive clutter filtering method requires a large
amount of computation which makes it very hard to be implemented in real-time. A
possible way to lower the computation load is to utilize a graphical processing unit
(GPU). The parallel architecture and C language like development interface of the GPU
has enabled easy implementation of parallelism on the color Doppler imaging algorithm.

7.2.2 B-Flow Imaging
The high frequency array-based imaging system was designed in an open
architecture so that it can facilitate add-on implementation of more imaging methods for
researchers. Other than color Doppler imaging, B-flow is a new technique for imaging
blood flow and tissue simultaneously with high resolution, dynamic range and frame rate.
B-flow imaging uses wideband pulse to achieve high resolution. In low frequency
condition where the blood echoes are orders of magnitude weaker than that from
89

surrounding tissue, coded excitation and temporal high-pass filtering can be used to
reduce the tissue signal and enhance blood signal such that both could be displayed
simultaneously. The temporal filtering using difference of two transmit u
1
, and u
2
is given
by
     
2
12
2 0 1 B E u u R R     

(7.1)
where B is the image brightness, E denotes statistical expectation and R(τ) is the
correlation function. Since it uses small packet size which only contains two consecutive
B-mode frame, higher frame rate than color Doppler imaging can be achieved.
Furthermore, given the fact that in high-frequency condition blood signal will become
stronger, regular pulse other than coded excitation will be adequate to obtain blood echo.
Therefore, such a method does not require extra change in the hardware, and can be
implemented into the current system only by some minor modification on the firmware
and software.

90

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Abstract (if available)

Abstract High frequency ultrasound imaging, capable of achieving superior spatial resolution in real-time, has been shown to be useful for imaging and visualizing blood flow in ophthalmology, dermatology, and small animal research. The utilization of high frequency array-based imaging system can alleviate the limitations of the systems with single element transducers. This dissertation presents an investigation of high frequency array-based imaging system and its potential biomedical applications. The system is capable of B-mode imaging, PW-Doppler, color Doppler imaging, and RF data acquisition. Three different types of high frequency (30 MHz 256-element linear, 20 MHz 192-element convex, and 20 MHz 48-element phased) array transducers were implemented on the array-based imaging system. The system was also utilized for ophthalmic imaging: 30 MHz linear array for anterior segment and 20 MHz convex array for both anterior and posterior segments imaging of the eye. Anatomical structures, such as cornea, iris, ciliary body, lens, and retina, choroid, and sclera layers were identified. The high frequency PW Doppler and micro-ECG were integrated to assess the ventricular diastolic function during heart regeneration of the adult zebrafish. Synchronized PW Doppler with ECG signals confirmed the A-wave in response to atrial contraction (P wave in ECG), E-wave in response to ventricular relaxation (T wave in ECG), and ventricular outflow in response to ventricular contraction (QRS complex in ECG). The E/A ratio is less than 1 in zebrafish at baseline, reflecting a higher active filling (A-wave) than passive filling (E-wave) velocities in the two-chamber heart system. High frequency dual mode pulsed-wave Doppler imaging, which provides both tissue Doppler and Doppler flow in a same cardiac cycle, was implemented on the array-based imaging system for monitoring the functional regeneration of adult zebrafish hearts. In the in vivo study of zebrafish, both tissue Doppler and flow Doppler signals were simultaneously obtained and the synchronized valve motions with the blood flow were identified. In the longitudinal study on the zebrafish heart regeneration, the parameters for diagnosing the diastolic dysfunction were measured, and the type of diastolic dysfunction caused by the amputation was found to be similar to the restrictive filling. The diastolic function was fully recovered within four weeks post-amputation. High frequency color Doppler imaging was implemented on the array-based imaging system and evaluated by the flow phantom and adult zebrafish in vivo studies. In the flow phantom study, constant velocity with opposite flow directions was detected utilizing color Doppler imaging. Also, color Doppler imaging could be used to monitor blood flows inside adult zebrafish heart and flow directions were clearly identified by the color-coded images.

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Asset Metadata

Creator Kang, Bong Jin (author)

Core Title High-frequency ultrasound array-based imaging system for biomedical applications

School Viterbi School of Engineering

Degree Doctor of Philosophy

Degree Program Biomedical Engineering

Publication Date 04/28/2015

Defense Date 03/10/2015

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

Tag high-frequency ultrasound,high-frequency ultrasound array-based imaging system,high-frequency ultrasound color Doppler,high-frequency ultrasound pulsed-wave Doppler,OAI-PMH Harvest

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Shung, Kirk Koping (committee chair), Kuo, C. C. Jay (committee member), Yen, Jesse T. (committee member)

Creator Email bongjink.usc@gmail.com,bongjink@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-562902

Unique identifier UC11302124

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Legacy Identifier etd-KangBongJi-3416.pdf

Dmrecord 562902

Document Type Dissertation

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Rights Kang, Bong Jin

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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

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