comparison of digital treatment setups and final treatment

UNLV Theses, Dissertations, Professional Papers, and Capstones

5-1-2020

Comparison of Digital Treatment Setups and Final Treatment Comparison of Digital Treatment Setups and Final Treatment

Outcomes of Class II Division 1 Malocclusions Treated with Outcomes of Class II Division 1 Malocclusions Treated with

Premolar Extractions Premolar Extractions

Sogol Shantiyai

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COMPARISON OF DIGITAL TREATMENT SETUPS AND FINAL

TREATMENT OUTCOMES OF CLASS II DIVISION 1

MALOCCLUSIONS TREATED WITH

PREMOLAR EXTRACTIONS

By

Sogol Shantiyai

Bachelor of Science - Biology San Diego State University

2012

Doctor of Dental Medicine Midwestern University College of Dental Medicine

2016

A thesis submitted in partial fulfillment of the requirements for the

Master of Science – Oral Biology

School of Dental Medicine

The Graduate College

University of Nevada, Las Vegas May 2020

ii

Thesis Approval

The Graduate College The University of Nevada, Las Vegas

March 10, 2020

This thesis prepared by

Sogol Shantiyai

entitled

Comparison of Digital Treatment Setups and Final Treatment Outcomes of Class II Division 1 Malocclusions Treated with Premolar Extractions

is approved in partial fulfillment of the requirements for the degree of

Master of Science – Oral Biology School of Dental Medicine

Kathryn Hausbeck Korgan, Ph.D. Graduate College Dean

Tanya Al-Talib, D.D.S. Examination Committee Chair

Brian Chrzan, Ph.D. Examination Committee Member

Robert Danforth, D.D.S. Examination Committee Member

Amei Amei, Ph.D. Graduate College Faculty Representative

iii

Abstract

Objective: This study aimed to determine whether there are differences between pre-orthodontic

treatment dimensions when compared to the virtual treatment simulations and actual orthodontic

treatment outcomes in Class II malocclusions treated with two or four premolar extractions.

Introduction: The use of intraoral scanners has become commonplace in orthodontic practices,

giving practitioners the ability to scan and assess maxillary and mandibular dental morphology

and occlusal relationships chairside and in real-time. Practitioners can use virtual treatment

planning to evaluate different extraction patterns, visualize potential non-extraction outcomes

using interproximal reduction, and alter anchorage strategies based on the amount of retraction or

protraction required for desired space closure. Similar to the dental Visualized Treatment

Objective (VTO), digital treatment projections allow the clinician to both visualize and quantify

the degree and direction of tooth movement desired.

Materials and Methods: 46 Class II division 1 patients were selected for this study: 22 subjects

treated with two maxillary premolar extractions, 24 treated with four premolar extractions.

Patients were selected based on presentation of Angle Class II malocclusion, confirmed with

evaluation of digital study models. All digital treatment projections were constructed using uLab

Systems (uLab Systems Inc. Redwood City, CA), and measurements for intermolar width, inter-

canine width, overjet and overbite were recorded.

Results: Two-tailed paired T-tests were performed to determine if there was a significant

difference between variables pre-treatment, post-treatment and from virtual setup with a

significance level of P < 0.05. Group 1 treated with two premolar extractions resulted in a

iv

significant difference between maxillary intercanine width, mandibular intercanine width, and

overbite between uLab virtual setup and treatment groups. Group 2 treated with four premolar

extractions found significant differences between maxillary intermolar width, maxillary and

mandibular intercanine widths, and overjet between treatment and virtual setup groups. There

was a significant difference for all variables measured when comparing pre-treatment

measurements to virtual setups treated with two premolar extractions. When comparing pre-

treatment to virtual setups treated with four premolar extractions, there was a significant

difference in all variables except overbite. Comparison of pre-treatment to post-treatment values

treated with two premolar extractions found significant difference between maxillary and

mandibular intermolar width, maxillary intercanine width, overjet and overbite. There was a

significant difference between pre- and post-treatment in maxillary intermolar width, mandibular

intermolar width, and overjet treated with four extractions.

Conclusions: Despite statistically significant differences between treatment outcomes and virtual

setups in variables including overbite and overjet, the difference between them was not clinically

significant. Statistically significant differences in both the maxillary and mandibular intercanine

widths between digital setups and treatment outcomes suggests that with software simulations,

the clinician tends to over-expand the intercanine width. Similarly, virtual setups showed a

tendency to expand intercanine dimensions more than actual treatment outcomes when

comparing to initial pre-treatment dimensions. This study supports the use of virtual setups for

the purpose of guiding treatment and visualizing potential outcomes.

v

Acknowledgements

I wish to express my gratitude to my committee chair, Dr. Tanya Al-Talib, for her

guidance throughout this project. Above all, I am sincerely thankful for the unwavering love and

support from my family and the love of my life.

vi

Table of Contents

Abstract .................................................................................................................................... iii Acknowledgements ..................................................................................................................... v

Table of Contents ....................................................................................................................... vi List of Tables ............................................................................................................................ vii

List of Figures ..........................................................................................................................viii Chapter 1: Introduction ............................................................................................................... 1

Chapter 2: Materials and Methods ............................................................................................... 3 uLab Virtual Setup Protocol .................................................................................................... 4

Digital Measurement Protocol ................................................................................................. 8 Statistical Analysis ................................................................................................................ 11

Chapter 3: Literature Review .................................................................................................... 12 Chapter 3: Results ..................................................................................................................... 26

Intra-observer Error Rate....................................................................................................... 31 Chapter 4: Discussion ............................................................................................................... 32

Limitations and Future Studies .............................................................................................. 36 Conclusions .......................................................................................................................... 36

Appendix A: Data Results ......................................................................................................... 38 Appendix B: Graphs ................................................................................................................. 42

Appendix C: Statistical Analysis Tables .................................................................................... 43 Appendix D: Reliability Studies ................................................................................................ 49

Appendix E: IRB Exemption .................................................................................................... 54 References ................................................................................................................................ 55

Curriculum Vitae ...................................................................................................................... 62

vii

List of Tables Table 1. Paired sample statistics of treatment and setup groups with two premolar extractions .. 26 Table 2. Paired sample statistics of treatment and setup groups with four premolar extractions . 27 Table 3. Paired sample statistics of pre-treatment and setup groups ........................................... 28 Table 4. Paired sample statistics of pre-treatment and treatment groups..................................... 29 Table 5. Intra-observer reliability with Intraclass Correlation Coefficient (n=40) ...................... 31

viii

List of Figures Figure 1. STL Model................................................................................................................... 4

Figure 2 Tooth segmentation ....................................................................................................... 5

Figure 3. Labeling dentition ........................................................................................................ 5

Figure 4-1 and 4-2. Tooth orientation .......................................................................................... 6

Figure 5-1 and 5-2. Virtual setup alignment ................................................................................ 6

Figure 6. Space Closure .............................................................................................................. 7

Figure 7. Occlusal interferences .................................................................................................. 7

Figure 8. Final Occlusion ............................................................................................................ 8

Figure 9. Intermolar width measurement ..................................................................................... 8

Figure 10. Intercanine width measurement .................................................................................. 9

Figure 11. Overjet and Overbite orientation ................................................................................ 9

Figure 12. Overbite and overjet measurements .......................................................................... 10

1

Chapter 1: Introduction

The use of intraoral scanners has become commonplace in orthodontic practices, often

praised by patients for eliminating the need for conventional diagnostic impressions. Digital

scans have the ability to improve efficiency of patient appointments by removing time-

consuming steps including tray selection, alginate impressions, bite registrations, disinfection, as

well as the accompanying laboratory procedures of pouring, trimming and storage of dental

casts. The potential complication of distortion associated with conventional impressions is also

eliminated. By removing the need for plaster cast production, the orthodontist has the ability to

scan and assess maxillary and mandibular dental morphology and occlusal relationships

chairside and in real-time.

The benefits of both digital or plaster study models in diagnosis and treatment planning

include the ability to collect useful information about general alignment, occlusion, arch width

(Hechler, 2008), arch length discrepancies, dental asymmetries, and mesiodistal dimensions of

the dentition (Camardella, Rothier, Vilella, Ongkosuwito, & Breuning, 2016). Recent

technological advancements allow practitioners to evaluate and manipulate digital models

chairside, setting teeth into their desired position and facilitating in-house aligner fabrication.

While digital projections may encourage patients to start treatment by providing a visualization

of potential treatment outcomes, the main goal should remain to give the orthodontist a realistic

view of how treatment will finish (Barreto, Faber, Vogel, & Araujo, 2016). Practitioners can use

virtual treatment planning to evaluate different extraction patterns, visualize potential non-

extraction outcomes using interproximal reduction, and alter anchorage strategies based on the

amount of retraction or protraction required for desired space closure. Similar to the dental

Visualized Treatment Objective (VTO) developed by McLaughlin and Bennet in 1971, digital

2

treatment projections allow the clinician to both visualize and quantify the degree and direction

of tooth movement desired. While the dental VTO is widely accepted as a helpful diagnostic aid,

it is limited by providing a two-dimensional (2D) analysis of three-dimensional (3D) structures.

For years, 3D virtual surgical planning has been used for orthognathic surgeries; allowing

maxillofacial surgeons to diagnose, plan surgical procedures and predict postoperative outcomes

(Tran et al., 2018). There are few published literatures regarding the accuracy of 3D treatment

planning and outcomes in orthodontic treatment alone. This study aims to investigate the

accuracy and reliability of digital treatment projections when compared to final outcomes for

patients with Class II division 1 malocclusions treated with either two and four premolar

extractions using edgewise orthodontic appliances. Further evaluation comparing pre-treatment

measures to setup and post-treatment outcomes were carried out to determine whether there were

significant changes and whether there are potential implications on long-term stability. The

information and knowledge gained from this retrospective study supports the use of virtual

treatment projections in daily practice to aid in treatment planning and visualizing possible

treatment outcomes.

3

Chapter 2: Materials and Methods

Approval to conduct this study was received by the University of Nevada, Las Vegas

Institutional Review Board (Protocol # 1280536). A retrospective study of Class II division 1

orthodontic patients treated at the UNLV School of Dental Medicine’s Orthodontic Residency

Program were studied.

Sample

Patients were selected based on presentation of Angle Class II malocclusion; defined as

the mesio-buccal cusp of the maxillary first molar occluding anterior to the buccal groove of the

mandibular first molar. Molar classification was confirmed with intraoral photos and evaluation

of digital study models. 46 patients were selected: 22 subjects treated with two maxillary

premolar extractions, 24 treated with four premolar extractions (14 maxillary first, mandibular

second premolars; 10 maxillary first, mandibular first premolars).

Case selection was based on the following criteria: (1) periodontally healthy subjects with

full permanent dentition, (2) patient received orthodontic treatment using edgewise technique (22

slot) with extraction of two or four premolars (maxillary first or second premolars only;

maxillary and mandibular first premolars; or maxillary first and mandibular second premolars),

(3) OrthoCad or 3Shape Trios digital models pre- and post-treatment available for each patient in

STL file format, (4) no supernumerary or impacted teeth (not including third molars), (5) pre-

treatment orthodontic records including intraoral photos, panoramic and cephalometric

radiographs available. The exclusion criteria included patients with congenital anomalies,

patients with missing permanent teeth, and any orthognathic surgical case.

Access was granted to the patient’s pre-treatment photographs, panoramic and

cephalometric radiographs (Dolphin Imaging, Chatsworth, CA). These diagnostic tools provided

4

information regarding whether the patient has a consonant or non-consonant smile arc, amount of

incisal and gingival display, and soft tissue considerations which were incorporated into the

patient’s digital treatment projection. Cephalometric data, including labially inclined maxillary

and mandibular incisors often seen in Class II division 1 cases were incorporated into treatment

projection when deciding the amount of retraction and incisor uprighting desired.

All digital treatment projections were constructed using uLab Systems Software

(Redwood City, CA). Pre-treatment, post-treatment and STL files from virtual setups were de-

identified by an independent researcher and digital measurements completed using uLab

software. The following linear measurements were then recorded: intermolar width, inter-canine

width, overjet and overbite.

uLab Virtual Setup Protocol

Figure 1. STL Model

Open shell STL model of pre-treatment arch-forms were uploaded into uLab Systems Software.

5

Figure 2. Tooth segmentation

Individual teeth, not including third molars, were segmented.

Figure 3. Labeling dentition

Teeth to be extracted were selected to reflect the actual treatment each patient received. Patients

were either treated with extraction of two maxillary first premolars, four first premolars, or

maxillary first and mandibular second premolars.

6

Figure 4-1 and 4-2. Tooth orientation

Mesio-distal and inciso-gingival orientation of each tooth were adjusted as needed.

Figure 5-1 and 5-2. Virtual setup alignment

Desired maxillary and mandibular incisor positions were determined based on pre-treatment

diagnostic records. Projected position of incisors used intraoral photos to determine amount of

incisal display and desired smile arc. Panoramic radiographs influenced inclination of dentition

for improved projected root parallelism. Extraoral and intraoral photographs, and cephalometric

radiographs helped determine the amount of retraction and uprighting of anterior dentition.

7

Figure 6. Space Closure

Reciprocal space closure was used to protract posterior dentition when indicated.

Figure 7. Occlusal interferences

Red markings on teeth indicate areas of heavy occlusion or occlusal interferences. Yellow

indicates moderate contact and green indicates light (ideal) contact.

8

Figure 8. Final Occlusion

Final occlusion in both arches were evaluated and adjusted as needed to confirm Class I molar

and canine relationships were achieved (in four premolar extraction cases), as well as ideal

overjet, overbite and inclination of dentition.

Digital Measurement Protocol

Figure 9. Intermolar width measurement

Intermolar width measured as the distance between the center of the occlusal surface of first

molars

9

Figure 10. Intercanine width measurement

Intercanine width was measured from cusp tip of contralateral canines.

Figure 11. Overjet and Overbite orientation

Final overjet was measured using uLab software from the center of the incisal edge of the

maxillary right central incisor to the center incisal edge of the mandibular right central incisor.

10

Figure 12. Overbite and overjet measurements

Final overbite measured by the uLab software as the vertical overlap from the incisal edge center

of the right maxillary central incisor to incisal edge of the mandibular incisor

11

Statistical Analysis

Statistical analysis was performed using Statistical Package for the Social Sciences 24

(SPSS 24) for Windows. All measurements were completed under the same setting using uLab

Systems Software. Descriptive statistics were used to calculate the mean values for each variable

measured (intermolar width, intercanine width, overjet, overbite). Paired T-tests were performed

with a 95% confidence interval to determine whether there was a statistically significant

difference between pre-treatment, post-treatment and virtual setup for each variable. A P-value

of <0.05 was defined as significant.

Intra-observer error was calculated using an Intraclass Correlation Coefficient (ICC). ICC

was based on repeated measurements on 40 randomly selected patients using the same viewing

conditions, with a three-month interval between scoring sessions (Table 5). A Bland-Altman plot

was used to visualize the difference in agreement between readings (Appendix D).

12

Chapter 3: Literature Review

3-Dimensional Scanners

In the 1990’s, the introduction of three-dimensional (3D) scanning software allowed

conventional study models to be converted to a digital format (Alcan, Ceylanoǧlu, & Baysal,

2009). Companies offering these services, such as OrthoCad (Cadent Inc.), receive polyvinyl

siloxane (PVS) or alginate impressions with bite registrations which are then digitized using a

3D surface model scanner. With an indirect digitization system like OrthoCad, potential for error

or distortions is increased because it is a two-step procedure (Alcan et al., 2009). The first step

involving converting the alginate impression to stone, the second taking multiple scans of the

stone model in thin slices which are stitched together to create a digitized product (Fleming,

Marinho, & Johal, 2011). Distortion of alginates can occur through evaporation, or syneresis of

water, causing contraction of the material or inversely alginates can expand through absorption

of moisture, or imbibition (Alcan et al., 2009). It has been suggested that the best method to

avoid distortion of alginate is to pour in stone within ten minutes of the impression (Skinner &

Pomes, 1946). Industrial grade scanners have become available with the ability used to scan

impressions directly (Kuo & Miller, 2003) and reduce time for distortion to occur.

Over the years, various scanning techniques have become available for digitizing models.

Laser scanners reflect a laser light from the surface of the stone model which is then captured by

an optical sensor (Kuo & Miller, 2003). While this system is comparatively inexpensive, it is

limited by its lower resolution and slow scanning time. White-light scanners use the same

mechanism as a laser scan, however white-light is reflected from the model which improves the

quality of the scan in a shorter amount of time. Destructive scanners encase a model with

urethane resin, thinly slices into layers and then scans. This process is more accurate than a laser

13

scan, however it destroys the model during the scanning process. Lastly, CT scans use digital

radiographs to produce models with great accuracy. These scanners can directly scan

impressions, bite registration material and stone models and are considered to be the most

accurate and least time consuming technology (Kuo & Miller, 2003).

A study by Wesemman et al. (2017) comparing accuracy of desktop surface scanners to

intraoral scanners found the R900 desktop scanner to have superior results to others tested. They

recommend that if the model is intended to be used for full-arch prosthodontic purposes, indirect

digitization using a desktop scanner is superior. However, for orthodontic purposes, they found

that direct digitization using intraoral scanners like the 3Shape Trios system offered an

acceptable alternative with comparable results. The generally accepted accuracy of 0.1mm is

considered adequate enough to not compromise the diagnostic value of the model (Hayashi et al.,

2013).

When measuring Bolton discrepancy, Tomasetti (2001) found no significant difference in

measurements completed digitally or using a caliper and plaster study models. Garino and

Garinocit (Garino & Garino, 2002) found that despite significant differences in linear

measurements when comparing manual and digital study models, the results were clinically

insignificant. In agreement, a systematic review by Fleming et al. (2011) comparing

measurements made on digital and stone models found the mean difference to be minor and

clinically insignificant. It is suggested that digital models are superior to stone when measuring

the Curve of Spee, as an antero-posterior line and vertical line to the deepest point of occlusion

can both be drawn on the software (Garino & Garino, 2002).

Recent technologic advancements have allowed for the production of digital models

using cone beam CT (CBCT) data without the need of impressions or scans. CBCT data can

14

create 3D renderings with or without the presence of anatomic roots (Hechler, 2008). These 3D-

models can then be examined with a conventional or transparent model base which offers

enhanced visualization of the dental crown and associated root morphology (Mah, 2007). With

the inclusion of detailed anatomical structures, the practitioner has more information in planning

treatment. These include the position of lingual cortical plates when determining whether to

retract or torque incisors, root proximity to the maxillary sinus, and amount of bone present

during space closure (Macchi, Carrafiello, Cacciafesta, & Norcini, 2006).

Virtual Treatment Planning in Orthodontics

The traditional approach of using stone models to create a treatment setup can now be

done virtually using 3D software. A study by Barreto et al. (2016) comparing manual and digital

setups for treatment planning found no significant difference between the two modalities when

measuring intercanine and intermolar widths, as well as the length of the individual dental

arches.

Digital setups provide the practitioner an idea of how the treatment will finish (Barreto et

al., 2016), while also providing a visualization for both patients and parents in understanding

treatment goals and potential outcomes. In borderline cases, these setups can help guide

treatment when deciding whether extractions are indicated. Additionally, various treatment

options with regards to anchorage considerations can be explored and compared during the

decision-making process.

Laboratory time required for stone model setup is often lengthy as it involves the

trimming of individual crowns and repositioning with wax to stabilize. As per Camardella et

al.(2016), a major disadvantage of this method was the inability to superimpose structures as

15

well as the inadvertent loss of tooth structure during the trimming and repositioning process.

With 3D software, tooth movements can be superimposed from their initial position to visualize

the direction and degree of desired tooth movement; illustrated by different colors that indicate

the initial and final tooth position. Additionally, digital setups require significantly less doctor

and staff time while also reducing physical storage requirements (Barreto et al., 2016).

Treatment of Class II Malocclusions

A commonly accepted treatment goal in orthodontics is to position the dentition in a way

that provides good facial esthetics while also in functional occlusion (Braun, 1999). Careful

analysis must be made when deciding on an extraction or non-extraction treatment plan in

correction of a Class II malocclusion. Extraction-based treatment plans must take into

consideration many factors including (but not limited to) dental and lip protrusion, the severity of

tooth size-arch length discrepancies (Mendes, Janson, Zingaretti Junqueira-Mendes, & Garib,

2019), resolving anteroposterior discrepancies, and patient growth potential (Samir E. Bishara,

Hoppens, Jakobsen, & Kohout, 1988). Extraction of two maxillary premolars for treatment of

Class II malocclusion is indicated when the mandibular arch has no significant crowding or

cephalometric discrepancy (Mendes et al., 2019). These patients often present with excess

overjet or crowding in the maxillary arch. Four-premolar extraction treatment can be indicated in

cases of dental crowding with or without cephalometric discrepancy. Two-premolar extraction

treatment generally requires less time than both four-premolars and non-extraction cases as the

molar relationship is maintained in a full-cusp Class II molar relationship.

Vaden (Vaden & Kiser, 1996) found that in Class II malocclusion patients treated without

extraction, a downward and backward mandibular rotation can be expected. In cases where

16

extractions are indicated but are not done, resulting clockwise vertical changes can be considered

an undesirable treatment sequela. Maintaining the vertical dimension is an important factor in

long-term stability, as increasing it in the posterior region results in an increased lower anterior

facial height (LAFH). Arquob et al. (2011) found that increased LAFH in both male and female

Class II patients were perceived to be the least attractive when measuring profile attractiveness.

It has been suggested that for every 1 millimeter (mm) of vertical change posteriorly, a 1.3mm

increase in anterior face height can be expected (Merrifield, 1982). Therefore, in deciding

whether to extract premolars in Class II malocclusion cases, vertical relationships should be

carefully considered.

Non-extraction treatment in Class II patients must apply mechanics for Class II

correction, such as Class II elastics or functional appliances. With the use of intermaxillary

elastics, the practitioner must keep in mind potential side effects that include the loss of

mandibular anchorage, mandibular incisor proclination, maxillary incisor extrusion and

associated increased soft tissue exposure upon smiling (Janson, Sathler, Fernandes, Branco, &

De Freitas, 2013). The extrusion of mandibular posterior teeth and maxillary incisors with the

use of intermaxillary elastics contributes to the clockwise rotation of the mandible and occlusal

plane (Nelson, Hansen, & Hagg, 2000) resulting in primarily dentoalveolar correction of the

malocclusion (Janson et al., 2013).

Numerous studies have found significant differences in perception of profile

attractiveness between laypersons and dentists (Abu Arqoub & Al-Khateeb, 2011). Dentists

proved to have a greater ability to distinguish profile changes (Maple, Vig, Beck, Larsen, &

Shanker, 2005), while a layperson’s perception of attractiveness is influenced more by extrinsic

features including hair color, style, shape and size of the nose (Cochrane, Cunningham, & Hunt,

17

1999). Laypersons are generally more critical than dentists while rating attractiveness, likely due

to a focus on extrinsic characteristics; while dentists have more experience with facial analysis

and, therefore, are considered more tolerant in their rating of attractiveness.

Mendes et al.(2019) compared profile attractiveness in Class II division 1 malocclusion

patients treated with either non-extraction, two-premolar or four-premolar extractions.

Laypersons and orthodontists rated the post-treatment and long-term esthetics by evaluating

androgynous facial silhouettes of the treatment groups with other variables affecting perceived

attractiveness eliminated. These included extrinsic factors of make-up and hair styles, and

intrinsic factors of skin complexion, eyes and facial expressions (Wuerpel, 1931). Post-

treatment, they found that the two-premolar extraction group was rated to have a significantly

more attractive profile than the four-premolar extraction group (Mendes et al., 2019). The two-

extraction and non-extraction groups had no statistically significant differences. Profile

attractiveness was found to be significantly greater in the two-premolar extraction group long-

term. A study by Bishara et al. (1997) found that prior to orthodontic treatment, laypersons

perceived profiles with clinically acceptable occlusions without facial disharmony as more

favorable than untreated patients with a Class II malocclusion. Immediately following four-

premolar extraction treatment, laypersons perceived profiles of the extraction group to be more

favorable than non-extraction group; however, long-term, there was no significant difference in

perceived profile attractiveness. In agreement, Janson et al. (2016) found that there was no

significant difference in long-term facial attractiveness between two-extraction, four-extraction

and non-extraction treatment of Class II division 1 malocclusion patients.

Current research suggests that there is no single extraction or non-extraction approach to

treating Class II malocclusion cases that guarantees a better perception of post-treatment facial

18

esthetics. Many factors must be evaluated in guiding treatment decisions including the severity

of the malocclusion, profile considerations, overjet (Mendes et al., 2019), inclination of incisors,

degree of crowding, cephalometric values such as long or short facial height, steepness of the

mandibular plane, and the need for dental compensation (S. E. Bishara & Jakobsen, 1997).

Characteristics of Class II Malocclusion

Two major categories exist for the classification of Class II malocclusions; distinguished

primarily based on the inclination of the maxillary incisors. Class II division 1 malocclusions

were characterized by Edward Angle as having labially inclined maxillary incisors (Angle,

1907). These malocclusions typically present with an increased buccal overjet with or without

maxillary arch narrowing (S. E. Bishara, 2006). Alternatively, Class II division 2 malocclusions

presented with lingual or upright maxillary incisors, often with excessive overbites and minimal

overjet (Angle, 1907). This lingual axial inclination of maxillary incisors is believed to be

consistent with the inclination of tooth bud development and often a narrow labiolingual crown

width (S. E. Bishara, 2006). An exaggerated curve of Spee is not uncommon in Class 2 division

2 patients in addition to lower incisor extrusion with impingement on palatal tissues.

In 1953, Fisk and his colleagues (1953) defined Class II division 1 malocclusions as

having six morphologic variations: 1) Maxilla and teeth positioned anteriorly in relation to the

cranium, 2) Maxillary teeth positioned anteriorly in the bone, 3) Underdeveloped mandible, 4)

Normal sized mandible in a posterior position, 5) Mandibular teeth posteriorly positioned in the

bone, or 6) Any combination of the above mentioned.

Skeletal characteristics of Class II malocclusions can be observed in cephalometric

radiographs displaying an increased ANB angle and Wits Appraisal (S. E. Bishara, 2006). In

19

Class II division 1 malocclusions, studies suggest that the maxilla to cranial base relationship is

often within normal range, and that the increased ANB angles and facial convexity are the result

of a retrusive mandible and chin position (Drelich, 1948). These patients may present with a

shortened mandibular body length or steeper mandibular plane angles (Maj, Luzi, & Lucchese,

1960). Class II division 2 cephalometric relationships often present with a larger angle of

convexity like their Class 1 counterpart. This finding could be attributed to a more protrusive

maxilla in relation to the mandible, or retrognathic mandible in relation to a normally positioned

maxillary basal bone (Hedges, 1958). The most consistent cephalometric finding that

distinguishes a Class II division 2 malocclusion is the upright inclination of the maxillary central

incisors.

Eruption of permanent first molars is influenced by the relationship of the primary second

molars. Bishara et al. (1988) found that when the primary molar relationship is considered to be a

distal step, the permanent occlusion will result in a Class II malocclusion which will not self-

correct. In the cases where primary molars are in a flush terminal plane relationship, an estimated

44% of them will develop into a Class II malocclusion while the remaining 56% finish as a Class

I occlusion. Environmental factors such as the early loss of primary second molars can cause

mesial drifting of permanent teeth and contribute to a Class II malocclusion.

There is no single etiological factor contributing to development of a Class II

malocclusion (Smith, 1938). Class II cases with an increased overjet can present with the lower

lip resting between the maxillary and mandibular incisors or a tongue thrust between the anterior

dentition. These compensatory lip and tongue positions often occur during swallowing and can

exaggerate the malocclusion. Additionally, this persistent muscle activity can cause narrowing of

the palate, incisor protrusion, spacing and proclination over time (Samir E. Bishara et al., 1988).

20

These patients may also present with a hyperactive mentalis muscle, which can contribute to

lingual axial inclination of incisors, reduced vertical facial height and a lower lip curl. Added

factors including thumb or lip sucking, mouth breathing, or swallowing habits can all contribute

to a Class II profile (Smith, 1938).

Biomechanical Considerations in Anchorage Preparation

Orthodontic anchorage can be defined as the resistance to tooth movement (Burstone &

Choy, 2015), or more specifically by Cope (2005) as the “amount of allowed movement of the

reactive unit.” The method of anchorage employed by the practitioner is crucial in managing

space closure in extraction cases and producing successful treatment outcomes.

Biologic variables can influence anchorage values and vary greatly between individuals

and dentoalveolar sites. When force is applied to a tooth with a large root, the stress magnitude at

the surrounding periodontal ligament (PDL) will be less than the stress magnitude of the same

force applied to a smaller tooth (Burstone & Choy, 2015). Fewer osteoclasts will be attracted to

the area of compression stress of a larger tooth as the force is distributed over a greater surface

area, giving reason as to why a larger tooth, like a molar, can expect to have a greater anchorage

value than an incisor. Furthermore, inflammatory mediators that contribute to tooth movement

can vary between individuals. An individual with decreased vascularity will have limited

recruitment of biologic inflammatory mediators like prostaglandins, cytokines and growth

factors which can delay or reduce tooth movement. Rate of bone metabolism can be influenced

by age, nutritional deficiencies, function of the kidneys and thyroid, local pathologies, systemic

conditions, or drug consumption (Dudic, Giannopoulou, & Kiliaridis, 2013).

21

Among individuals, variations in bone morphology and turnover occur in the maxilla and

mandible and specific dentoalveolar sites (Burstone & Choy, 2015). Generally speaking, the

maxilla is comprised of thinner cortical plates and more porous bone, whereas the mandible has

thicker cortical plates and dense cancellous bone. Areas of decreased bone density present with a

decreased anchorage value; less bone removal is required of osteoclasts and tooth movement can

be accelerated at these sites. This anatomic variation allows teeth in the maxilla to be moved

with more ease than in the mandibular arch.

Marcotte (1990) classified three types of orthodontic anchorage: Type A, Type B and

Type C. Type A anchorage, also known as maximum anchorage, defines the anterior dentition as

the active unit and posterior dentition as reactive. In this anchorage system, the reactive unit

remains stationary while the anterior teeth are actively retracted. In Type B anchorage, both

anterior and posterior segments are active, resulting in reciprocal space closure toward the

midpoint between them. Type C anchorage is inverse of Type A anchorage; the posterior

segment is actively protracted while the anterior is reactive and remains stationary.

Numerous methods to achieve orthodontic anchorage have been developed throughout

history. The clinician must account for anchorage based on the amount and direction of desired

space closure. One of the simplest methods to increase anchorage during space closure is to

increase the number of teeth in that segment. If the second premolar and first molar are ligated as

an anchor unit, the anchorage ratio is roughly 1:1; resulting in reciprocal space closure (Burstone

& Choy, 2015). Theoretically, in reciprocal space closure, one can expect the space to be closed

with 50% anterior retraction and 50% posterior protraction (McLaughlin, Bennett, & Trevisi,

2001). In order to increase the anchorage value of the posterior, the second molar can be

included with the posterior segment, altering the ratio to nearly 1.6:1; resulting in more anterior

22

retraction and a decrease in anchorage loss from the posterior (Burstone & Choy, 2015). When

minimal anchorage is desired and a majority of the space is to be closed by protraction of the

posterior segments, it would be beneficial to extract a second premolar and refrain from bonding

the second molar during initial treatment (McLaughlin et al., 2001). This approach will result in

a greater anterior anchor unit, as the ratio competes two molars versus eight teeth positioned

anterior to the extraction space. Molar protraction can be aided with the use of elastic to apply a

continuous, light force to the tooth.

In cases where utilization of the extractions space is necessary to resolve crowding or

reduce excessive overjet, maximum anchorage may be required. In these scenarios it is important

to control mesial movement of the molar. Methods to control this includes the use of lab

fabricated appliances such as a trans-palatal arch (TPA), Nance appliance or a lower lingual

holding arch (LLHA). While a TPA can assist by de-rotating and up-righting molars, stabilizing

transverse arch dimensions, and maintaining space in mixed dentition, some studies suggest it

does not significantly maintain the anteroposterior position of the maxillary molar in cases of

anterior retraction (Zablocki, McNamara, Franchi, & Baccetti, 2008). In these scenarios,

alternative methods of anchorage should be applied. Extraoral traction using a headgear can be

employed as a method of skeletal or dental modification. Force applied to the headgear tube on a

molar band can result in either tipping or bodily movements dependent on the direction of force

relative to the center of resistance of that tooth. However, the use of headgear may prove

challenging as it relies solely on patient compliance. Studies suggest that in order for headgear to

produce desired outcomes, it must be worn continuously for 12 hours per day (Jacobson, 1979).

The use of temporary anchorage devices (TADs), also known as mini-implant, for

skeletal anchorage has become increasingly common in the practice of orthodontics. This

23

method provides “absolute anchorage” in cases where complete anchorage must be maintained.

The TAD can be incorporated using direct or indirect anchorage. Anchorage can be indirectly

reinforced by ligating a TPA from the molars to palatal TADs during anterior retraction. Leung

et al. (2008) found that in this indirect system, a small loss of anchorage ranging between 0.2mm

to 1.6mm occurs likely due to TPA deformation. Alternatively, anterior retraction using direct

anchorage can be applied at the bracket level to the TAD, or to vertical hooks attached directly to

the archwire. Vertical hooks apply force near the center of resistance of the tooth to produce

bodily movement of the segment. Everdi (2005) suggested that bodily movement during

retraction of the anterior segment results in more favorable tissue response than two-step

retraction which involves tipping teeth followed by them uprighting. The use of TADs is

beneficial as placement is quick and success with immediate loading has been proven (Chen,

Kyung, Zhao, & Yu, 2009). Success of their placement can be influenced by insertion technique,

design, bone quality and quantity. Marquezan (2014) determined that diameter of the TAD has

greater influence on primary stability than length, as well as placement in areas of increased

cortical bone thickness.

Stability Following Orthodontic Treatment

Long-term stability following orthodontic treatment can be influenced by various factors

including the severity of pre-treatment malocclusion, oral habits, muscular balance, periodontal

status and an increased lower inter-canine width post-treatment (Anuwongnukroh,

Dechkunakorn, kunakornporamut, & Tua-Ngam, 2017).

Numerous studies have been published regarding the effects of increased inter-canine

width on post-treatment stability. It has been noted that more relapse can be expected following

24

canine expansion (Anuwongnukroh et al., 2017); causing notable irregularities after retention.

When inter-canine width is reduced, greater stability can be expected with minimal relapse

(Canut & Arias, 1999).

In untreated patients, the inter-canine width can be expected to decrease with age

(Sinclair & Little, 1983). This change can be due to the constant constriction of perioral muscles

on the maxillary and mandibular arches. Similarly, in orthodontically treated patients, the inter-

canine measurement tends to decrease in width long-term; suggesting that there should be an

attempt to maintain initial arch dimensions and inter-canine width to support improved long-term

transverse stability after treatment (Anuwongnukroh et al., 2017).

Rotational relapse following orthodontic treatment is more prevalent in areas of light

contacts or incomplete correction of original rotations (Zachrisson, 1997). The clinician may

consider re-contouring small contacts between incisors while maintaining anatomic form to

produce larger areas of contact (Tuverson, 1980). The distal contact between mandibular lateral

incisors can also be positioned slightly facial to the mesial contact of mandibular canines to

reduce post-treatment relapse (Zachrisson, 1997).

De La Cruz et al. (1995) found that the greater the change to the initial arch form during

treatment, the greater post-retention change can be expected. Patient’s treated with rounded

maxillary arch forms tend to become more tapered following retention. Due to individual

variation, prefabricated arch forms cannot be expected to fit the dental arch of every patient and,

therefore, customization should be considered when preparing archwires (Felton, Sinclair, Jones,

& Alexander, 1987). While the practitioner may aim to maintain the pre-treatment arch forms,

the maxillary arch is often adapted for coordination with the mandibular arch (Zachrisson, 1997).

25

If the anterior dentition is too upright following deep bite correction, a greater tendency

for relapse back to a deep bite following treatment can be expected (Lewis, 1987). The final

position of the incisors and inter-incisal relationship plays an important role in post-treatment

stability in the vertical dimension.

26

Chapter 3: Results

In each sample group there were six variables measured: maxillary intermolar width,

mandibular intermolar width, maxillary intercanine width, mandibular intercanine width, overjet

and overbite. Patients were treated with either two maxillary premolar extractions (N=22), or

four premolar extractions (N=24). Two-tailed paired T-tests were performed to determine if there

was a significant difference between variables pre-treatment, post-treatment and from virtual

setup with a significance level of P < 0.05. See Appendix C for complete statistical analysis

results.

GROUP 1

Paired Samples Statistics

Two Premolar Extractions Mean Std. Deviation Std. Error

Mean Pair 1 Treatment Mx Intermolar 44.2755 1.96555 0.41906

Setup Mx Intermolar 44.9545 1.93876 0.41334 Pair 2 Treatment Md Intermolar 43.3268 1.85364 0.39520

Setup Md Intermolar 43.3682 1.94383 0.41443 Pair 3 Treatment Mx Intercanine* 35.6773 1.76275 0.37582

Setup Mx Intercanine* 36.4818 1.55491 0.33151 Pair 4 Treatment Md Intercanine* 27.2659 0.93809 0.20000

Setup Md Intercanine* 28.1864 1.31413 0.28017 Pair 5 Tx Overjet 2.8164 1.03122 0.21986

Setup Overjet 2.4182 0.38992 0.08313 Pair 6 Treatment Overbite* 1.2109 0.86350 0.18410

Setup Overbite* 1.8864 0.66996 0.14284 Asterisk (*) indicates statistically significant P value

Table 1. Paired sample statistics of treatment and setup groups with two premolar extractions

This sample compared 22 patients treated with two maxillary premolar extractions.

Paired sample T-tests showed significant difference (P<.05) between maxillary intercanine width

(p=0.026), mandibular intercanine width (p=0.006), and overbite (p=0.014) between uLab virtual

27

setup and treatment groups. There was no significant difference in maxillary intermolar width

(p=0.078), mandibular intermolar width (p=0.922) or overjet (p=0.146) among the samples.

GROUP 2


Four Premolar Extractions Mean Std. Deviation Std. Error

Mean Pair 1 Treatment Mx Intermolar* 45.8454 3.07397 0.62747

Setup Mx Intermolar* 46.9833 3.25625 0.66468 Pair 2 Treatment Md Intermolar 40.6683 2.36435 0.48262

Setup Md Intermolar 41.0500 2.92486 0.59703 Pair 3 Treatment Mx Intercanine* 35.9683 2.20478 0.45005

Setup Mx Intercanine* 37.9542 2.39691 0.48927 Pair 4 Treatment Md Intercanine* 27.8263 1.54234 0.31483

Setup Md Intercanine* 29.5542 2.00564 0.40940 Pair 5 Tx Overjet* 3.1100 0.65078 0.13284

Setup Overjet* 2.3583 0.46989 0.09592 Pair 6 Tx Overbite 1.5250 0.64900 0.13248

Setup Overbite 1.7667 0.65519 0.13374 Asterisk (*) indicates statistically significant P value

Table 2. Paired sample statistics of treatment and setup groups with four premolar extractions

This sample included 24 patients treated with four premolar extractions. Paired sample t-

tests showed significant difference between maxillary intermolar width (p=0.297), maxillary

intercanine width (p=0.000), mandibular intercanine width (p=0.000), and overjet (p=0.000)

between treatment and virtual setup groups. There was no significant difference between

mandibular intermolar width (p=0.297) or overbite (p=0.110) among the groups.

28

GROUP 3



Mean Pair 1 Pre-treatment Mx Intermolar* 45.8500 2.76849 0.59024

Setup Mx Intermolar* 44.9545 1.93876 0.41334 Pair 2 Pre-treatment Md Intermolar* 41.9727 2.41822 0.51557

Setup Md Intermolar* 43.3682 1.94383 0.41443 Pair 3 Pre-treatment Mx Intercanine* 34.6818 2.58395 0.55090

Setup Mx Intercanine* 36.4818 1.55491 0.33151 Pair 4 Pre-treatment Md Intercanine* 26.9045 2.14908 0.45819

Setup Md Intercanine* 28.1864 1.31413 0.28017 Pair 5 Pre-treatment Overjet* 6.0000 2.75145 0.58661

Setup Overjet* 2.4182 0.38992 0.08313 Pair 6 Pre-treatment Overbite* 2.8727 1.66538 0.35506

Setup Overbite* 1.8864 0.66996 0.14284

Four Premolar Extractions

Pair 7 Pre-treatment Mx Intermolar* 47.4875 3.38761 0.69149 Setup Mx Intermolar* 46.9833 3.25625 0.66468

Pair 8 Pre-treatment Md Intermolar* 43.1625 3.00634 0.61367 Setup Md Intermolar* 41.0500 2.92486 0.59703

Pair 9 Pre-treatment Mx Intercanine* 35.7583 3.13409 0.63974 Setup Mx Intercanine* 37.9542 2.39691 0.48927

Pair 10 Pre-treatment Md Intercanine* 27.4250 2.63756 0.53839 Setup Md Intercanine* 29.5542 2.00564 0.40940

Pair 11 Pre-treatment Overjet* 4.4667 1.54488 0.31535 Setup Overjet* 2.3583 0.46989 0.09592

Pair 12 Pre-treatment Overbite 1.3417 1.69908 0.34682 Setup Overbite 1.7667 0.65519 0.13374

Asterisk (*) indicates statistically significant P value Table 3. Paired sample statistics of pre-treatment and setup groups

When comparing pre-treatment measurements to virtual setups for two premolar

extractions (N=22), paired sample T-tests showed significant difference for all variables

29

measured. In the four premolar extraction group (N=24), pre-treatment measurements compared

to setup showed significant difference for all variables except for overbite (p=0.139).



Mean Pair 1 Pre-treatment Mx Intermolar* 45.8500 2.76849 0.59024

Treatment Mx Intermolar* 44.2755 1.96555 0.41906 Pair 2 Pre-treatment Md Intermolar* 41.9727 2.41822 0.51557

Treatment Md Intermolar* 43.3268 1.85364 0.39520 Pair 3 Pre-treatment Mx Intercanine* 34.6818 2.58395 0.55090

Treatment Mx Intercanine* 35.6773 1.76275 0.37582 Pair 4 Pre-treatment Md Intercanine 26.9045 2.14908 0.45819

Treatment Md Intercanine 27.2659 0.93809 0.20000 Pair 5 Pre-treatment Overjet* 6.0000 2.75145 0.58661

Treatment Overjet* 2.8164 1.03122 0.21986 Pair 6 Pre-treatment Overbite* 2.8727 1.66538 0.35506

Treatment Overbite* 1.2109 0.86350 0.18410


Pair 7 Pre-treatment Mx Intermolar* 47.4875 3.38761 0.69149 Treatment Mx Intermolar* 45.8454 3.07397 0.62747

Pair 8 Pre-treatment Md Intermolar* 43.1625 3.00634 0.61367 Treatment Md Intermolar* 40.6683 2.36435 0.48262

Pair 9 Pre-treatment Mx Intercanine 35.7583 3.13409 0.63974 Treatment Mx Intercanine 35.9683 2.20478 0.45005

Pair 10 Pre-treatment Md Intercanine 27.4250 2.63756 0.53839 Treatment Md Intercanine 27.8263 1.54234 0.31483

Pair 11 Pre-treatment Overjet* 4.4667 1.54488 0.31535 Treatment Overjet* 3.1100 0.65078 0.13284

Pair 12 Pre-treatment Overbite 1.3417 1.69908 0.34682 Treatment Overbite 1.5250 0.64900 0.13248

Asterisk (*) indicates statistically significant P value Table 4. Paired sample statistics of pre-treatment and treatment groups

30

There was no significant difference between mandibular intercanine width between pre-

treatment and post-treatment groups treated with two maxillary premolar extractions. There was

a significant difference between maxillary intermolar width (p=0.000), mandibular intermolar

width (p=0.008), maxillary intercanine width (p=0.043), overjet (p=0.000) and overbite

(p=0.000).

There was no significant difference between maxillary intercanine width, mandibular

intercanine width and overbite between pre-treatment and post-treatment groups treated with

four premolar extractions. There was a significant difference between pre- and post-treatment in

maxillary intermolar width (p=0.000), mandibular intermolar width (p=0.000), and overjet

(p=0.000) treated with four extractions.

31

Intra-observer Error Rate

Intraclass Correlation Coefficient (ICC) estimates and their 95% confidence interval were

calculated using SPSS statistical package version 24 (SPSS Inc, Chicago IL) based on absolute-

agreement, 2-way mixed-effects model. An ICC value less than 0.5 indicates poor reliability,

0.5-0.75 indicates moderate, 0.75-0.9 indicates good, and lastly, greater than 0.9 indicates

excellent reliability. ICC calculations revealed excellent reliability among measurements, which

establishes reliable repeatability of measurements with a single examiner.

ICC

Maxillary Intermolar 0.987

Maxillary Intercanine 0.979

Mandibular Intermolar 0.989

Mandibular Intercanine 0.948

Overjet 0.976

Overbite 0.985

Table 5. Intra-observer reliability with Intraclass Correlation Coefficient (n=40)

32

Chapter 4: Discussion

This study aimed to determine whether there were significant differences between virtual

treatment simulations and actual treatment outcomes in Class II malocclusions treated with two

or four premolar extractions. Further comparison to pre-treatment dimensions were carried out to

determine whether there were significant changes, and potential implications on long-term

stability.

Treatment plans involving maxillary premolar extractions are generally selected to relieve

crowding in that arch or to reduce excessive overjet, with little to no change to the mandibular

arch. Within this study, overjet decreased in 20 of the 22 patients from pre- to post-treatment.

The two patients which did not have a decrease from pre-treatment values were likely treated

with extractions due to crowding in the maxillary arch. Similarly, of the 24 patients treated with

four premolar extractions, overjet decreased in all but three patients. There was no significant

difference in overjet between treatment outcomes and virtual simulations treated with two

extractions; suggesting that actual treatment and simulated projections produced similar results.

Deepening of the bite is a common characteristic observed in extraction cases. Uprighting

and relative extrusion of the maxillary anterior dentition can contribute to this when being

retracted to reduce overjet. In patients treated with two premolar extractions, we found a

statistically significant difference in overbite between both pre-treatment versus post-treatment

results and pre-treatment results versus virtual simulation. The data showed that from initial pre-

treatment values, overbite increased more post-treatment, while with virtual simulation, the

average change in overbite decreased. This suggests virtual simulation may have produced

superior results in preventing bite deepening from their initial values. In patients with deep bites

33

pre-treatment, mechanics such as segmented archwires can be applied to prevent further bite

deepening during retraction.

Pre- and post-treatment evaluation of patients treated with two premolar extractions found a

statistically significant difference between maxillary intercanine width, with a mean difference of

-0.99mm. This suggests that throughout the course of treatment, there was a tendency to expand

the maxillary intercanine width about 1mm from its initial parameters. In a study evaluating

dental arch changes post-retention in Class II division 1 malocclusions treated with extractions,

Anuwongnukroh et al. (2017) found that intercanine width increased significantly in both the

maxillary and mandibular arches following treatment. This increase in intercanine width post-

extraction can be attributed to the distalization of the canines into a wider area of the archform.

Alternatively, intermolar width can be expected to decrease after treatment, as the molars move

anteriorly into the extraction spaces occupying a narrower area of the archform (Shapiro, 1974).

Of the patients in this study treated with four premolar extractions, there was an average decrease

in intermolar width between pre- and post-treatment in both the maxillary and mandibular

arches. Therefore, the intercanine and intermolar width changes observed were consistent with

findings presented in the literature.

Evaluation of virtual simulation and treatment outcomes found statistically significant

differences in maxillary and mandibular intercanine widths in patients treated with two or four

premolar extractions. The mean difference in intercanine width among these groups suggests that

the virtual simulation expanded the canine width more than the actual treatment outcome in both

arches.

Comparison of pre-treatment dimensions to the virtual simulation found statistically

significant differences in maxillary and mandibular intercanine width in patients treated with two

34

and four premolar extractions. We found that there was a greater tendency to expand intercanine

width using 3D-software than during actual treatment, with an average increase of between 1.2-

2.1mm from pre-treatment dimensions. The general trend of expanding intercanine width may be

viewed as a potential weakness of virtual treatment simulation. However, a potential benefit of

this retrospective study design is that it offers the primary operator an opportunity to learn trends

and weaknesses of their treatment simulations which can then be applied to future patients.

A number of investigators have evaluated the effects of intercanine and intermolar width

changes following a post-retention phase. Shapiro et al. (1974) found that increased mandibular

intercanine width showed a strong tendency to return to pre-treatment dimensions at 10 years

post-retention. It has been suggested that Class II division 2 malocclusions show greater post-

treatment stability with intercanine expansion than their Class I and Class II division 1

counterparts. Similarly, a study by Motamedi (2015) found that an increase in intercanine width

was not maintained post-treatment. From this, we can conclude that intercanine expansion in

Class II division 1 malocclusions is not stable long-term. For patients in this study with increased

intercanine dimensions post-treatment, either prolonged or permanent retention may be indicated

to prevent unwanted relapse. Changes in intermolar dimensions did not present as much concern,

as a decrease in intermolar width has been found to remain following a post-retention period

(Motamedi et al., 2015).

The development of the Visualized Treatment Objective (VTO) by McLaughlin and Bennett

(1999) in 1971 has assisted clinicians in organizing and simplifying treatment planning for years.

Dental VTO analysis aids in diagnosis and treatment planning decisions by allowing the clinician

to visualize and quantify the degree and direction of movement required for desired correction. It

also can help determine whether such movements are reasonable within the confines of patient

35

anatomy. The clinician records detailed information such as midline relationships, initial and

desired canine and molar relationships, the degree of spacing or crowding and the curve of spee.

This simple analysis aids in treatment planning by creating a summary of anticipated treatment

changes required to achieve a desired outcome and inter-arch relationships. Important treatment

decisions including whether to extract or not extract can be evaluated, as well as whether

correction can be achieved with orthopedic tooth movement alone or if surgical intervention is

indicated. Despite its great contribution to treatment planning, the VTO is not without

limitations. This analysis uses 2-dimensional calculations to predict movement of 3-dimensional

structures. The dental VTO does not consider individual variability including the size or

angulation of the dentition, overjet and overbite.

The technique of using digital software demonstrated in this study produces a 3D simulation

of potential treatment outcomes. Much like a VTO analysis, digital software can quantify desired

tooth movement. These calculations incorporate features not included in the VTO such as

overjet, overbite and angulation changes of the dentition. This ability to directly visualize the

type, degree and direction of desired tooth movement using virtual simulations can aid in

treatment decisions.

36

Limitations and Future Studies

Several limitations should be noted as patients in this study were collected from the

database of a university residency program and therefore treated by various providers. Many

differing biomechanical approaches were used in the treatment of these patients, all of which can

influence final treatment outcomes. The sample was also limited by the amount of information

available as many patient files did not include important and relevant data like diagnostic aids or

pre-treatment STL files and therefore could not be included.

This study may be repeated in the future with a larger sample size in both two and four

premolar extraction groups. Furthermore, a prospective study could be designed using virtual

setups as a goal for treatment results. Post-treatment outcomes can be compared to virtual setups

to determine whether there is a statistically significant difference in variables when simulations

are used to guide treatment. Future studies may also compare the results of VTO analyses to

virtual setups to determine whether suggested degree and direction of prescribed tooth

movements coincide.

Conclusions

Digital models of 48 Class II division 1 malocclusion patients treated with two and four

premolar extractions were selected. Pre-treatment, post-treatment and virtual treatment

simulations were measured for intercanine width, intermolar width, overjet and overbite. The

purpose was to observe whether there were statistically significant changes among these

variables. The following conclusions can be made based on the findings in this study:

1. Despite statistically significant differences between treatment outcomes and virtual

setups in variables including overbite and overjet, the difference between them was not

clinically significant.

37

2. Statistically significant differences in both the maxillary and mandibular intercanine

widths between digital setups and treatment outcomes suggests that with software

simulations, the clinician tends to over-expand the intercanine width.

3. Virtual setups showed a tendency to expand intercanine dimensions more than the actual

treatment outcomes when comparing to the initial pre-treatment dimensions.

4. This study supports the use of virtual setups for the purpose of guiding treatment and

visualizing potential outcomes.

38

Appendix A: Data Results

GROUP 1: TWO EXTRACTIONS MAXILLARY INTERMOLAR

MEASUREMENTS

MANDIBULAR INTERMOLAR MEASUREMENTS

PRE-TX TREATMENT SETUP PRE-TX TREATMENT SETUP 45.2 43.48 45.6 39.5 42.04 41.9

43.5 44.63 44.2 40.2 41.49 41.4 49.4 47.53 47.5 43.1 42.73 43.4 47.6 44.24 46.8 45.1 44.38 47.6 45.7 45.43 43.4 45 43.75 44.4 43.1 41.57 43.6 40.7 42.27 43.3 49.1 44.51 46.7 44.1 42.6 45.9 40.8 41.73 42.4 38.2 43.11 43.1 41.3 41.13 43.4 39.1 39.26 41.2 49.9 47.23 47.9 45.6 46.73 46.6 45.4 45.03 46 42.7 40.11 44.1 46.5 43.92 45.3 41.7 42.47 42.6 44.4 43.4 43.7 41.2 42.3 41.8 48.1 44.24 46 44 44.62 45.4 44.4 44.81 42.8 39.6 42.73 40.6 48.8 45.36 45.4 46.7 46.32 45.5 42.7 41.71 42 38.1 44.9 40.4 48.6 47.21 44.2 42.3 45.68 43.1 47.5 45.68 46.2 42 43.56 42.3 48.9 46.02 49.2 42.7 44.88 44.3 45.1 44.5 42.9 41.3 44.6 43.2 42.7 40.7 43.8 40.5 42.66 42

MAXILLARY INTERCANINE MANDIBULAR INTERCANINE

PRE-TX TREATMENT SETUP PRE-TX TREATMENT SETUP 37.3 34.92 37.4 26.4 26.67 26.7 32.4 35.82 36.1 29.1 27.14 30.3 32.9 37.69 36.4 29 27.41 29.2 33.2 36.11 37.8 27.7 27.32 30.8 30.6 33.53 33.4 25.5 27.32 26.1 38.5 37.42 37.3 24.9 27.84 27.6 34.8 34.75 36.8 26.2 26.49 27.5 33.5 34.94 36.9 28.7 28.62 28.2

39

34.8 34.86 35.7

23.3 25.5 28.3 36.6 37.95 38.8 28.4 27.62 29.2

37 36.91 39 27.8 28.89 28.3 35 34.48 36.8 26.4 27.55 28.6

34.6 34.21 35.1 26.4 26.55 27.5 30.5 36.12 35 22.3 27.88 26.4

33 36.17 35.9 26.6 26.87 28.1 34.6 33.92 36 28.3 26.55 27.8 34.8 34.07 34.8 25.8 25.53 28.3 36.2 38.19 36.4 27.1 28.22 27.8 38.9 37.44 39.5 30.4 28.71 30 39.1 37.45 38 30.1 27.66 29.7 34.6 36.8 34.4 28.1 27.5 27.9 30.1 31.15 35.1 23.4 26.01 25.8

OVERJET OVERBITE

PRE-TX TREATMENT SETUP PRE-TX TREATMENT SETUP 5.6 2.8 2.8 3.3 0.1 1.9 12 3.6 2.3 5 0.8 4 3.1 4.13 2.4 3.1 1.21 2.4

13.5 4.6 2.5 4 2.3 1 7.3 3 2 -0.7 1.6 1.8

5 2 3.1 2.5 1.1 2.2 9 2.7 2.1 3.2 1.4 2.3

4.2 2.4 2.4 3.5 0.1 2.4 1.9 2 1.7 0.8 1.5 1 7.2 3.5 2.8 0.8 1.8 2

7 3.7 2 4.4 2.1 1.5 4.7 2.8 2.3 4 0.8 1.7 6.2 1.5 2.4 5.6 0.5 1.4

3 1.7 2.6 1.9 0.6 1.5 6.1 5.1 1.6 0.6 1 1.6 5.2 2.32 2.4 1.3 0.75 2.4 5.4 3 2.2 3.8 1 1.1 5.7 3.1 2.4 3.8 0.8 2.4 5.7 2.4 3 2.2 0.9 1.4 4.6 2.8 2.6 1.3 0.4 1.4 2.9 0.6 2.7 3.6 1.9 2.4 6.7 2.21 2.9 5.2 3.98 1.7

40

GROUP 2: FOUR EXTRACTIONS MAXILLARY INTERMOLAR

MEASUREMENTS

MANDIBULAR INTERMOLAR MEASUREMENTS

PRE-TX TREATMENT SETUP PRE-TX TREATMENT SETUP 46.5 43.63 46.8 40.5 37.98 41.5 48.7 45.6 49.6 44.2 41.54 42 50.2 49.03 51.1 46.4 43.19 44.6 45.8 44.23 45.5 40.9 40.1 40 52.1 49.64 50.9 44.3 42.38 43.9 45.5 46.16 46.2 41.9 41.46 41.1 50.8 47.94 49.7 43.6 42.2 44.1 44.8 42.7 44.1 40.2 37.71 37.6 46.6 44.49 46.4 43.6 39.8 41.3 47.9 48.37 49.7 47.2 41.07 42.2 47.8 45.13 45.9 41.9 39.62 40.3 50.4 49.43 50.5 45.9 43.81 44.5

51 48.58 49.5 46.2 41.81 44.1 50.9 46.41 47.9 44 40 41.2 41.9 40.14 41 38.7 36.55 36.3 50.9 51.5 51.6 48 44.78 47 42.6 41.52 42.1 40.5 38.11 37.3 41.1 40.82 40.9 38.5 37 37.1 48.9 45.61 48 45 40.84 40.6 51.8 49.41 48.7 46.4 41.81 42.9 42.4 42.93 42.3 38 39.38 36.3 43.5 42.96 43.5 39.7 38.84 37.1 49.5 47.57 48.2 46.6 45.7 41 48.1 46.49 47.5 43.7 40.36 41.2

MAXILLARY INTERCANINE MANDIBULAR INTERCANINE

PRE-TX TREATMENT SETUP PRE-TX TREATMENT SETUP 36.2 35.72 38.2 27.6 28.69 29.9 30.7 34.8 34.9 24.4 26.27 26.6 36.9 37.53 39.6 26.8 29.2 30.5 34.2 35.8 36.1 25 27.09 28.9 38.4 36.79 40.2 25.4 28.42 30 37.2 37.39 40.1 30.1 28.56 29.9 38.7 39.4 41.1 30.7 30.18 31.8 33.3 35.23 36.6 25.4 27.64 28.9 37.2 36.31 38 27 27.69 29.5 38.1 36.46 38.8 30.9 28.32 29.8

41

39.8 37.34 39.5

28.9 29.45 30.7 41 40.03 41.6 29.1 30.91 34.2

37.1 37.05 39.4 28.7 28.51 31.1 37.3 35.23 37.6 25.9 27.98 29.3 32.8 31.92 34.6 22.5 24.85 26.9

39 37.98 41.3 33.8 28.63 32.7 30.2 30.84 32.7 25.3 24.96 25.5 28.5 31.39 33.7 23.5 25.55 26.3 35.7 36.32 39.9 29.7 28.61 31 35.9 36.46 38.7 28.2 27.08 28.9

37 36.23 36.2 25.8 26.67 27.5 34.9 35.35 37.4 27.5 27.58 29.4 32.3 37.23 37.3 26.7 28.92 29.9 35.8 34.44 37.4 29.3 26.07 30.1

OVERJET OVERBITE

PRE-TX TREATMENT SETUP PRE-TX TREATMENT SETUP 5.5 3.1 2.2 2.6 0.3 1.6

4 2.68 2.1 0.6 1.49 1.1 5.1 3.8 3.4 3.2 1.8 2.6 3.9 4 2.9 2.4 1.5 2.1 4.4 3.3 2.6 1.8 2.9 2.1 5.7 2.68 2.9 1 1.19 1.9 3.8 3.2 2.4 1.1 1.4 1.7 3.5 2.4 1.6 1.6 2 1.5 3.3 3.2 2.1 0 0.8 1 1.9 2.5 2 0.2 0.8 1 5.4 3.8 2.2 2.2 2.1 1.9 6.7 4 2.2 2 2.1 1.6 1.7 2.7 1.7 -0.3 0.7 1 3.2 2.4 1.9 3.2 2.6 2 2.5 2.1 3 0 0.7 1 3.9 3.3 1.6 -3.4 1.4 0.7 5.3 3.08 2.1 3.3 1.42 1.4 4.7 2.6 2.3 2.9 1.3 3.4 7.3 3.1 2.4 2.3 1.6 2 3.8 2.9 2.9 0.2 2 2.5 4.3 3.3 2.7 4.3 2.1 2.8 7.8 2.7 2.2 -1.3 1.4 1.4 3.7 5 2.3 1.5 2.2 1.9 5.8 2.8 2.9 0.8 0.8 2.2

42

Appendix B: Graphs Maxillary Intercanine Width of Patients Treated with Two Premolar Extractions

Mandibular Intercanine Width of Patients Treated with Two Premolar Extractions

0

5

10

15

20

25

30

35

40

45

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

INTE

RCAN

INE

WID

TH (M

M)

TWO-PREMOLAR EXTRACTION GROUP

Maxillary Intercanine Width

Pre-Treatment

Treatment Group

Setup Group

0

5

10

15

20

25

30

35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

INTE

RCAN

INE

WID

TH (M

M)

TWO-PREMOLAR EXTRACTION GROUP

Mandibular Intercanine Width Pre-Treatment

TreatmentGroup

43

Appendix C: Statistical Analysis Tables ANALYSIS OF TREATMENT AND SETUP GROUPS TREATED WITH TWO PREMOLAR EXTRACTIONS Paired T-Test

Paired Differences

Mean Std.

Deviation Std. Error

Mean

95% Confidence Interval of the

Difference Lower Upper

Pair 1

TX Mx Intermolar – SU Mx Intermolar

-0.67909

1.71753 0.36618 -1.44060 0.08242

Pair 2

Tx Mn Intermolar – SU Mn Intermolar

-0.04136

1.95414 0.41662 -0.90778 0.82505

Pair 3

TX Mx Canine – SU Mx Canine

-0.80455

1.57138 0.33502 -1.50126 -0.10783

Pair 4

TX Mn Canine – SU Mn Canine

-0.92045

1.40134 0.29877 -1.54177 -0.29914

Pair 5

TX Overjet – SU Overjet

0.39818 1.23803 0.26395 -0.15073 0.94710

Pair 6

TX Overbite – SU Overbite

-0.67545

1.18180 0.25196 -1.19944 -0.15147

t df Sig. (2-tailed) -1.855 21 0.078

-0.099 21 0.922

-2.401 21 0.026

-3.081 21 0.006

1.509 21 0.146 -2.681 21 0.014

44

ANALYSIS OF TREATMENT AND SETUP GROUPS TREATED WITH FOUR PREMOLAR EXTRACTIONS Paired T-Test

Paired Differences

Mean Std.


Mean

95% Confidence Interval of the Difference

Lower Upper Pair 1

TX Mx Intermolar – SU Mx Intermolar

-1.13792

1.08653 0.22179 -1.59672 -0.67912

Pair 2

Tx Mn Intermolar – SU Mn Intermolar

-0.38167

1.75112 0.35745 -1.12110 0.35777

Pair 3

TX Mx Canine – SU Mx Canine

-1.98583

1.02226 0.20867 -2.41750 -1.55417

Pair 4

TX Mn Canine – SU Mn Canine

-1.72792

0.96771 0.19753 -2.13654 -1.31929

Pair 5

TX Overjet – SU Overjet

0.75167 0.73529 0.15009 0.44118 1.06215

Pair 6

TX Overbite – SU Overbite

-0.24167

0.71277 0.14549 -0.54264 0.05931

t df Sig. (2-tailed) -5.131 23 0.000

-1.068 23 0.297

-9.517 23 0.000

-8.747 23 0.000

5.008 23 0.000

-1.661 23 0.110

45

ANALYSIS OF PRE-TREATMENT AND SETUP GROUPS TREATED WITH TWO AND FOUR PREMOLAR EXTRACTIONS Paired T-Test

Two Premolar Extractions

Paired Differences

Mean Std.


Mean



Pair 1

Pre Mx Intermolar – SU Mx Intermolar*

0.89545 1.66232 0.35441 0.15842 1.63249

Pair 2

Pre Mn Intermolar – SU Mn Intermolar*

-1.39545

1.24307 0.26502 -1.94660 -0.84431

Pair 3

Pre Mx Canine - SU Mx Canine*

-1.80000

1.83977 0.39224 -2.61571 -0.98429

Pair 4

Pre Mn Canine – SU Mn Canine*

-1.28182

1.52335 0.32478 -1.95724 -0.60640

Pair 5

Pre Overjet – SU Overjet*

3.58182 2.79006 0.59484 2.34478 4.81886

Pair 6

Pre Overbite – SU Overbite*

0.98636 1.66456 0.35489 0.24834 1.72439


Pair 7

Pre Mx Intermolar – SU Mx Intermolar*

0.50417 1.17120 0.23907 0.00961 0.99872

Pair 8

Pre Mn Intermolar – SU Mn Intermolar*

2.11250 1.55320 0.31705 1.45664 2.76836

Pair 9

Pre Mx Canine - SU Mx Canine*

-2.19583

1.52984 0.31228 -2.84183 -1.54984

Pair 10

Pre Mn Canine – SU Mn Canine*

-2.12917

1.70587 0.34821 -2.84949 -1.40884

Pair 11

Pre Overjet – SU Overjet*

2.10833 1.51282 0.30880 1.46953 2.74714

Pair 12

Pre Overbite – SU Overbite

-0.42500

1.35719 0.27703 -0.99809 0.14809

46

t df

Sig. (2-

tailed) 2.527 21 0.020

-5.265

21 0.000

-4.589

21 0.000

-3.947

21 0.001

6.021 21 0.000 2.779 21 0.011

2.109 23 0.046

6.663 23 0.000

-7.032

23 0.000

-6.115

23 0.000

6.827 23 0.000 -

1.534 23 0.139

ANALYSIS OF PRE-TREATMENT AND POST-TREATMENT GROUPS TREATED WITH TWO AND FOUR PREMOLAR EXTRACTIONS Paired T-Test

Two Premolar Extractions

Paired Differences

Mean Std.


Mean



Pair 1

Pre Mx Intermolar – TX Mx Intermolar*

1.57455 1.53619 0.32752 0.89344 2.25566

Pair 2

Pre Mn Intermolar – TX Mn Intermolar*

-1.35409

2.17522 0.46376 -2.31853 -0.38965

Pair 3

Pre Mx Canine - TX Mx Canine*

-0.99545

2.16511 0.46160 -1.95541 -0.03550

47

Pair 4

Pre Mn Canine – TX Mn Canine

-0.36136

1.89389 0.40378 -1.20107 0.47834

Pair 5

Pre Overjet – TX Overjet*

3.18364 2.38531 0.50855 2.12605 4.24122

Pair 6

Pre Overbite – TX Overbite*

1.66182 1.75305 0.37375 0.88456 2.43908


Pair 7

Pre Mx Intermolar – TX Mx Intermolar*

1.64208 1.36621 0.27888 1.06518 2.21898

Pair 8

Pre Mn Intermolar – TX Mn Intermolar*

2.49417 1.61382 0.32942 1.81271 3.17562

Pair 9

Pre Mx Canine - TX Mx Canine

-0.21000

1.85059 0.37775 -0.99144 0.57144

Pair 10

Pre Mn Canine – TX Mn Canine

-0.40125

2.06355 0.42122 -1.27261 0.47011

Pair 11

Pre Overjet – TX Overjet*

1.35667 1.54354 0.31507 0.70489 2.00845

Pair 12

Pre Overbite – TX Overbite

-0.18333

1.58657 0.32386 -0.85328 0.48662

48

t df

Sig. (2-

tailed) 4.808 21 0.000

-2.920

21 0.008

-2.157

21 0.043

-0.895

21 0.381

6.260 21 0.000 4.446 21 0.000

5.888 23 0.000 7.571 23 0.000

-0.556

23 0.584

-0.953

23 0.351

4.306 23 0.000 -

0.566 23 0.577

49

Appendix D: Reliability Studies Bland Altman Plot of Maxillary Intermolar Measurements

Intraclass Correlation Coefficient of Maxillary Intermolar Measurements

Reliability Statistics Cronbach's

Alpha N of Items .997 2

Intraclass Correlation Coefficient of Maxillary Intercanine Measurements



-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Diffe

renc

e be

twee

n m

easu

rem

ents

Mean of measurements

Bland Altman Plot of Maxillary Intermolar Width

50

Intraclass Correlation Coefficient of Mandibular Intermolar Measurements



Intraclass Correlation Coefficient

Intraclass 95% Confidence Interval F Test with True Value 0


Intraclass

Correlationb

95% Confidence Interval F Test with True Value 0 Lower Bound

Upper Bound Value df1 df2 Sig

Single Measures

.979a .961 .989 95.178 39 39 .000

Average Measures

.989c .980 .994 95.178 39 39 .000

Two-way mixed effects model where people effects are random and measures effects are fixed. a. The estimator is the same, whether the interaction effect is present or not. b. Type A intraclass correlation coefficients using an absolute agreement definition. c. This estimate is computed assuming the interaction effect is absent, because it is not estimable otherwise.


Intraclass

Correlationb

95% Confidence Interval F Test with True Value 0

Lower Bound


Single Measures

.987a .833 .996 338.668 39 39 .000

Average Measures

.993c .909 .998 338.668 39 39 .000


51

Correlationb Lower Bound


Single Measures

.989a .979 .994 172.866 39 39 .000

Average Measures

.994c .989 .997 172.866 39 39 .000


Intraclass Correlation Coefficient of Mandibular Intercanine Measurements




Intraclass

Correlationb


Lower Bound


Single Measures

.948a .905 .972 36.919 39 39 .000

Average Measures

.974c .950 .986 36.919 39 39 .000


Intraclass Correlation Coefficient of Overjet Measurements

52




Intraclass

Correlationb


Lower Bound


Single Measures

.976a .954 .987 79.165 39 39 .000

Average Measures

.988c .977 .993 79.165 39 39 .000


Intraclass Correlation Coefficient of Overbite Measurements




Intraclass

Correlationb


Lower Bound


Single Measures

.985a .972 .992 131.845 39 39 .000

53

Average Measures

.992c .986 .996 131.845 39 39 .000

Two-way mixed effects model where people effects are random and measures effects are fixed. a. The estimator is the same, whether the interaction effect is present or not.

b. Type A intraclass correlation coefficients using an absolute agreement definition.

c. This estimate is computed assuming the interaction effect is absent, because it is not estimable otherwise.

54

Appendix E: IRB Exemption

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Curriculum Vitae

Graduate College

University of Nevada, Las Vegas

Sogol Shantiyai, DMD

Email: [email protected] Degrees: Bachelor of Science- Biology San Diego State University, 2012 Doctor of Dental Medicine Midwestern University College of Dental Medicine, 2016 General Practice Residency Stony Brook University, 2017 Thesis Title: Comparison of digital treatment setups and final treatment outcomes of Class II Division 1 malocclusions treated with premolar extractions Thesis Examination Committee: Chairperson, Tanya Al-Talib, D.D.S., M.S. Committee Member, Brian G. Chrzan, D.D.S., Ph.D. Committee Member, Robert A. Danforth, D.D.S. Graduate Faculty Representative, Amei Amei, Ph.D., M.S. Graduate Program Director, James K. Mah, D.D.S., M.S., D.M.Sc.

comparison of digital treatment setups and final treatment

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