University of Southern California Dissertations and Theses

Assessment of 3D surface changes following virtual bracket removal

(USC Thesis Other)

Assessment of 3D surface changes following virtual bracket removal

PDF

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content

Assessment of 3D surface changes
following virtual bracket removal
by Alexandra Chamberlain-Umanoff, DDS

A thesis presented to the faculty of the Graduate School of the
University of Southern California in partial fulfillment of the
requirements for the degree Master of Science in Craniofacial Biology

Los Angeles, May 2019

Assessment of 3D surface changes following virtual bracket removal | 2

Acknowledgements
I would like to thank Dr. Andre Weisheimer for his dedication to teaching. His knowledge,
guidance, and mentorship were fundamental to the success of this project.

I would also like to thank Dr. Kaifeng Yin for performing statistical analysis for this study.

Additionally, I offer special thanks to INBRACE, 3M Unitek, and SprintRay for their
contributions to this project.

Finally, I thank my family and friends for their unwavering support and encouragement
throughout this process.

Assessment of 3D surface changes following virtual bracket removal | 3

TABLE OF
CONTENTS

1. Abstract 4
2. Introduction 5
3. Material and Methods 9
a. Sample 9
b. Protocols 13
c. Measurements 22
d. Statistical Analysis 25
4. Results 26
5. Discussion 38
6. Conclusion 44
7. References 46
8. Appendix 51

Assessment of 3D surface changes following virtual bracket removal | 4

1. ABSTRACT
Introduction: Computer-aided design and manufacturing of orthodontic retainers from
digitally debonded models can be used to facilitate same-day delivery. The purpose of this study
was to 1) establish reliable virtual bracket removal (VBR) techniques using two 3D modeling
software programs and 2) assess their accuracy and reproducibility.
Methods: The sample consisted of nine 3D-printed maxillary models that were digitized with
an intraoral scanner for use as a control group. The control models were bonded with labial
brackets and scanned. VBR was performed using Ortho Analyzer™ (3Shape A/S, Copenhagen,
Denmark) and Meshmixer™ (Autodesk, San Rafael, CA). The virtually debonded models were
superimposed onto the control models, and 3D Euclidean distances between surface points of the
superimposed models were calculated for comparative analysis of surface changes due to VBR.
Linear surface changes were expressed via color mapping.
Results: Intra- and inter-operator reliability were determined to be high (> 0.9). The accuracy
of VBR did not differ significantly between software programs. However, statistically significant
differences (P < 0.05) were detected between three tooth segments (incisors, canines/premolars,
and first molars), with VBR in the posterior segments showing the least accuracy.
Conclusions: VBR is accurate and reproducible when using the protocols established in this
study. Moreover, VBR using Ortho Analyzer™ and Meshmixer™ is comparable and facilitates
computer-aided design and manufacture of retainers.
Assessment of 3D surface changes following virtual bracket removal | 5

2. INTRODUCTION
Recent developments in three-dimensional (3D) imaging technologies have dramatically
changed the field of orthodontics. Digital advancements in 3D imaging have increased diagnostic
accuracy (Vaid, 2018) and paved the way for customized treatment (Jheon et al., 2017). Among
other advantages over conventional records, digital records can be captured readily, stored
indefinitely, and shared electronically (Vasudavan et al., 2010). Accordingly, digital records
have numerous applications in orthodontics, ranging from virtual diagnosis and treatment
planning to computer-aided design and manufacture (CAD/CAM) of appliances.

As digital imaging capabilities have become more sophisticated, innovations in software to
process, manage, and analyze 3D imaging (Grauer et al., 2009) have made it possible to assess
the accuracy of digital records. For example, image registration—which is the process of
overlaying and integrating two or more 3D images (Brown, 1992; Lin et al., 2013; Zitová and
Flusser, 2003)—has been used extensively in the literature to assess the accuracy of 3D imaging
(Claus et al., 2018; Ender et al., 2016; Ender and Mehl, 2013a; Flügge et al., 2013). Moreover,
studies have compared image registration techniques used to analyze 3D imaging and concluded
that surface-based registration using an iterative closest point (ICP) algorithm (Besl and McKay,
1992) is more reliable than landmark-based registration because surface-based registration is
based on thousands of surface points rather than on a few manually selected landmarks
Assessment of 3D surface changes following virtual bracket removal | 6

(Ghoneima et al., 2017; Gkantidis et al., 2015; Grauer et al., 2009). For that reason, many
investigators opt for surface-based techniques when assessing the accuracy of digital records.

Given the growing acceptance of digital records, particularly of digitally scanned occlusal
records, there has been much interest in comparing the accuracy of digital models with that of
conventional dental models. Although stereolithographic (STL) models do not contain any
volumetric data, their triangulated surface data can be used for superimposition (Gkantidis et al.,
2015). Indeed, surface-based registration using an ICP algorithm has been shown to be a reliable
method for superimposing 3D surface data of digital models (Brown, 1992; Ghoneima et al.,
2017; Lin et al., 2013). Comparative analysis of linear distance measurements between the
superimposed surfaces can therefore be used to assess accuracy (Ender and Mehl, 2013a).

Using this method, studies have shown that the accuracy of digital models is clinically
acceptable (Flügge et al., 2013; Sousa et al., 2012; Wiranto et al., 2013), though they are less
accurate than conventional dental models (Ender and Mehl, 2013a). Nonetheless, diagnosis and
treatment planning decisions are comparable regardless of whether conventional or digital
models are analyzed (Wiranto et al., 2013). Moreover, model digitization can overcome some of
the limitations of conventional dental models, including dimensional deformation of impression
materials (Mack et al., 2017), as well as alleviate storage problems associated with conventional
models.

Considering the advantages of digital records, many clinicians prefer digital models over
conventional models. There are several methods available to acquire digital models: 1) laser
Assessment of 3D surface changes following virtual bracket removal | 7

surface scanning of impressions or dental models; 2) CBCT scans or CBCT scanning of
impressions or dental models; 3) or direct intraoral scanning of the dentition (Hazeveld et al.,
2014; Wiranto et al., 2013). Although extraoral scanning techniques show higher precision than
direct intraoral scanning (Flügge et al., 2013), studies have shown that directly-acquired digital
models are clinically acceptable and reproducible when compared with conventional dental
models (Flügge et al., 2013; Sousa et al., 2012; Wiranto et al., 2013). Moreover, intraoral
scanning is less susceptible to errors than conventional impression techniques in patients with
fixed labial appliances (Claus et al., 2018) irrespective of bracket characteristics (Jung et al.,
2016). Thus, the accuracy of digital models derived from intraoral scanners is sufficient for
orthodontic applications before, during, and after treatment.

The reliability of commercially available intraoral scanners, together with recent advancements
in 3D printing and CAD/CAM software, has made it possible to fabricate orthodontic appliances
from 3D-printed models. This approach is typical of commercially manufactured aligners such as
Invisalign
®
and ClearCorrect, which are fabricated from a series of reconstructed printed models.
Likewise, retainers can be fabricated from 3D-printed models. Indeed, studies have demonstrated
comparable clinical acceptability and stability between retainers fabricated from printed models
and those fabricated from conventional dental models (Tahir et al., 2018; Vasudavan et al.,
2010). Moreover, retainers fabricated from digital models were preferred by clinicians
significantly more often than those fabricated from conventional models (Vasudavan et al.,
2010).

Assessment of 3D surface changes following virtual bracket removal | 8

Retainer delivery immediately following fixed appliance removal is feasible because CAD/CAM
software can be used to virtually remove brackets (Groth et al., 2018; Kravitz, 2010; Nelson,
2015). Given that digital models provide a reliable surface area for appliance fabrication (Mack
et al., 2017), it has been suggested that fabrication is more accurate and consistent, yet less labor-
intensive (Sassani et al., 1995; Vasudavan et al., 2010). However, the accuracy of fabricated
retainers would be limited by any inaccuracies in the digital model caused by virtual bracket
removal (VBR). Since precision of fit is essential for retainers (Rudolph et al., 2007),
quantitative and qualitative 3D analysis of VBR techniques is necessary. Thus, the objectives of
this study are to 1) establish reliable VBR techniques using two 3D modeling software programs
and 2) assess their accuracy and reproducibility.

Assessment of 3D surface changes following virtual bracket removal | 9

3. MATERIAL AND
METHODS

a. Sample
The University Park Institutional Review Board (UPIRB) determined that this study did not
qualify as Human Subjects Research and, therefore, did not require approval by UPIRB.

This two-part study was conducted at the University of Southern California in association with
INBRACE. Part I established reliable techniques for VBR using two 3D modeling software
programs: Ortho Analyzer™ (3Shape A/S, Copenhagen, Denmark) and Meshmixer™ (version
3.5.474; Autodesk, San Rafael, CA). Part II of this study assessed the accuracy and
reproducibility of VBR using the techniques for Ortho Analyzer™ and Meshmixer™ established
in Part I.

The sample consisted of nine 3D digital records of maxillary dentitions acquired at the
completion of orthodontic treatment after all fixed appliances were removed. The inclusion
criteria were: 1) complete, permanent dentition; and 2) normal crown morphology. The sample
was printed (100 μm resolution) in gray photopolymer resin using MoonRay 3D Printer
(SprintRay, Los Angeles, CA) (Fig 1). The nine printed models were scanned using TRIOS
®

Assessment of 3D surface changes following virtual bracket removal | 10

Intraoral Scanner (3Shape A/S, Copenhagen, Denmark) (Fig 2) for conversion to STL format
(labeled control models), which is an open source, surface-based extension that can be used with
most commercial and freeware software applications (Gkantidis et al., 2015).

Although several commercially available intraoral scanners generate reliable digital models (Anh
et al., 2016; Flügge et al., 2013; Gan et al., 2016; Lim et al., 2018; Sousa et al., 2012; Wiranto et
al., 2013), TRIOS
®
was preferred in this study because it is less likely to be influenced by
scanning technique (Anh et al., 2016; Ender and Mehl, 2013b) or the length of clinical career
(Lim et al., 2018). Moreover, TRIOS
®
has demonstrated reliable scanning accuracy of dentitions
with fixed labial appliances (Claus et al., 2018; Jung et al., 2016; Park et al., 2016), which was
critical for this study.
Fig 1. MoonRay 3D Printer and Resin
(SprintRay, Los Angeles, CA).
Images from:
https://sprintray.com/moonray-desktop-
3d-printer/
Fig 2. TRIOS
®
Intraoral Scanner
(3Shape A/S, Copenhagen,
Denmark).
Image from:
https://www.3shape.com/en/produ
cts/trios/intraoral-scanners
Assessment of 3D surface changes following virtual bracket removal | 11

The scanner was calibrated before use and all scanning was performed by a trained operator
according to the manufacturer’s instructions (3Shape, 2015b). 3D images acquired from steady
and continuous scanning were considered optimal. However, occasional voids occurred during
initial acquisition of 3D images and rescanning of these areas was necessary. Scans with large
voids or obvious mismatching of 3D images were discarded and new 3D images were acquired.
Automatic post-processing was performed after scanning for detail optimization, noise reduction,
and void repair (3Shape, 2015b).

The printed models were bonded from first molar to first molar with Victory Series™ Low
Profile 022 brackets with APC™ II adhesive precoat (3M Unitek, Monrovia, CA) (Fig 3) and
scanned using TRIOS
®
for conversion to STL format (labeled bonded models).

Fig 3. Illustration of Model 09 before and after bonding with Victory Series™ Low Profile 022
brackets with APC™ II adhesive precoat (3M Unitek, Monrovia, CA).
Images from: https://multimedia.3m.com/mws/media/636611O/3m-orthodontic-product-
catalog.pdf
Assessment of 3D surface changes following virtual bracket removal | 12

The ability to make meaningful conclusions about error due to VBR relied on scanning accuracy.
Therefore, surface-based superimposition of the control and bonded models using an iterative
closest point (ICP) algorithm (Besl and McKay, 1992) was performed to verify accuracy before
VBR (Fig 4). 3D Euclidean distances between surface points on the control and bonded models
were expressed via color mapping using 3-matic 3D Modeling Software (Materialise, Leuven,
Belgium) (Fig 5). Because the accuracy of TRIOS
®
for the maxillary arch is 80 ± 18 μm (Gan et
al., 2016), the threshold parameter for scanning accuracy was set at 100 μm.

Fig 4. Illustration of surface-based superimposition of a bonded
model and its corresponding control model using 3-matic.
Fig 5. Illustration of color mapping used to verify scanning accuracy
within 100 μm. Green hues, which indicated agreement between the
control and bonded model surfaces, were seen on all surfaces except
in the areas where brackets were bonded.
Assessment of 3D surface changes following virtual bracket removal | 13

b. Protocols
Model Preparation
In some instances, it was necessary to digitally remove scanning artifacts connected to brackets
prior to VBR. All protocols used in model preparation, including those for digital artifact
removal, are listed in Table I.

Table I. Protocols for model preparation.
ORTHO ANALYZER
TM

1. The bonded model was imported in STL format.
2. Prepare Model Set > Sculpt Maxillary
3. Visualization menu > Show scanner acquired texture
4.
Artifacts connected to a bracket were deleted using the Remove Artifacts tool (0.150
mm) together with zoom and 3D rotational controls (Fig 6).
5.
Zoom and 3D rotational controls were used to manipulate the digital model such that
only UR7, UR6, and UR5 were in view.
MESHMIXER
TM

1. The bonded model was imported in STL format.
2.
Artifacts connected to a bracket were selected using Brush selection mode (Unwrap-
mode, size 20) together with zoom and 3D rotational controls (Fig 7A).
a. Edit menu > Discard operation (Hotkey “X”)
3. Voids resulting from deleted artifacts were repaired (Fig 7B).
a. Analysis menu > Inspector tool (Hotkey “I”) (Fig7C)
b. Void repair by left-clicking blue sphere(s) (Fig 7D)
4.
Zoom and 3D rotational controls were used to manipulate the digital model such that
only UR7, UR6, and UR5 were in view.
UR7, upper right second molar; UR6, upper right first molar; UR5, upper right second
premolar

Assessment of 3D surface changes following virtual bracket removal | 14

Fig 6. Illustration of digital removal of an artifact connected
to a bracket using Ortho Analyzer
TM
. A, Artifact selection
using Remove Artifacts tool (0.150 mm); B, Digital removal
of selected artifact.
A B
Assessment of 3D surface changes following virtual bracket removal | 15

Fig 7. Illustration of digital removal of an artifact connected
to a bracket using Meshmixer
TM
. A, Artifact selection using
Brush mode (Unwrap-mode, size 20); B, Digital removal of
selected artifact using Discard operation (Hotkey “X”); C,
Void detection using Inspector tool (Hotkey “I”) set to
property panel defaults; D, Void repair by left-clicking blue
sphere(s).
A B
C D
Assessment of 3D surface changes following virtual bracket removal | 16

Part I
A bonded model (Model 01) was used to compare the reliability of three VBR techniques using
Ortho Analyzer™ and six techniques using Meshmixer™.
Ortho Analyzer™
The Remove Artifacts tool, while not specifically designed for VBR, can be used to virtually
debond digital models. The following techniques for VBR using Ortho Analyzer™ were
compared (Fig 8):

Technique 1 Remove Artifacts setting: 0.150 mm
Technique 2 Remove Artifacts setting: 0.405 mm
Technique 3 Remove Artifacts setting: 0.574 mm

3D Euclidean distances between surface points of the superimposed control and debonded
models from each technique were measured using VECTRA
®
Analysis Module (VAM) for
analyzing 3D images (version 2.8.3; Canfield Scientific, Parsippany, NJ). Surface changes due to
VBR were expressed via color mapping (± 300 μm visualization range).

Technique 1 Technique 2
Technique 3
Fig 8. The three Ortho Analyzer ™ techniques that were compared varied by
volumetric size of the Remove Artifacts tool.
Assessment of 3D surface changes following virtual bracket removal | 17

Meshmixer™
Although Meshmixer™ is not specifically designed for orthodontic applications, there are
several operations that can be used to virtually debond digital models. Brush selection mode
selects triangular surface faces by “painting” via Unwrap mode (which selects a highlighted,
connected patch of the surface around the brush) or Sphere mode (which replaces the surface
patch with a semitransparent sphere and selects all faces inside of the sphere) (Autodesk, 2019).
Surface Lasso selection mode is an alternative to Brush mode in which faces can be selected
without “painting” (Autodesk, 2019). Regardless of selection mode, selection boundaries can be
automatically refined using the Smooth Boundary tool (Fig 9).

A B C
Fig 9. Meshmixer ™ Smooth Boundary tool illustration. A, The bracket was selected using
either Brush or Surface Lasso mode; B, Smooth Boundary tool (Hotkey “B”) was applied;
C, The irregular selection boundary around the bracket was refined.
Assessment of 3D surface changes following virtual bracket removal | 18

The following techniques for VBR using Meshmixer™ were compared (Fig 10):

Technique 1 Selection mode: Brush
Brush mode: Sphere
Size: 30
Technique 2 Selection mode: Brush
Brush mode: Unwrap
Size: 30
Technique 3 Selection mode: Brush
Brush mode: Unwrap
Size: 30
plus Smooth Boundary tool
Technique 4 Selection mode: Brush
Brush mode: Unwrap
Size: 40
Technique 5 Selection mode: Surface Lasso
Technique 6 Selection mode: Surface Lasso
plus Smooth Boundary tool

3D Euclidean distances between surface points of the superimposed control and debonded
models from each technique were measured using VAM. Surface changes due to VBR were
expressed via regional color mapping (± 300 μm visualization range).

1 2 & 3
5 & 6 4
Fig 10. The six Meshmixer™ techniques
that were compared varied by selection
mode and volumetric size of artifact
removal.
Assessment of 3D surface changes following virtual bracket removal | 19

Part II
For each software program, the virtual debonding technique with the lowest RMS value was
used for VBR in Part II of this study. Two operators were calibrated and performed VBR
according to the same debonding protocols (Tables II and III).

Table II. Protocols for virtual bracket removal.
ORTHO ANALYZER
TM

1.
Starting at the disto-gingival aspect of UR6, each bracket was circumscribed using
the Remove Artifacts tool (0.150 mm) together with 3D rotational controls (Fig 11).
2. Brackets were virtually debonded sequentially from UR6 to UL6.
3. Debonded models were exported in STL format.
MESHMIXER
TM

1.
Starting at the disto-gingival aspect of UR6, each bracket was slowly circumscribed
using Surface Lasso selection mode together with 3D rotational controls (Fig 12A).
a.
Modify menu > Smooth Boundary tool (Hotkey “B”) > Accept (Hotkey “Enter”)
(Fig 12B)
b.
Edit menu > Erase & Fill operation (Hotkey “F”) > Accept (Hotkey “Enter”)
(Fig 12C)
2. Brackets were virtually debonded sequentially from UR6 to UL6.
3. Debonded models were exported in STL format.
UR6, upper right first molar; UL6, upper left first molar

Assessment of 3D surface changes following virtual bracket removal | 20

Table III. Summary of Meshmixer™
hotkeys.
Select mode “S”
Discard operation “X”
Inspector tool “I”
Smooth Boundary tool “B”
Accept command
“A”
“Enter”
Erase & Fill operation “F”
Undo operation “Ctrl + Z”
A B
Fig 11. Illustration of virtual bracket removal using Ortho Analyzer ™. A,
Circumscription of the bracket using Remove Artifacts tool (0.150 mm); B,
Virtual removal of the bracket.
Assessment of 3D surface changes following virtual bracket removal | 21

In Part II, 3D Euclidean distances between surface points of the superimposed control and
debonded models were measured using VAM. Surface changes due to VBR were expressed via
color mapping (± 300 μm visualization range).

B
A C
Fig 12. Illustration of virtual bracket removal using Meshmixer ™. A, Circumscription of
the bracket using Surface Lasso selection mode; B, Boundary refinement using Smooth
Boundary tool (Hotkey “B”); C, Virtual removal of the bracket using Erase & Fill
operation (Hotkey “F”) set to property panel defaults.
Assessment of 3D surface changes following virtual bracket removal | 22

c. Measurements
All Part I measurements were performed by one investigator using VAM. Surface-based
superimposition of the control and virtually debonded models using an ICP algorithm was
performed for comparative analysis of surface changes due to VBR (Fig 13). For each technique,
the Paint Area Selection tool was used to select all areas where brackets were formerly bonded
(Fig 14A). Regional color maps of the selected areas illustrated the linear surface changes due to
VBR (Fig 14B). VAM automatically calculated the minimum, maximum, Root Mean Square
(RMS), and mean values with standard deviation of the selected areas. Comparisons were made
between the three VBR techniques for Ortho Analyzer™ and six techniques for Meshmixer™.

Fig 13. Illustration of surface-based superimposition of a debonded
model and its corresponding control model using VAM.
Assessment of 3D surface changes following virtual bracket removal | 23

All Part II measurements were performed twice by one investigator after a one-week interval
using VAM. Surface-based superimposition of the control and virtually debonded models was
performed for comparative analysis of surface changes due to VBR. The Color Surface by
Distance tool (±300 μm visualization range) was used to illustrate surface changes via color
mapping (Fig 15A). For each tooth, the Paint Area Selection tool was used to select the area
where the bracket was virtually removed (Fig 15B). A regional color map of the selected area
illustrated the linear surface changes due to VBR (Fig 15C). VAM automatically calculated the
minimum, maximum, RMS, and mean values with standard deviation of each selected area.
Comparisons were made between software programs, virtually debonded models, and tooth
segments.

Fig 14. Illustration of VAM method used to measure linear surface changes by technique in Part
I. A, Selection of areas where brackets were virtually removed using Paint Area Selection tool;
B, Regional color maps of linear surface changes due to virtual bracket removal.
A
B
Assessment of 3D surface changes following virtual bracket removal | 24

Fig 15. Illustration of VAM method used to measure linear surface changes by tooth in Part II.
A, Color map of linear surface changes after virtual bracket removal on a first molar (±300 μm
visualization range); B, Selection of area where bracket was virtually removed using Paint Area
Selection tool; C, Regional color map of linear surface changes of selected area due to VBR.
A
B
C
Assessment of 3D surface changes following virtual bracket removal | 25

d. Statistical Analysis
In Part I of this study, the linear surface changes due to VBR were measured for each technique
and expressed via regional color mapping. The RMS values—which best represented the overall
magnitudes of surface change irrespective of the direction of change—of the three techniques for
Ortho Analyzer™ and six techniques for Meshmixer™ were compared.

In Part II, descriptive statistical analysis was performed with RStudio Desktop (version 3.0.2;
RStudio, Boston, MA) to describe linear surface changes due to VBR. Inter-operator
(Cronbach’s alpha) and intra-operator (ICC) reliability were determined. The Shapiro-Wilk test
was used to evaluate normality of the data. Multivariate linear regression analysis was used to
identify any statistical significance between software programs, virtually debonded models, and
tooth segments (incisors, canines/premolars, and first molars). Results were considered
significant at P < 0.05.
Assessment of 3D surface changes following virtual bracket removal | 26

4. RESULTS
In Part I of this study, 3D Euclidean distances between surface points of the superimposed
control and debonded models were measured using VAM for comparative analysis of surface
changes due to VBR (Tables IV and V). Analysis focused on RMS values, which represented the
overall magnitude of surface change due to VBR.

Of the three Ortho Analyzer™ techniques compared, the Remove Artifacts setting of 0.150 mm
(Technique 1) demonstrated the lowest RMS value (0.11 mm). The RMS value increased as the
volume removal setting was increased to 0.405 mm (Technique 2) and 0.574 mm (Technique 3).

For the six techniques evaluated using Meshmixer™, Sphere (Technique 1) and Unwrap
(Technique 2) Brush selection modes demonstrated comparable RMS values (0.11 and 0.12 mm,
respectively). Surface Lasso selection mode (Technique 5) demonstrated a lower RMS value
than Sphere and Unwrap Brush selection modes (0.08 mm). In Techniques 3 and 6, the addition
of the Smooth Boundary tool reduced the magnitude of surface change. The combination of the
Surface Lasso selection mode with the Smooth Boundary tool (Technique 6) demonstrated the
lowest RMS value (0.06 mm) of all VBR techniques.

Assessment of 3D surface changes following virtual bracket removal | 27

Table IV. Summary of surface changes (mm) of Model 01 following different
virtual bracket removal techniques using Ortho Analyzer™.
Technique Min Max RMS Mean SD
1 -0.304652 0.402592 0.105379 -0.0274003 0.101754
2 -0.416216 0.494756 0.12333 -0.0424524 0.115793
3 -0.469823 0.518618 0.145288 -0.0429242 0.138803
Min, minimum; Max, maximum; RMS, root mean square; SD, standard
deviation

Table V. Summary of surface changes (mm) of Model 01 following different
virtual bracket removal techniques using Meshmixer™.
Technique Min Max RMS Mean SD
1 -0.266458 0.446075 0.106762 0.0485289 0.095095
2 -0.279261 0.435544 0.118286 0.0486287 0.107828
3 -0.187365 0.25123 0.072009 0.037288 0.0616028
4 -0.131243 0.375306 0.105855 0.0599282 0.0872582
5 -0.145079 0.346742 0.0766292 0.0330738 0.0691242
6 -0.20775 0.271641 0.0645386 0.0303714 0.0569457
Min, minimum; Max, maximum; RMS, root mean square; SD, standard
deviation

In Part II of this study, descriptive statistical analysis of 3D Euclidean distances between surface
points of superimposed control and debonded models was performed to describe linear changes
due to VBR. Analysis focused on RMS values—which represented the overall magnitude of
surface change due to VBR—and mean values—which indicated the net direction of surface
change.
Assessment of 3D surface changes following virtual bracket removal | 28

Inter-operator (Cronbach’s alpha) and intra-operator (ICC) reliability were determined to be high
(> 0.9). Because there were no significant inter-operator differences in VBR or intra-operator
measurement reliability, the RMS values from both operators and measurement trials were
averaged by tooth for each software program. The mean surface changes of each tooth were also
averaged. Normal distribution of the data for both software programs was confirmed with the
Shapiro-Wilk test. Multivariate linear regression analysis was used to identify any statistically
significant differences between software programs, virtually debonded models, and tooth
segments (incisors, canines/premolars, and first molars).

As summarized in Table VI, the averaged RMS and mean surface changes of the models
debonded with Ortho Analyzer™ were 0.077 mm (SD 0.05) and -0.017 mm (SD 0.05),
respectively. The averaged RMS and mean surface changes of the models debonded with
Meshmixer™ were 0.075 mm (SD 0.05) and -0.011 mm (SD 0.06).

Table VI. Summary of averaged RMS (mm) and mean surface changes (mm) of each software
program after virtual bracket removal.
Software Program RMS SD Mean SD
Ortho Analyzer™ 0.0770479 0.0507455 -0.017494598 0.05498944
Meshmixer™ 0.07497618 0.04530797 -0.01119033 0.0627295
RMS, root mean square; SD, standard deviation

Assessment of 3D surface changes following virtual bracket removal | 29

There was a similar pattern of distribution of RMS values ranging from 0.03 to 0.22 mm for both
software programs (Fig 16). Although the averaged means for the software programs were
comparable, there was a wider distribution between the positive and negative extremes of Ortho
Analyzer™ compared to Meshmixer™ (Fig 17). However, multivariate linear regression
analysis did not show a statistically significant difference in the overall magnitude or net
direction of surface changes between software programs.

0
0.05
0.1
0.15
0.2
0.25
RMS Values by Software Program
Meshmixer
Ortho Analyzer
Fig 16. Plot illustrating agreement between software programs in the overall magnitude of
surface changes (mm) after virtual bracket removal.
Assessment of 3D surface changes following virtual bracket removal | 30

Table VII summarizes the averaged RMS and mean surface changes of the nine virtually
debonded models. The overall magnitude of surface change between control and virtually
debonded models ranged from 0.06 to 0.09 mm for all models. There was a comparable pattern
of distribution between models with the averaged RMS values ranging from 0.03 to 0.22 mm
(Fig 18). The net direction of surface change was negative for 89% of the virtually debonded
models (Fig 19). Averaged RMS and mean values were comparable across all models and
multivariate linear regression analysis did not show any statistically significant differences in the
overall magnitude or net direction of surface changes between virtually debonded models.

-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
Mean Surface Changes by Software Program
Meshmixer
Ortho Analyzer
Fig 17. Plot illustrating agreement between software programs in the net direction of surface
changes (mm) after virtual bracket removal, but disagreement in the pattern of distribution of
positive and negative extremes.
Assessment of 3D surface changes following virtual bracket removal | 31

Table VII. Summary of averaged RMS (mm) and mean surface changes (mm) of each model
after virtual bracket removal.
Model RMS SD Mean SD
01 0.08505517 0.05453957 0.028709174 0.06087598
02 0.07526887 0.03343044 -0.015491302 0.05693789
03 0.06872956 0.02039869 -0.018425941 0.03587241
04 0.06120898 0.05543049 -0.023760362 0.04943046
05 0.08838859 0.05599217 -0.013607605 0.07640361
06 0.06337201 0.02115969 -0.006477707 0.04996005
07 0.08788764 0.05719113 -0.042890501 0.05714593
08 0.08308104 0.06477432 -0.027110945 0.06925135
09 0.07111656 0.05211396 -0.010027009 0.05709504
RMS, root mean square; SD, standard deviation

Fig 18. Plot illustrating agreement between models in the overall magnitude of surface changes
(mm) after virtual bracket removal.
0
0.05
0.1
0.15
0.2
0.25
RMS Values by Model
Model 01
Model 02
Model 03
Model 04
Model 05
Model 06
Model 07
Model 08
Model 09
Assessment of 3D surface changes following virtual bracket removal | 32

Table VIII summarizes the results of multivariate linear regression analysis. The coefficient
estimates for software programs and models did not differ significantly, whereas the coefficient
estimates for tooth segments showed a significant difference (P < 0.05) for averaged RMS and
mean surface changes. Consequently, the linear regression models were simplified into single-
variable models equivalent to one-way ANOVAs (Tables IX and XI). The averaged RMS values
of the incisor, canine/premolar, and first molars segments were 0.05 mm, 0.06 mm, and 0.15
mm, respectively. The averaged mean values of the incisor, canine/premolar, and first molars
segments were -0.03 mm, 0.02 mm, and -0.10 mm, respectively.

Post hoc analysis with Scheffé ’s test showed a pairwise difference in averaged RMS values
between the incisor and first molar segments as well as between canine/premolar and first molar
Fig 19. Plot illustrating agreement between models in the net direction of surface changes (mm)
after virtual bracket removal.
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
Mean Surface Changes by Model
Model 01
Model 02
Model 03
Model 04
Model 05
Model 06
Model 07
Model 08
Model 09
Assessment of 3D surface changes following virtual bracket removal | 33

segments, but not between the incisor and canine/premolar segments (Table X). Post hoc
comparisons showed a pairwise difference in mean surface changes between all tooth segments
(Table XII).

Table VIII. Summary of multivariate linear regression analysis.
RMS Mean
Variables
Coefficient
Estimate
P-value
Coefficient
Estimate
P-value
Software Programs 0.0065639 0.376 -0.008258 0.44925
Models -0.0007178 0.623 -0.003691 0.08253
Tooth Segments 0.0417188 1.17E-11
*
-0.022730 0.00492*
*Statistically significant
RMS, root mean square; SD, standard deviation

Table IX. One-way ANOVA of RMS values (mm) by tooth segment.
SUMMARY
Groups Count Sum Average Variance
Incisors 36 1.95714874 0.05436524 0.0002532
Canines/Premolars 54 3.50971721 0.06499476 0.0010781
First molars 18 2.74243523 0.15235751 0.0030031

Source of Variation SS df MS F P-value F crit
Between Groups 0.128339 2 0.064170 57.56007 1.3268E-17 3.082852
Within Groups 0.117057 105 0.001115
Total 0.245396 107
SS, sum of squares; df, degrees of freedom; MS, mean squares; F, F statistic; F crit, F
critical value

Assessment of 3D surface changes following virtual bracket removal | 34

Table X. Scheffé ’s post hoc analysis of RMS values (mm) by tooth segment.
Pair T-statistic P-value Inference
Incisors v. Canine/Premolars 1.4796 0.3384709 NS
Incisors v. First Molars 10.1667 2.2204E-16 P < 0.01*
Canines/Premolars v. First Molars 9.6137 3.9968E-15 P < 0.01*
*Statistically significant
NS, not significant

Table XI. One-way ANOVA of mean surface changes (mm) by tooth segments.
SUMMARY
Groups Count Sum Average Variance
Incisors 36 -0.9480508 -0.0263347 0.00049012
Canines/Premolars 54 1.24818019 0.02311445 0.00148971
First molars 18 -1.8491158 -0.1027287 0.00307197

Source of Variation SS df MS F P-value F crit
Between Groups 0.221559 2 0.110779 78.41744 1.4655E-21 3.082852
Within Groups 0.148332 105 0.001413
Total 0.369891 107
SS, sum of squares; df, degrees of freedom; MS, mean squares; F, F statistic; F crit, F
critical value

Assessment of 3D surface changes following virtual bracket removal | 35

Table XII. Scheffé ’s post hoc analysis of mean surface changes (mm) by tooth segment.
Pair T-statistic P-value Inference
Incisors v. Canine/Premolars 6.1145 1.1354E-07 P < 0.01*
Incisors v. First Molars 7.0409 1.5233E-09 P < 0.01*
Canines/Premolars v. First Molars 12.3019 1.1102E-16 P < 0.01*
*Statistically significant

A similar pattern of distribution of the averaged RMS values ranging from 0.03 to 0.21 mm was
seen in the incisor and canine/premolar segments (Fig 20). However, the pattern of distribution
seen in the first molar segments illustrated significantly greater RMS values.

0
0.05
0.1
0.15
0.2
0.25
RMS Values by Tooth Segment
Incisors
Canine/Premolars
First Molars
Fig 20. Plot illustrating disagreement between tooth segments in the overall magnitude of surface
changes (mm) after virtual bracket removal, with first molar segments showing the greatest RMS
values.
Assessment of 3D surface changes following virtual bracket removal | 36

The pattern of distribution of directional surface changes was significantly different in all tooth
segments (Fig 21). Incisors showed the narrowest clustering compared to the wider distributions
seen for canines/premolars and first molars. The net direction of surface change was positive for
the canine/premolar segments, and negative for the incisors and first molar segments.

In addition to quantitative analysis, color mapping illustrated surface changes due to VBR using
Ortho Analyzer™ and Meshmixer™ (Fig 22). Color map visualization showed that negative
surface changes (blue hues) were more prevalent in the incisor and first molar segments while
positive surface changes (red hues) were more prevalent in the canines/premolar segments.

-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
Mean Surface Changes by Tooth Segment
Incisors
Canine/Premolars
First Molars
Fig 21. Plot illustrating disagreement between tooth segments in the net direction of surface
changes (mm) after virtual bracket removal.
Assessment of 3D surface changes following virtual bracket removal | 37

Fig 22. Illustration of linear surface changes between
a control model and its corresponding debonded
model by tooth segment. Red hues indicate positive
surface changes, whereas blue hues indicate negative
surface changes.
Assessment of 3D surface changes following virtual bracket removal | 38

5. DISCUSSION
Since VBR has not been investigated in the literature, Part I of this study was designed to
establish reliable VBR techniques for Ortho Analyzer™ and Meshmixer™. Techniques were
assessed by superimposing the control and virtually debonded models and using VAM’s Paint
Area Selection tool to measure linear surface changes of all areas where brackets were virtually
removed. RMS values, which represented the overall magnitudes of surface change, were
compared between techniques.

The Remove Artifacts tool in Ortho Analyzer™ was designed for the removal of artifacts caused
by intraoral scanning (3Shape, 2017). However, online resources published by 3Shape have
demonstrated that this tool can also be used for VBR (3Shape, 2015a). The volumetric size of the
removal tool can be adjusted to accommodate the dimensions of the digital artifact of interest.

Of the three VBR techniques evaluated for Ortho Analyzer™, the lowest Remove Artifacts
setting (0.150 mm) demonstrated the lowest RMS value (0.11 mm). The overall magnitude of
surface change increased as the volume of the removal setting was increased. The lowest setting
allowed for more precise circumscription of the bracket compared to the higher settings, which
might explain these findings. Therefore, Technique 1 was used with Ortho Analyzer™ in Part II
of this study.

Assessment of 3D surface changes following virtual bracket removal | 39

In Meshmixer™, Brush and Surface Lasso modes can be used to select and delete digital
artifacts (Autodesk, 2019), including orthodontic brackets. Settings, including Brush mode and
size, can be adjusted according to the artifact of interest. Moreover, accessory tools can be used
to refine selection boundaries.

For the six VBR techniques evaluated in Meshmixer™, Surface Lasso selection mode
demonstrated a lower RMS value (0.08 mm) than Sphere and Unwrap Brush selection modes,
which may be attributable to how the different selection modes influence the selection boundary.
In Surface Lasso mode, the bracket was circumscribed and only the faces inside the lasso were
selected, whereas the bracket was “painted” in Brush mode. It is possible that over-selection of
triangular faces at the periphery of the bracket was more likely in Brush mode and that over-
selection may have increased the magnitude of surface changes. Although the selection boundary
was more precise with Surface Lasso mode, it is important to note that lasso selection can fail on
meshes with very skinny triangles. However, slow circumscription can overcome this limitation
(Autodesk, 2019).

Utilization of the Smooth Boundary tool reduced the overall magnitude of surface change for
both selection modes. This outcome was anticipated because the tool was designed to transform
irregular selection boundaries into smooth loops (Autodesk, 2019). The combination of Surface
Lasso mode with the Smooth Boundary tool demonstrated the lowest RMS value (0.06 mm) of
all VBR techniques. Consequently, Technique 6 was used with Meshmixer™ in Part II of this
study.

Assessment of 3D surface changes following virtual bracket removal | 40

The purpose of Part II of this study was to assess the accuracy and reproducibility of the VBR
techniques established in Part I for Ortho Analyzer™ and Meshmixer™. Accuracy was assessed
by superimposing the control and virtually debonded models and using VAM’s Color Surface by
Distance tool (±300 μm visualization range) to illustrate linear surface changes between the
models. The Paint Area Selection tool, which is designed for identifying regions of dimensional
difference (Scientific, 2018), was used to generate regional color maps on the labial surfaces
where brackets were virtually removed for quantitative analysis of the minimums, maximums,
RMS values, means, and standard deviations. Negative values (blue hues) indicated zones of
unintentional tooth surface removal, whereas the positive values (red hues) indicated zones of
inadequate bracket removal. Averaged RMS values represented the overall magnitude of surface
changes, whereas mean values indicated the net direction of changes. Comparisons of averaged
RMS and mean surface changes were made between software programs, virtually debonded
models, and tooth segments.

There were no significant inter-operator differences in VBR using Ortho Analyzer™ and
Meshmixer™ (Cronbach’s alpha > 0.90). Moreover, intra-operator measurement reliability was
high (> 0.90). Thus, for each software program, the RMS values from both operators and
measurement trials were averaged by tooth. The mean surface changes were also pooled and
averaged by tooth. Normality of the averaged RMS and mean surface change data was confirmed
with the Shapiro-Wilk test, and multivariate linear regression analysis was used to identify any
statistical significance between software programs, virtually debonded models, and tooth
segments (incisors, canines/premolars, and first molars).

Assessment of 3D surface changes following virtual bracket removal | 41

The linear regression models did not show any statistically significant differences in the overall
magnitude or net direction of surface changes between software programs or virtually debonded
models. VBR using Ortho Analyzer™ and Meshmixer™ resulted in a comparable magnitude of
surface change (0.077 mm and 0.075 mm, respectively) that was net negative in direction. In
other words, on average, VBR resulted in unintentional removal of tooth surface.

Given that only the coefficient estimates for tooth segments showed statistical significance (P <
0.05), the linear regression models for RMS and mean surface changes were simplified into
single-variable models equivalent to one-way ANOVAs. Because the sample sizes of the tooth
segments were unequal, post hoc analysis with Scheffé ’s test (Scheffé , 1959) was conducted to
evaluate pairwise differences between segments. This conservative test has the added advantage
of controlling Type I error (Kao and Green, 2008), meaning it is more likely that any differences
found between segments would be truly significant.

The first molar segments demonstrated a significantly greater amount of surface change (0.15
mm) compared to the incisor and canine/premolar segments, indicating that VBR is least
accurate in the posterior segments. Additionally, post hoc analysis showed a statistically
significant difference in mean surface changes between all tooth segments. Surface changes were
net negative in the incisor and first molar segments and positive in the canine/premolar
segments. Color mapping showed a prevalence of blue hues on the labial surfaces of incisors and
first molars and red hues on the surfaces of canines and premolars. Negative surface changes
(blue hues) indicated removal of tooth surface during VBR, whereas positive surface changes
(red hues) indicated inadequate bracket removal.
Assessment of 3D surface changes following virtual bracket removal | 42

While earlier studies focused on the influence of digital models on the accuracy of virtual
diagnosis and treatment planning (Vaid, 2018), recent publications have focused on their
applications in CAD/CAM appliance fabrication (Claus et al., 2018; Jheon et al., 2017; Nasef et
al., 2014; Park et al., 2016; Tarraf and Ali, 2018). Although the clinical acceptability of
appliances fabricated from digital and conventional models is comparable (Vasudavan et al.,
2010), optimal adaption to the dentition is dependent on the accuracy of the working models.
Digital models contain a source risk for inaccuracy because multiple, consecutively recorded 3D
images must be assembled by the intraoral scanner (Claus et al., 2018). However, several authors
have shown that the accuracy of commercially available scanners, including TRIOS
®
, is
sufficient for numerous orthodontic applications (Claus et al., 2018; Ender and Mehl, 2013b;
Flügge et al., 2013; Gan et al., 2016; Jung et al., 2016; Lim et al., 2018). Furthermore, for
patients in treatment with labial fixed appliances, intraoral scanning was proven to be less
susceptible to errors than conventional impression methods (Claus et al., 2018).

In this study, superimposition of the control and bonded digital models was performed prior to
VBR and verified less than 100 μm of error due to intraoral scanning. Thus, any surface changes
greater than 0.10 mm between the control and virtually debonded models were attributable to
VBR and considered virtual debonding error. Since the overall magnitude of surface changes for
both Ortho Analyzer™ and Meshmixer™ was less than 0.10 mm, the source of error cannot be
definitively determined. However, regardless of whether the surface changes were attributable
intraoral scanning or virtual debonding, it is unlikely that errors less than 0.10 mm would have
any clinical significance on the adaptation of a retainer fabricated from a digital working model.
Assessment of 3D surface changes following virtual bracket removal | 43

Therefore, VBR using Ortho Analyzer™ and Meshmixer™ can be utilized in the computer-aided
design and manufacture of retainers.

Although virtual debonding error was nominal for both software programs, there was a
statistically significant difference in surface changes between tooth segments, with VBR in the
first molar segments demonstrating the least accuracy. While studies have shown that intraoral
scanning with TRIOS
®
is least accurate in the molar region (Anh et al., 2016; Ender et al., 2016;
Flügge et al., 2013; Rudolph et al., 2007), scanning error is less than 100 μm at the distal tooth
(Ender et al., 2016). Superimposition between the control and bonded virtual models performed
prior to VBR verified that scanning accuracy was within 100 μm. Thus, surface changes seen in
first molar segments that exceeded the amount of error attributable to intraoral scanning must be
considered virtual debonding error. One possible explanation for the significance is that the
software may not be able to navigate strong changes in surface curvature, similar to how
curvature limits the accuracy of intraoral scanners (Rudolph et al., 2007).

The combination of scanning and virtual debonding error seen in the first molar segments may
be clinically significant, as it has been suggested that errors greater than 0.10 mm may have a
significant impact on the adaptation of appliances fabricated from digital working models
(Wiranto et al., 2013). The net negative direction of these surface changes may increase clinical
significance because retainers—particularly vacuum-formed thermoplastic retainers—may not
adapt well to areas where tooth surface was unintentionally removed. Since optimal adaptation to
the dentition is critical for retention (Rudolph et al., 2007), additional research is needed to
investigate the clinical implications of virtual debonding error in the posterior segments.
Assessment of 3D surface changes following virtual bracket removal | 44

6. CONCLUSION
VBR is comparatively accurate and reproducible using Ortho Analyzer™ and Meshmixer™.
Both software programs can be utilized in the computer-aided design and manufacture of
retainers, although minor relief on the labial surfaces of posterior segments due to unintentional
tooth surface removal may be necessary. Moreover, VBR can be delegated to trained auxiliaries
or laboratory technicians as indicated by high inter-operator reliability. Furthermore, the
fabrication of retainers from virtually debonded models facilitates same-day delivery, thereby
minimizing the risk of relapse or other undesirable tooth movement after appliance removal.

Table XIII summarizes the digital workflow for VBR. Because the precision of clinical bracket
removal can vary, future studies should investigate the accuracy of VBR using intraoral scans of
bonded dentitions. The influence of different bracket materials and characteristics, including
clear aligner attachments, on VBR should also be investigated.

Table XIII. Digital workflow for virtual bracket removal.
1. Acquire intraoral scan of the bonded dentition.
2. Perform VBR on the digital model using 3D modeling software.
3. 3D print the virtually debonded model for retainer fabrication.
4. Perform clinical bracket removal and deliver retainer(s).

Assessment of 3D surface changes following virtual bracket removal | 45

As there were no significant differences in accuracy between VBR using Ortho Analyzer™ and
Meshmixer™, decisions between software programs are multifactorial and depend on the
intended applications of the software. Considerations include cost, ease of use, efficiency, and
versatility (Table XIV).

Table XIV. Multifactorial comparison between Ortho Analyzer™ and Meshmixer™.
Factor Ortho Analyzer™ Meshmixer™
Cost Commercially available Freeware
Ease of Use Basic operations Complex functionality
Efficiency Manual
Automated
(keyboard shortcuts)
Versatility
Designed specifically for use
in orthodontics
Unlimited applications

Assessment of 3D surface changes following virtual bracket removal | 46

7. REFERENCES
3Shape (2015a). How To De-Bond a Model. In 3Shape Ortho System "How-To" Series, 3Shape,
ed. (Denmark: 3Shape).
3Shape (2015b). TRIOS
®
User Manual.
3Shape (2017). Ortho System User Manual.
Anh, J.W., Park, J.M., Chun, Y.S., Kim, M., and Kim, M. (2016). A comparison of the precision
of three-dimensional images acquired by 2 digital intraoral scanners: effects of tooth irregularity
and scanning direction. Korean Journal of Orthodontics 46, 3-12.
Autodesk (2019). Meshmixer Overview.
Besl, P.J., and McKay, N.D. (1992). A Method for Registration of 3-D Shapes. IEEE
Transactions on Pattern Analysis and Machine Intelligence 14, 239-256.
Brown, L.G. (1992). A survey of image registration techniques. ACM Computing Surveys 24,
325-376.
Claus, D., Radeke, J., Zint, M., Vogel, A.B., Satravaha, Y., Kilic, F., Hibst, R., and Lapatki, B.G.
(2018). Generation of 3D digital models of the dental arches using optical scanning techniques.
Seminars in Orthodontics 24, 416-429.
Ender, A., Attin, T., and Mehl, A. (2016). In vivo precision of conventional and digital methods
of obtaining complete-arch dental impressions. Journal of Prosthetic Dentistry 115, 313-320.
Ender, A., and Mehl, A. (2013a). Accuracy of complete-arch dental impressions: a new method
of measuring trueness and precision. Journal of Prosthetic Dentistry 109, 121-128.
Assessment of 3D surface changes following virtual bracket removal | 47

Ender, A., and Mehl, A. (2013b). Influence of scanning strategies on the accuracy of digital
intraoral scanning systems. International Journal of Computerized Dentistry 16, 11-21.
Flügge, T.V., Schlager, S., Nelson, K., Nahles, S., and Metzger, M.C. (2013). Precision of
intraoral digital dental impressions with iTero and extraoral digitization with the iTero and a
model scanner. American Journal of Orthodontics and Dentofacial Orthopedics 144, 471-478.
Gan, N., Xiong, Y., and Jiao, T. (2016). Accuracy of Intraoral Digital Impressions for Whole
Upper Jaws, Including Full Dentitions and Palatal Soft Tissues. PLOS ONE 11, e0158800.
Ghoneima, A., Cho, H., Farouk, K., and Kula, K. (2017). Accuracy and reliability of landmark-
based, surface-based and voxel-based 3D cone-beam computed tomography superimposition
methods. Orthodontics & Craniofacial Research 20, 227-236.
Gkantidis, N., Schauseil, M., Pazera, P., Zorkun, B., Katsaros, C., and Ludwig, B. (2015).
Evaluation of 3-dimensional superimposition techniques on various skeletal structures of the
head using surface models. PLOS ONE 10, e0118810.
Grauer, D., Cevidanes, L.S.H., and Proffit, W.R. (2009). Working with DICOM craniofacial
images. American Journal of Orthodontics and Dentofacial Orthopedics 136, 460-470.
Groth, C., Kravitz, N.D., and Shirck, J.M. (2018). Incorporating three-dimensional printing in
orthodontics. Journal of Clinical Orthodontics : JCO 52, 28-33.
Hazeveld, A., Huddleston Slater, J.J.R., and Ren, Y. (2014). Accuracy and reproducibility of
dental replica models reconstructed by different rapid prototyping techniques. American Journal
of Orthodontics and Dentofacial Orthopedics 145, 108-115.
Jheon, A.H., Oberoi, S., Solem, R.C., and Kapila, S. (2017). Moving towards precision
orthodontics: An evolving paradigm shift in the planning and delivery of customized orthodontic
therapy. Orthodontics & Craniofacial Research 20 Suppl 1, 106-113.
Assessment of 3D surface changes following virtual bracket removal | 48

Jung, Y.R., Park, J.M., Chun, Y.S., Lee, K.N., and Kim, M. (2016). Accuracy of four different
digital intraoral scanners: effects of the presence of orthodontic brackets and wire. International
Journal of Computerized Dentistry 19, 203-215.
Kao, L.S., and Green, C.E. (2008). Analysis of variance: is there a difference in means and what
does it mean? Journal of Surgical Research 144, 158-170.
Kravitz, N.D. (2010). Debanding Day: The final step in creating simply spectacular smiles. In
OrthodonticProductsOnline.com, pp. 64-68.
Lim, J.H., Park, J.M., Kim, M., Heo, S.J., and Myung, J.Y. (2018). Comparison of digital
intraoral scanner reproducibility and image trueness considering repetitive experience. Journal of
Prosthetic Dentistry 119, 225-232.
Lin, H.H., Chiang, W.C., Lo, L.J., and Wang, C.H. (2013). A new method for the integration of
digital dental models and cone-beam computed tomography images. Conference proceedings:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society
IEEE Engineering in Medicine and Biology Society Annual Conference 2013, 2328-2331.
Mack, S., Bonilla, T., English, J.D., Cozad, B., and Akyalcin, S. (2017). Accuracy of 3-
dimensional curvilinear measurements on digital models with intraoral scanners. American
Journal of Orthodontics and Dentofacial Orthopedics 152, 420-425.
Nasef, A.A., El-Beialy, A.R., and Mostafa, Y.A. (2014). Virtual techniques for designing and
fabricating a retainer. American Journal of Orthodontics and Dentofacial Orthopedics 146, 394-
398.
Nelson, G. (2015). Post-Treatment Management of Orthodontic Patients. In Dentaltown
Magazine.
Assessment of 3D surface changes following virtual bracket removal | 49

Park, J.M., Choi, S.A., Myung, J.Y., Chun, Y.S., and Kim, M. (2016). Impact of Orthodontic
Brackets on the Intraoral Scan Data Accuracy. BioMed Research International 2016, 5075182.
Rudolph, H., Luthardt, R.G., and Walter, M.H. (2007). Computer-aided analysis of the influence
of digitizing and surfacing on the accuracy in dental CAD/CAM technology. Computers in
Biology and Medicine 37, 579-587.
Sassani, F., Elmajian, A.R.A., and Roberts, S. (1995). Computer-assisted fabrication of
orthodontic appliances: Considering the possibilities. The Journal of the American Dental
Association 126, 1296-1300.
Scheffé , H. (1959). The analysis of variance (New York: Wiley).
Canfield Scientific (2018). VECTRA User Guide.
Sousa, M.V.S., Vasconcelos, E.C., Janson, G., Garib, D., and Pinzan, A. (2012). Accuracy and
reproducibility of 3-dimensional digital model measurements. American Journal of Orthodontics
and Dentofacial Orthopedics 142, 269-273.
Tahir, N.M., Wan Hassan, W.N., and Saub, R. (2018). Comparing retainers constructed on
conventional stone models and on 3D printed models: a randomized crossover clinical study.
European Journal of Orthodontics.
Tarraf, N.E., and Ali, D.M. (2018). Present and the future of digital orthodontics. Seminars in
Orthodontics 24, 376-385.
Vaid, N.R. (2018). Digital technologies in orthodontics: An update. Seminars in Orthodontics 24,
373-375.
Vasudavan, S., Sullivan, S.R., and Sonis, A.L. (2010). Comparison of intraoral 3D scanning and
conventional impressions for fabrication of orthodontic retainers. Journal of Clinical
Orthodontics: JCO 44, 495-497.
Assessment of 3D surface changes following virtual bracket removal | 50

Wiranto, M.G., Engelbrecht, W.P., Tutein Nolthenius, H.E., van der Meer, W.J., and Ren, Y.
(2013). Validity, reliability, and reproducibility of linear measurements on digital models
obtained from intraoral and cone-beam computed tomography scans of alginate impressions.
American Journal of Orthodontics and Dentofacial Orthopedics 143, 140-147.
Zitová, B., and Flusser, J. (2003). Image registration methods: a survey. Image and Vision
Computing 21, 977-1000.

Assessment of 3D surface changes following virtual bracket removal | 51

8. APPENDIX
Table XV. RMS values of virtual bracket removal using Ortho Analyzer™.
Model Tooth M1 M2 M3 M4 AVG SD
01
UR6 0.0819915 0.0814511 0.0726956 0.0701698 0.076577 0.006033
UR5 0.251947 0.229137 0.17325 0.192815 0.211787 0.035397
UR4 0.147881 0.134614 0.123535 0.140404 0.136609 0.010269
UR3 0.0462249 0.0430243 0.0511129 0.0629247 0.050822 0.008727
UR2 0.0545971 0.0509014 0.0408421 0.0410702 0.046853 0.006975
UR1 0.0332119 0.0317364 0.0251282 0.0270519 0.029282 0.003816
UL6 0.0817346 0.0816048 0.111202 0.112859 0.09685 0.017542
UL5 0.202033 0.182603 0.206185 0.211153 0.200494 0.012496
UL4 0.108686 0.108177 0.150744 0.153786 0.130348 0.025339
UL3 0.0612361 0.0592344 0.0548707 0.0504335 0.056444 0.004808
UL2 0.0396792 0.037207 0.0428874 0.0454833 0.041314 0.003624
UL1 0.152397 0.137259 0.0299063 0.0296369 0.0873 0.066715
02
UR6 0.10663 0.106008 0.117675 0.116648 0.11174 0.006279
UR5 0.168588 0.16659 0.18397 0.15585 0.16875 0.011587
UR4 0.0243147 0.025019 0.0378834 0.037756 0.031243 0.007599
UR3 0.0528607 0.0475059 0.056794 0.0570578 0.053555 0.004466
UR2 0.0739382 0.0785349 0.0941581 0.0930739 0.084926 0.010218
UR1 0.0679933 0.0714826 0.0684207 0.0673578 0.068814 0.001832
UL6 0.102767 0.103554 0.126573 0.125022 0.114479 0.013089
UL5 0.124409 0.124748 0.122579 0.112421 0.121039 0.005824
UL4 0.0628374 0.0629027 0.0609401 0.0600777 0.061689 0.001408
UL3 0.0454226 0.0445229 0.04073 0.0419483 0.043156 0.002187
UL2 0.0604923 0.0571345 0.0476927 0.0451702 0.052622 0.007351
UL1 0.0563112 0.0610554 0.0433483 0.0420173 0.050683 0.009454
03
UR6 0.10694 0.100668 0.0887681 0.087897 0.096068 0.009299
UR5 0.0509848 0.0490832 0.0471542 0.0495194 0.049185 0.00158
UR4 0.0458171 0.0433464 0.0609249 0.0644301 0.05363 0.010593
UR3 0.0650751 0.0631991 0.0595262 0.0611121 0.062228 0.002422
UR2 0.105443 0.10137 0.10084 0.109104 0.104189 0.003868
UR1 0.0636549 0.0659451 0.0524976 0.0571423 0.05981 0.006138
UL6 0.091584 0.088978 0.0907926 0.0908556 0.090553 0.001109
UL5 0.0442964 0.0439769 0.07561 0.0826059 0.061622 0.020392
UL4 0.0690011 0.0661278 0.0992872 0.106184 0.08515 0.020534
UL3 0.0556234 0.0576213 0.0440863 0.0449163 0.050562 0.007054
UL2 0.0560181 0.0526208 0.0571039 0.0577081 0.055863 0.002272
Assessment of 3D surface changes following virtual bracket removal | 52

UL1 0.0315498 0.0301853 0.0267422 0.0238355 0.028078 0.003477
04
UR6 0.16471 0.176544 0.175194 0.174921 0.172842 0.005468
UR5 0.0462811 0.0467977 0.0398366 0.0413975 0.043578 0.003485
UR4 0.0350761 0.0361681 0.0393573 0.036833 0.036859 0.001816
UR3 0.0646807 0.0603344 0.0199892 0.0204675 0.041368 0.024475
UR2 0.0346799 0.0341063 0.0265001 0.0275589 0.030711 0.00428
UR1 0.0455118 0.0449663 0.031496 0.031783 0.038439 0.007856
UL6 0.168831 0.172 0.171699 0.167082 0.169903 0.002362
UL5 0.0476053 0.0469034 0.0615698 0.0621778 0.054564 0.008449
UL4 0.0591866 0.0540868 0.0570684 0.0549849 0.056332 0.002276
UL3 0.0286122 0.0257837 0.0349243 0.0340089 0.030832 0.004369
UL2 0.0378204 0.040023 0.0382303 0.0398296 0.038976 0.001113
UL1 0.0296589 0.0291775 0.0375613 0.0372664 0.033416 0.004622
05
UR6 0.194123 0.212257 0.176489 0.159521 0.185598 0.022704
UR5 0.0789031 0.0821636 0.0799938 0.0830553 0.081029 0.001913
UR4 0.0689853 0.070315 0.0988016 0.0974487 0.083888 0.016458
UR3 0.0688409 0.0704502 0.0804346 0.0807615 0.075122 0.006359
UR2 0.0378984 0.0424378 0.0353185 0.0369886 0.038161 0.003045
UR1 0.0402489 0.0435457 0.0328549 0.0313038 0.036988 0.00586
UL6 0.203414 0.226882 0.180619 0.191592 0.200627 0.019825
UL5 0.0508085 0.0545054 0.0573995 0.0566624 0.054844 0.002957
UL4 0.0476935 0.0471999 0.0547082 0.0514071 0.050252 0.003514
UL3 0.0356162 0.0355111 0.0423629 0.0377132 0.037801 0.003206
UL2 0.0810454 0.0851723 0.0735945 0.0667836 0.076649 0.008137
UL1 0.0655363 0.0683835 0.0752623 0.0677881 0.069243 0.004196
06
UR6 0.0915173 0.0956585 0.080088 0.0825606 0.087456 0.007349
UR5 0.0619792 0.064842 0.0641021 0.0633865 0.063577 0.00122
UR4 0.0636838 0.0614746 0.0644184 0.0649347 0.063628 0.001525
UR3 0.0308045 0.0307655 0.0385864 0.0372532 0.034352 0.004155
UR2 0.0778381 0.0695641 0.054169 0.0552545 0.064206 0.011481
UR1 0.0372469 0.0397637 0.0523738 0.0497105 0.044774 0.007391
UL6 0.0811898 0.0802708 0.0832241 0.0871507 0.082959 0.003055
UL5 0.0536024 0.0557267 0.0487386 0.0492768 0.051836 0.003386
UL4 0.0796451 0.0713386 0.059622 0.060563 0.067792 0.009523
UL3 0.0332866 0.0349077 0.0414975 0.0398913 0.037396 0.003921
UL2 0.0563492 0.0554181 0.103784 0.0937522 0.077326 0.025099
UL1 0.0921091 0.100142 0.111818 0.103284 0.101838 0.008149
07
UR6 0.202868 0.201236 0.213772 0.216728 0.208651 0.007744
UR5 0.0870142 0.0860237 0.0980308 0.100759 0.092957 0.007528
UR4 0.0884636 0.0885035 0.10056 0.101249 0.094694 0.007177
UR3 0.10754 0.110868 0.117227 0.119183 0.113705 0.00543
UR2 0.129209 0.125547 0.100902 0.103033 0.114673 0.014772
UR1 0.0389379 0.0357152 0.0548583 0.0579068 0.046855 0.01115
UL6 0.228383 0.21119 0.217697 0.22734 0.221153 0.008201
UL5 0.0649012 0.0648342 0.0545075 0.0518721 0.059029 0.006828
Assessment of 3D surface changes following virtual bracket removal | 53

UL4 0.0613538 0.0610519 0.0575042 0.0587367 0.059662 0.001853
UL3 0.0391606 0.0391399 0.0416456 0.0410747 0.040255 0.001297
UL2 0.0661537 0.0651903 0.0615122 0.0588405 0.062924 0.003378
UL1 0.0541124 0.0508617 0.0412517 0.04181 0.047009 0.006467
08
UR6 0.232289 0.236088 0.224981 0.235578 0.232234 0.00512
UR5 0.0437715 0.0440037 0.0519607 0.0515818 0.047829 0.004555
UR4 0.0546706 0.0554591 0.0463416 0.0463752 0.050712 0.005037
UR3 0.0668 0.0627179 0.0553438 0.0598196 0.06117 0.004826
UR2 0.0743568 0.0750724 0.0489033 0.0525544 0.062722 0.013931
UR1 0.0538047 0.0506734 0.0588687 0.0638088 0.056789 0.005771
UL6 0.24296 0.227755 0.198274 0.1972 0.216547 0.022594
UL5 0.0336104 0.0343054 0.0307115 0.0302978 0.032231 0.002021
UL4 0.0318348 0.0325097 0.033554 0.0329397 0.03271 0.000724
UL3 0.0514337 0.0535245 0.0437774 0.043338 0.048018 0.005224
UL2 0.104795 0.106981 0.089847 0.0892188 0.09771 0.009488
UL1 0.106785 0.0978413 0.0835294 0.0887423 0.094225 0.010252
09
UR6 0.160363 0.187358 0.176068 0.173364 0.174288 0.011087
UR5 0.0650287 0.0649626 0.0526943 0.0522472 0.058733 0.007234
UR4 0.0418184 0.041722 0.0452352 0.0443856 0.04329 0.00179
UR3 0.0423088 0.0455981 0.0428707 0.0426612 0.04336 0.00151
UR2 0.0794338 0.0724405 0.0766334 0.076393 0.076225 0.002876
UR1 0.063615 0.0629132 0.0722933 0.0626052 0.065357 0.004644
UL6 0.216667 0.197246 0.237714 0.215903 0.216883 0.016538
UL5 0.0498135 0.0490184 0.0413538 0.0378587 0.044511 0.00585
UL4 0.0287049 0.0282162 0.0503425 0.0454121 0.038169 0.011391
UL3 0.0593452 0.0585977 0.0716752 0.0663891 0.064002 0.006204
UL2 0.0642813 0.0643059 0.0691766 0.0697719 0.066884 0.003001
UL1 0.0368608 0.0357477 0.0420373 0.0378044 0.038113 0.002748
M1, Operator 1 (measurement 1); M2, Operator 1 (measurement 2); M3, Operator 2
(measurement 1); M4, Operator 2 (measurement 2); AVG, average; SD, standard deviation

Table XVI. RMS values of virtual bracket removal using Meshmixer™.
Model Tooth M1 M2 M3 M4 AVG SD
01
UR6 0.0752325 0.0769567 0.0706851 0.0678234 0.072674 0.004178
UR5 0.154187 0.168143 0.160766 0.149408 0.158126 0.008141
UR4 0.134465 0.133252 0.105329 0.0902629 0.115827 0.021716
UR3 0.0349897 0.0374295 0.0417879 0.0371056 0.037828 0.002853
UR2 0.0275186 0.0261415 0.0346869 0.0295473 0.029474 0.003747
UR1 0.0339679 0.0335219 0.0291716 0.0289547 0.031404 0.002711
UL6 0.0708655 0.0679005 0.0702707 0.0655749 0.068653 0.002419
UL5 0.146131 0.156422 0.141062 0.135978 0.144898 0.008729
Assessment of 3D surface changes following virtual bracket removal | 54

UL4 0.115094 0.121257 0.0740745 0.0738144 0.09606 0.025661
UL3 0.0615496 0.0648182 0.06048 0.0590179 0.061466 0.002464
UL2 0.0368727 0.0349509 0.0362462 0.0373434 0.036353 0.001037
UL1 0.0203678 0.0239823 0.0270113 0.0241628 0.023881 0.002722
02
UR6 0.170904 0.194144 0.139472 0.116795 0.155329 0.034086
UR5 0.0624071 0.0587177 0.103018 0.100148 0.081073 0.02376
UR4 0.0287522 0.0294262 0.0583927 0.0526057 0.042294 0.015432
UR3 0.0419727 0.0468411 0.0268593 0.0260554 0.035432 0.010557
UR2 0.0641246 0.0671192 0.053248 0.0526921 0.059296 0.00741
UR1 0.0588104 0.0620276 0.0513363 0.0452682 0.054361 0.007537
UL6 0.0743571 0.0857869 0.0959642 0.0829911 0.084775 0.008906
UL5 0.0837804 0.0864096 0.105074 0.107715 0.095745 0.012391
UL4 0.0977028 0.0884035 0.0643984 0.063187 0.078423 0.017322
UL3 0.0588741 0.0607715 0.0645838 0.0605958 0.061206 0.002409
UL2 0.0460593 0.0458293 0.0412132 0.0419282 0.043758 0.002544
UL1 0.0472255 0.049485 0.0591304 0.0524217 0.052066 0.005168
03
UR6 0.110695 0.0986488 0.086525 0.0862407 0.095527 0.011649
UR5 0.0700698 0.0640823 0.0685633 0.0652509 0.066992 0.002795
UR4 0.0645131 0.059891 0.0709561 0.0644563 0.064954 0.00455
UR3 0.0580885 0.0588469 0.064145 0.0593771 0.060114 0.002739
UR2 0.0731659 0.0779261 0.0703748 0.0666628 0.072032 0.004747
UR1 0.054137 0.051637 0.0422423 0.0408458 0.047216 0.006652
UL6 0.1033 0.102963 0.137858 0.10751 0.112908 0.016762
UL5 0.0677579 0.0665511 0.0976492 0.0755564 0.076879 0.014411
UL4 0.114112 0.112874 0.139575 0.110423 0.119246 0.013639
UL3 0.0597683 0.0569613 0.0562248 0.0504349 0.055847 0.003918
UL2 0.090162 0.0396778 0.0374991 0.0376631 0.051251 0.02596
UL1 0.0311296 0.027597 0.0302912 0.0294047 0.029606 0.001513
04
UR6 0.185571 0.185236 0.189334 0.173658 0.18345 0.006787
UR5 0.044214 0.0399495 0.0384827 0.0368806 0.039882 0.003148
UR4 0.034514 0.0363357 0.0384393 0.0400216 0.037328 0.002408
UR3 0.0160452 0.0159985 0.023479 0.0239219 0.019861 0.004437
UR2 0.025505 0.0258043 0.0323697 0.0317381 0.028854 0.003706
UR1 0.0338736 0.0343275 0.030946 0.0310947 0.03256 0.001789
UL6 0.196563 0.181871 0.190422 0.187156 0.189003 0.006149
UL5 0.0506598 0.050001 0.0548982 0.0544706 0.052507 0.002534
UL4 0.0316101 0.0354686 0.0373067 0.0427579 0.036786 0.004635
UL3 0.0403181 0.0396269 0.0252804 0.0264897 0.032929 0.008153
UL2 0.0411608 0.0419661 0.0435003 0.0433298 0.042489 0.001121
UL1 0.0278283 0.0275174 0.0242093 0.0226278 0.025546 0.002543
05
UR6 0.15403 0.179742 0.190209 0.190763 0.178686 0.017201
UR5 0.0872309 0.0939772 0.135922 0.13606 0.113298 0.026349
UR4 0.133706 0.139073 0.158724 0.159822 0.147831 0.0134
UR3 0.093922 0.0921804 0.0835416 0.0861505 0.088949 0.004907
UR2 0.026878 0.0301307 0.0290787 0.0327026 0.029698 0.002419
Assessment of 3D surface changes following virtual bracket removal | 55

UR1 0.044999 0.0476872 0.0494943 0.0413902 0.045893 0.003524
UL6 0.211052 0.269961 0.243559 0.271181 0.248938 0.02829
UL5 0.0555274 0.0598812 0.0394088 0.0397905 0.048652 0.010604
UL4 0.0530802 0.0554068 0.0583493 0.0554378 0.055569 0.002158
UL3 0.0213908 0.0223239 0.022449 0.0223698 0.022133 0.000498
UL2 0.0464722 0.0463316 0.0657053 0.0664142 0.056231 0.011353
UL1 0.0579273 0.0604072 0.143284 0.119379 0.095249 0.042804
06
UR6 0.0862451 0.0828085 0.0937612 0.100067 0.09072 0.007729
UR5 0.102789 0.0984045 0.103082 0.102085 0.10159 0.002165
UR4 0.085591 0.0777993 0.0671668 0.0688373 0.074849 0.008549
UR3 0.0295139 0.0280368 0.0326173 0.0334459 0.030903 0.002553
UR2 0.0404168 0.0419942 0.0341879 0.0332666 0.037466 0.004382
UR1 0.0444878 0.044586 0.0375737 0.033829 0.040119 0.005326
UL6 0.0892548 0.0923696 0.107539 0.102438 0.0979 0.008541
UL5 0.057579 0.0612329 0.0785629 0.0743297 0.067926 0.0101
UL4 0.0481038 0.0932308 0.054754 0.0516733 0.06194 0.021036
UL3 0.0209307 0.0207873 0.0325345 0.0324285 0.02667 0.006711
UL2 0.0256408 0.0299487 0.0319813 0.0346211 0.030548 0.00379
UL1 0.0682715 0.0900363 0.0901243 0.0841836 0.083154 0.010304
07
UR6 0.191002 0.192468 0.21734 0.197603 0.199603 0.012158
UR5 0.0587033 0.0548624 0.0520683 0.0539023 0.054884 0.002798
UR4 0.0910269 0.0899046 0.0846954 0.0841367 0.087441 0.00353
UR3 0.0966812 0.0940758 0.0787812 0.0789476 0.087121 0.009594
UR2 0.0607132 0.062513 0.061944 0.0599072 0.061269 0.001178
UR1 0.0306313 0.0324064 0.0380144 0.0339514 0.033751 0.003149
UL6 0.191743 0.202638 0.20355 0.188745 0.196669 0.007528
UL5 0.0414334 0.0425914 0.0604676 0.0619896 0.051621 0.011122
UL4 0.0401128 0.0405045 0.050293 0.0491452 0.045014 0.005456
UL3 0.0355092 0.034815 0.0352168 0.030957 0.034125 0.002131
UL2 0.0313129 0.0335428 0.0487514 0.0454948 0.039775 0.008636
UL1 0.0494196 0.0512077 0.0653566 0.059877 0.056465 0.007483
08
UR6 0.243339 0.236316 0.224298 0.227181 0.232784 0.008704
UR5 0.0363878 0.0352205 0.0343365 0.0349109 0.035214 0.000864
UR4 0.0722764 0.0676582 0.0627766 0.0584283 0.065285 0.005995
UR3 0.061958 0.0626267 0.0534048 0.0531425 0.057783 0.005215
UR2 0.0329487 0.0339827 0.0651687 0.0589913 0.047773 0.016717
UR1 0.0411768 0.0437098 0.0366631 0.0363419 0.039473 0.003585
UL6 0.205882 0.202356 0.188539 0.17377 0.192637 0.014636
UL5 0.0527578 0.0459952 0.0311194 0.0289981 0.039718 0.011522
UL4 0.0274859 0.0259396 0.0239717 0.0235294 0.025232 0.001832
UL3 0.0456053 0.0450251 0.0624791 0.0619419 0.053763 0.00976
UL2 0.0874165 0.0798406 0.0748981 0.0743003 0.079114 0.006066
UL1 0.0702486 0.0736288 0.112447 0.112771 0.092274 0.023522
09
UR6 0.166655 0.184523 0.15917 0.175769 0.171529 0.011005
UR5 0.0450416 0.0456305 0.0418178 0.0412532 0.043436 0.002219
Assessment of 3D surface changes following virtual bracket removal | 56

UR4 0.029428 0.0275485 0.0288317 0.0298762 0.028921 0.00101
UR3 0.0383422 0.0340074 0.0507737 0.0554646 0.044647 0.010124
UR2 0.0382022 0.0391184 0.0413109 0.0411116 0.039936 0.001522
UR1 0.0604641 0.0616475 0.0638248 0.0637198 0.062414 0.001642
UL6 0.16537 0.168963 0.148872 0.147506 0.157678 0.011068
UL5 0.037549 0.0405744 0.0283839 0.0268526 0.03334 0.00675
UL4 0.0297354 0.0323944 0.0594605 0.0542035 0.043948 0.01507
UL3 0.0538305 0.0591507 0.0611346 0.0560046 0.05753 0.003247
UL2 0.0615907 0.0605807 0.0627973 0.0592466 0.061054 0.001508
UL1 0.0326896 0.0343246 0.0313032 0.0318834 0.03255 0.001312
M1, Operator 1 (measurement 1); M2, Operator 1 (measurement 2); M3, Operator 2
(measurement 1); M4, Operator 2 (measurement 2); AVG, average; SD, standard deviation

Abstract (if available)

Abstract Introduction: Computer‐aided design and manufacturing of orthodontic retainers from digitally debonded models can be used to facilitate same‐day delivery. The purpose of this study was to 1) establish reliable virtual bracket removal (VBR) techniques using two 3D modeling software programs and 2) assess their accuracy and reproducibility. ❧ Methods: The sample consisted of nine 3D‐printed maxillary models that were digitized with an intraoral scanner for use as a control group. The control models were bonded with labial brackets and scanned. VBR was performed using Ortho Analyzer™ (3Shape A/S, Copenhagen, Denmark) and Meshmixer™ (Autodesk, San Rafael, CA). The virtually debonded models were superimposed onto the control models, and 3D Euclidean distances between surface points of the superimposed models were calculated for comparative analysis of surface changes due to VBR. Linear surface changes were expressed via color mapping. ❧ Results: Intra‐ and inter‐operator reliability were determined to be high (> 0.9). The accuracy of VBR did not differ significantly between software programs. However, statistically significant differences (P < 0.05) were detected between three tooth segments (incisors, canines/premolars, and first molars), with VBR in the posterior segments showing the least accuracy. ❧ Conclusions: VBR is accurate and reproducible when using the protocols established in this study. Moreover, VBR using Ortho Analyzer™ and Meshmixer™ is comparable and facilitates computer‐aided design and manufacture of retainers.

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

3D assessment of virtual bracket removal for modern orthodontic retainers: a prospective clinical study

PDF

An assessment of orthognathic surgery outcomes utilizing virtual surgical planning and a patented full-coverage 3D-printed orthognathic splint

PDF

3D ssessment of bracket position accuracy for lingual appliances using CAD/CAM technology: a pilot study

PDF

An evaluation of bond strength using sham lingual brackets with differences in base morphology and preparation

PDF

Shear bond strength comparison of mesh, sandblasted and laser-etched orthodontic brackets

PDF

Comparison of HLD CAL-MOD scores obtained from digital versus plaster models

PDF

The creation of a novel full-coverage orthognathic surgical splint utilizing 3D printing & virtual surgical planning

PDF

Bonding accuracy of a novel lingual customized orthodontic appliance (INBRACE™): an in-vivo study

PDF

An overview of the dental and skeletal relationships in individuals of Vietnamese ancestry

PDF

Monitering of typodont root movement via crown superimposition of single CBCT and consecutive iTero scans

PDF

The accuracy of intraoral scans of interproximal spaces with and without saliva: a prospective clinical study

PDF

Cirtual 3D placement of temporary orthodontic anchorage implants

PDF

Classification of 3D maxillary incisor root shape

PDF

Use of digital models to assess orthodontic treatment progress and identify deficiencies

PDF

Overbite correction with fully customized lingual appliances

PDF

The reliability of simultaneous quantitative 3D analysis of bone and soft tissue volumes

PDF

Prevalence of TMJ morphological changes and scoring system based on CBCT imaging

PDF

Orthodontic rotational relapse: prevalence and prevention

PDF

Detrimental effects of dental encroachment on secondary alveolar bone graft outcomes in the treatment of patients with cleft lip and palate: a cone-beam computed tomography study

PDF

Comparison of facial midline landmark and condylar position changes following orthognathic surgery

Asset Metadata

Creator Chamberlain-Umanoff, Alexandra (author)

Core Title Assessment of 3D surface changes following virtual bracket removal

School School of Dentistry

Degree Master of Science

Degree Program Craniofacial Biology

Publication Date 04/24/2019

Defense Date 02/22/2019

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

Tag digital artifact removal,digital bracket removal,OAI-PMH Harvest,virtual artifact removal,virtual bracket removal

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Sameshima, Glenn (committee chair), Grauer, Dan (committee member), Yen, Steve (committee member)

Creator Email alexanmc@usc.edu,chamberlainsmiles@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-141959

Unique identifier UC11675388

Identifier etd-Chamberlai-7230.pdf (filename),usctheses-c89-141959 (legacy record id)

Legacy Identifier etd-Chamberlai-7230.pdf

Dmrecord 141959

Document Type Thesis

Format application/pdf (imt)

Rights Chamberlain-Umanoff, Alexandra

Type texts

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

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

Repository Name University of Southern California Digital Library

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