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Esthetic dental perception comparisons between 2D- and 3D-simulated dental discrepancies
RESEARCH AND EDUCATION
Esthetic dental perception comparisons between 2D- and 3D-simulated dental discrepancies Marta Revilla-León, DDS, MSD,a Hayley E. Campbell,b Matthew J. Meyer,c Mikhail Umorin, PhD,d Amerian Sones, DDS, MS,e and Amirali Zandinejad, DDS, MSf
ABSTRACT Statement of problem. Intraoral scanners (IOSs), facial scanners (FSs), and computer-aided design (CAD) software programs have become powerful tools for treatment planning. However, discrepancies in perception regarding 2-dimensional (2D) or 3-dimensional (3D) simulations by dentists, dental students, and laypeople have not been analyzed. Purpose. The purpose of this observational study was to analyze the perceptions of laypersons, dental students, and dentists regarding disparities of the maxillary dental midline and the occlusal plane when analyzing the dental discrepancies on 2D- and 3D-clinical simulations. Material and methods. A female model was digitized by using an FS, IOS, and a full-face smile photograph. Dental discrepancies were simulated by using a 2D photograph (2D group) and 3D scan (3D group) of the model. In both simulation groups, 2 subgroups were produced. The occlusal plane of the first subgroup was modified in 1-degree increments without changing the dental midline or the position of the maxillary dental incisors. In the second subgroup, the occlusal plane was modified by using the same increments, but the maxillary central incisors and dental midline were altered to match the inclination of the occlusal plane. A total of 300 participants (N=300) were asked to rate the 2D images (N=12) and 3D videos (N=12) on a 1-to-6 scale and answer a questionnaire. Ordinal logistic regression was used to analyze the ratings. Results. The ratings decreased with the increased tilt of the occlusal plane, and the layperson group gave consistently higher ratings than the other 2 groups. For dentists, the odds of giving a higher versus lower rating decreased by almost a half for each degree of tilt. However, for students, that effect was diminished by a positive interaction term, and for laypersons, the effect was even less. Students gave similar ratings to dentists, but laypersons gave higher ratings. As the age of the participants increased, however, the ratings also increased. The use of 3D versus 2D images had a positive effect on the ratings, but the effect decreased for the student observers and decreased even further for laypersons. Furthermore, midline alteration led to higher ratings but also resulted in worsening of the odds ratio for the tilt. Seventy percent of the dentists, 57% of the dental students, and 52% of the laypersons preferred 2D simulations to 3D simulations. Conclusions. Dentists, dental students, and laypersons decreased their ratings with increased inclination of the occlusal plane; however, laypersons still graded all the 2D and 3D images as esthetically pleasant, giving consistently higher ratings than the dentists and dental students. Overall, 3D simulations obtained higher ratings than 2D images, but the positive effect decreased for the student observers and decreased even further for laypersons. (J Prosthet Dent 2019;-:---)
The integration of digital technologies such as facial scanners (FSs), intraoral scanners (IOSs), and computeraided design (CAD) software programs into restorative treatment planning procedures1-6 allows the production
of virtual diagnostic waxing.7-13 Digital technologies facilitate the superimposition of 3D digital waxing into the 2D or 3D image of the patient,7-12 which represents a powerful diagnostic tool and may improve patient
a
Assistant Professor and Assistant Program Director AEGD, Comprehensive Dentistry Department, College of Dentistry, Texas A&M University, Dallas, Texas; and Affiliate Assistant Professor, Graduate Prosthodontics, University of Washington, Seattle, Wash; and Researcher, Revilla Research Center, Madrid, Spain. b Predoctoral student, College of Dentistry, Texas A&M University, Dallas, Texas. c Predoctoral student, College of Dentistry, Texas A&M University, Dallas, Texas. d Assistant Professor, Department of Biological Sciences, College of Dentistry, Texas A&M University, Dallas, Texas. e Director, Continuing Education, College of Dentistry, Texas A&M University, Dallas, Texas. f Associate Professor and Program Director AEGD, Comprehensive Dentistry Department, College of Dentistry, Texas A&M University, Dallas, Texas.
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MATERIAL AND METHODS
Clinical Implications The esthetic perception of dental parameters may vary among dentists, dental students, and laypersons depending on the technological combination selected, namely 2D (photography) or 3D (facial scan) for superimposition with the digitized dentition.
visualization of the outcome of the proposed treatment.7,8,12,13 Dental professionals and laypersons have been reported to detect discrepancies in smile characteristics at differing levels, and for many reasons, laypersons were less discriminating than practitioners.14-28 Those studies used 2D images from a single smile of an unknown model modified with photograph-editing software programs.16 However, the ideal symmetric model virtually created with a specific esthetic parameter as an evaluating target does not represent an actual clinical situation.17 Moreover, survey studies using digitally modified 2D images are limited in the number of parameters they can assess, and none can give sufficient information to provide a comprehensive definition of an appealing smile.16 Furthermore, a layperson’s awareness of esthetic dental discrepancies when considering the same dental discrepancies on 2D and 3D simulations has not been evaluated. The subjective perception of esthetics has been analyzed with step-wise discrepancies between the occlusal plane and the facial references of the facial and maxillary dental midline.16-18,24-27 The majority of these protocols displayed only the lower third of the face, and the studies’ respective protocols for manipulating the maxillary occlusal plane also altered the maxillary dental midline. In these studies, laypersons only recognized deviations exceeding 3 degrees15,16 or 4 degrees.25 If the occlusal plane was tilted without altering the maxillary dental midline, however, laypersons rated a tilt of 5 degrees or less as esthetically pleasant.28 Even so, these studies did not compare discrepancies between the 2D and 3D perception of the occlusal plane and alterations in the maxillary dental midline inclination. The purpose of this observational study was to measure differences in esthetic perception among laypersons, dental students, and dentists regarding disparities between the occlusal plane and dental midline when simulations were presented on a full-face photograph (2D image) and a digitized face (3D video). The null hypothesis was that no significant differences in perception of disparities between the occlusal plane and dental midline existed among laypersons, dental students, or dentists or between 2D and 3D digital simulations.
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Three subpopulations, each containing 100 individuals, participated in the study: laypersons, dental students, and dentists. All participants were recruited at the Texas A&M Health Science Center. The protocol was approved by the Institutional Review Board (IRB) committee of the College of Dentistry at Texas A&M University (IRB 20190570-CD-EXM). The participants were all over 18 years of age, but non-English speakers, pregnant women, individuals with physical disabilities, individuals with cognitive disabilities, prisoners, individuals with psychiatric disorders, emotional or social impairments, and individuals with depression were all excluded. A woman was selected as the model (Fig. 1A). No digital modification of the face was performed. The model presented facial asymmetries, but the facial midline was coincident with the maxillary dental midline, and the occlusal plane was parallel to both the interpupillary line and the commissural line (Fig. 1B). A medium lip line and convex smile line were present. Furthermore, the gingival margins of the model’s maxillary teeth were even and bilaterally symmetric, no dental restorations were present in her dentition, and her oral health was good. Two groups of simulated dental discrepancies were created: a 2D simulation with a full-face maximum smile photograph (2D group) and a 3D simulation with a facial scanner (3D group) (Table 1). For the 2D group, a full-face frontal smile of the model was obtained by using a digital camera (EOS 70D DSLR; Canon U.S.A., Inc). A digital scan was then obtained by using an intraoral scanner (IOS) (iTero Element; Cadent) under room light following the manufacturer’s recommended scanning protocol (1000 lux) for ambient light scanning conditions. When the digital scan was completed, the IOS device created a standard tessellation language (STL) file labeled as STL1. Once the STL1 file was imported into a dental CAD software program (Dental Systems; 3Shape), 2 groups of digital simulations were created. In 1 subgroup (Post subgroup), the occlusal plane was modified in incremental inclinations of 1 degree (0, 1, 2, 3, 4, and 5 degrees) rotating to the model’s left, but the maxillary dental midline and the position of both maxillary central incisors were not manipulated for this group (Fig. 2). In the second subgroup (Post+Midline subgroup), the occlusal plane was modified by the same increments as in the Post group; however, the position of both maxillary central incisors was modified to match the inclination of the occlusal plane by changing the inclination of the dental midline (Fig. 3). In both subgroups (Post and Post+Midline), the height of the clinical crowns of the maxillary arch was modified without altering the gingival margin. The digital
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Figure 1. A, Full-face frontal smile photograph of female model. B, Facial midline and maxillary dental midline coincident and interpupillary and commissural lines parallel.
Table 1. Description of data-capturing procedures and digitally performed simulations on 2D and 3D groups Data Capturing Model’s Facial Tissues 2D using full-face photograph (2D group)
3D using facial scanner (3D group)
Data Capturing Model’s Mouth Digital scan using intraoral scanner (iTero Element; Cadent)
CAD Software
Simulations
Post subgroup (0, 1, 2, 3, 4, and 5)
Occlusal plane tilted by 1-degree increments to model’s left without changing maxillary dental midline or position of maxillary central incisors.
exocad 2.3 Matera (exocad)
Post+Midline Subgroup (0, 1, 2, 3, 4, and 5)
Occlusal plane tilted by 1-degree increments to model’s left. Maxillary dental midline modified to follow tilting of occlusal plane.
diagnostic waxing casts were superimposed on the 2D photograph of the participant by using a specific CAD tool (Real View of Dental Systems; 3Shape). A total of 12 images were obtained. For the 3D group, a facial scanner (Bellus3D Face Camera PRO; Bellus3D) was used to digitalize the participant’s extraoral facial soft tissues. A reference and smile scans were obtained by using an extraoral (ScanBodyFace; AFT Dental System) and intraoral (ScanBodyMouth; AFT Dental System) scan bodies. The model was instructed to refrain from making facial expressions that would displace the forehead scan body. For the reference scan, the intraoral scan body was positioned in the participant’s mouth and stabilized by using high- and low-viscosity polyvinyl siloxane impression material (Virtual putty regular setting; Ivoclar Vivadent AG). A facial scan was made by using both scan bodies following the manufacturer’s instructions. For the smile scan, the intraoral scan body was removed, but the forehead scan body remained in the same position. When the facial scans were completed, the software created a geometry definition (OBJ) file for each reference (OBJR file) and smile (OBJS file) scan. The intraoral scan body was digitized by using a laboratory dental scanner (E2 scanner; 3Shape) following the Revilla-León et al
Subgroups
Dental systems (3Shape)
manufacturer instructions, and an STL file (STL2) was exported. The STL1, OBJR, OBJS, and STL2 files were imported into a dental CAD software program (exocad Dental CAD Matera 2.3; exocad GmbH). The facial and intraoral scans were superimposed by using the forehead and intraoral scan bodies as common references. The 3D group files were digitally manipulated in the same manner as with the 2D group to create 2 subgroups within the 3D group (Figs. 4, 5). Once the 3D simulations were created, a video for each simulation was obtained so that participants could visualize the model’s 3D face with 180 degrees of horizontal rotation. A total of 12 videos were prepared. The participants were asked to evaluate each image and video according to their own esthetic criteria by using a visual analog scale from 1 to 6, in which 1 was the least esthetically appealing and 6 was the most esthetically appealing. The sequence of presentation images and videos were randomized each time for each participant by using a shuffled deck of cards. After the participant evaluated the images and videos, they answered the questionnaire (Table 2). Medians were used to summarize the rating data, and 95% confidence intervals for the medians were calculated THE JOURNAL OF PROSTHETIC DENTISTRY
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Figure 2. Two-dimensional (2D) dental discrepancies simulations performed by using intraoral scan and full-face smile photography. In Post subgroup, occlusal plane modified in incremental inclinations of 1 degree (0, 1, 2, 3, 4, and 5 degrees) rotated to model’s left, but maxillary dental midline and position of both maxillary central incisors unaltered. A, 0 degrees. B, 1 degree. C, 2 degrees. D, 3 degrees. E, 4 degrees. F, 5 degrees.
as 1.78 times the interquartile range.29 The effects of the observer group, sex, age, image type (2D versus 3D), midline modification, occlusal plane tilt, and their interactions on the ratings were evaluated. Ordinal logistic regression was used to account for the ordinal nature of the response variable.30 As this was a repeated-measures design and as individuals were nested within observer group levels, confounding between individuals and observer group and inclusion of interaction between
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observer groups and other variables resulted in a none full-rank model matrix and singularity of intermediate matrices during numeric optimization of the regression coefficients. From the authors’ previous work, fitting a linear model to the raw rating responses had provided qualitatively the same results.28 Thus, to identify significant effects while accounting for repeated measures and random effects of individuals, a linear mixed model with all main effects and their pairwise interactions and a
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Figure 3. Two-dimensional (2D) dental discrepancy simulations performed by using intraoral scans and full-face smile photography. In Post+Midline subgroup, occlusal plane modified in incremental inclinations of 1 degree (0, 1, 2, 3, 4, and 5 degrees) down to model’s left, but maxillary dental midline and position of both maxillary central incisors unaltered. A, 0 degrees. B, 1 degree. C, 2 degrees. D, 3 degrees. E, 4 degrees. F, 5 degrees.
random individual component was used. Significant terms from the linear mixed model were then incorporated in the ordinal regression model. A proportional odds assumption was made because it allowed the estimation of the parameters of the logistic regression and the odds ratios (OR). Analysis was performed in R statistical environment31 (R Core Team 2019) with the VGAM software package.32 Revilla-León et al
RESULTS Table 3 presents the age and sex of the surveyed individuals. The results showed that the ratings became lower with increased tilt of the occlusal plane (Figs. 6, 7). Also, observer group ratings gradually diverged from those of the layperson group, giving consistently higher ratings than the other 2 groups.
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Figure 4. Three-dimensional (3D) dental discrepancies simulations performed by using intraoral scan and facial smile scan. In Post subgroup, occlusal plane was modified in incremental inclinations of 1 degree (0, 1, 2, 3, 4, and 5 degrees) rotated to model’s left, but maxillary dental midline and position of both maxillary central incisors unaltered. A, 0 degrees. B, 1 degree. C, 2 degrees. D, 3 degrees. E, 4 degrees. F, 5 degrees.
The results of fitting a linear mixed model with the observer group, sex, age, image type, midline modification, occlusal plane tilt, their pairwise interactions, and a random effect for individuals are presented in Table 4. Based on the significance of the terms (significance level after Bonferroni correction for 21 terms=0.05/21=0.0024), the observer group, tilt, image type, age, and midline and group: tilt, group: image type, tilt: age, and tilt: midline pairwise interactions THE JOURNAL OF PROSTHETIC DENTISTRY
were included in the ordinal logistic model of the image ratings (Table 5); odds ratios (OR) for corresponding terms and their 95% confidence intervals are presented in Table 6. The R2 of the linear predictor of the latent variable following the study by McKelvey and Zavoina33 was 0.2865. As the values in Table 6 represent the ratio of odds of giving higher rating versus lower rating (for example, 3 and above versus below 3) per unit change in the Revilla-León et al
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Figure 5. Three-dimensional (3D) dental discrepancy simulations performed by using intraoral scans and full-face smile photography. In Post+Midline subgroup, occlusal plane modified in incremental inclinations of 1 degree (0, 1, 2, 3, 4, and 5 degrees) rotated to model’s left, but maxillary dental midline and position of both maxillary central incisors unaltered. A, 0 degrees. B, 1 degree. C, 2 degrees. D, 3 degrees. E, 4 degrees. F, 5 degrees.
independent variable and keeping other variables constant, Table 6 can be interpreted to mean that the inclination of the occlusal plane had a significant negative effect on the ratings but that the degree of the effect varied across observer groups: for dentists, the odds of giving higher versus lower rating would decrease by almost a half for each degree of tilt (OR=0.4747). However, for students, that effect would be diminished by a positive interaction term Revilla-León et al
(OR(student: tilt)=1.1238), and for laypersons, the effect would be even less (OR(layperson: tilt)=1.5846). Group by itself affected the ratings: students gave similar ratings to dentists (OR students=1.1087, n.s. from 1.0), but laypersons gave higher ratings (OR laypersons=1.3454) on average. The significant interaction of age and tilt (OR(tilt: age) =1.0021) was so slight that it should be considered of no practical consequence. As the age of the participants THE JOURNAL OF PROSTHETIC DENTISTRY
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What method would you like to implement in your private practice? a. Photograph
a. Photograph
b. Facial scan
b. Facial scan
c. None
c. None
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5
Laypersons What method would you like to be used by your dentist?
Rating
Dentists
Issue
6
Table 2. Questionnaire given to dentists, dental students, and laypersons Dental Students
-
4 3 2 1 0
Table 3. Age and sex structure of survey sample
1
2
3
4
5
Tilt, Degrees
A
Sex Population Count
Dentists
N=100
Students
Laypersons
N=100
N=100
Age Group
F
M
18-25
3
2
26-35
18
15
36-45
10
8
46-55
10
9
56-65
6
10
Total:
49
51
18-25
54
29
26-35
8
8
36-45
0
1
46-55
0
0
56-65
0
0
Total:
62
38
18-25
31
8
26-35
7
3
36-45
5
6
46-55
8
4
56-65
8
4
Total
70
30
increased, however, they gave higher ratings (OR per year of age=1.0114). The use of 3D images versus 2D had a positive effect on the ratings (OR=1.1978), but the effect decreased in the student population (OR(student:3D-image.type)=0.4824) and was even further decreased in laypersons (OR(laypersons:3D-image.type) =0.2448). Interestingly, midline alteration led to higher ratings (OR=1.3699) but also resulted in worsening of the odds ratio for the tilt (OR(tilt: midline)=0.8996). That is, participants gave relatively worse ratings to the images with increased tilt when the midline was altered versus when it was not. Seventy percent of the dentists and 57% of the dental students preferred to incorporate the 2D simulations into their private practice, while 52% of the laypersons preferred that their dentists used the 2D simulations rather than the 3D simulations. DISCUSSION Dentists, dental students, and laypeople rated significantly differently the different disparities between the occlusal plane and the interpupillary and commissural lines with or without the alteration of the maxillary dental THE JOURNAL OF PROSTHETIC DENTISTRY
6 5
Rating
Population Name
4 3 2 1 0
1
2
3
Tilt, Degrees
4
5
B
Figure 6. Observer group medians (solid lines) and 95% CI (error bars). A, As function of occlusal plane tilt for unchanged midline and 2D image type. B, As function of occlusal plane tilt for modified midline and 2D image type. Dentists: red line, dental students: green line, laypersons: blue line. Note: lines for dental students and those not in dental field groups offset by plus or minus 0.1 to prevent line overlap.
midline inclination on 2D and 3D simulations. Therefore, both null hypotheses were rejected. Overall, all participants decreased their ratings with increased inclination of the occlusal plane. Observer group ratings gradually diverged with those of the layperson group, giving consistently higher ratings than the dentists and dental students. Those results are consistent with those of previous studies.16,25,28 However, the results of those studies showed that deviations in occlusal plane inclinations were not noticeable by laypersons unless they exceeded 2 degrees,24 3 degrees,14 or 4 degrees.15,24,25 Most of those studies included only the display of the lower third and the alteration of the maxillary occlusal plane and maxillary midline together at different inclines. In a previous study by the authors of this study,28 the perception disparities among dentists, dental students, and laypersons regarding the inclination of the occlusal plane in relationship to the horizontal facial references such as the interpupillary and commissural line were evaluated. However, dental discrepancies on a perfectly symmetrical model were produced with a photographediting software program. In the present study, an actual female model was used, so both 2D and 3D simulations Revilla-León et al
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Table 4. Analysis of variance of the linear mixed regression model, including observer group, sex, age, image type, midline modification, occlusal plane tilt, all pairwise interactions as fixed effects, and individuals as random effects
Rating
5 4
Term tilt
3
Df
P
2425.27
1
<2.00E-16
group: tilt
266.14
2
<2.00E-16
2
mage type
248.08
1
<2.00E-16
group: image type
194.61
2
<2.00E-16
1
group
48.89
2
2.40E-11
midline: tilt
25.8
1
3.80E-07
age: image type
18.11
1
2.10E-05
age: tilt
17.53
1
2.80E-05
age
9.37
1
.002
mage type: midline
8.21
1
.004
mage type: tilt
8
1
.005
0
1
2
3
4
5
Tilt, Degrees
A
6 5
Rating
Chi Square
4
sex: midline
4.32
1
.038
sex
4.24
1
.039
3
group: sex
6.02
2
.049
sex: tilt
3.17
1
.075
2
midline
3.15
1
.076
group: age
4.94
2
.085
1
sex: age
2.07
1
.150
0
1
2
3
Tilt, Degrees
4
5
B
Figure 7. Observer group medians (solid lines) and 95% CI (error bars). A, As function of occlusal plane tilt for unchanged midline and 3D image type. B, As function of occlusal plane tilt for modified midline and 3D image type. Dentists: red line, dental students: green line, laypersons: blue line. Note: lines for dental students and those not in dental field groups offset by plus or minus 0.1 to prevent line overlap.
could be performed identically, and a dental CAD software program was used to superimpose the real dentition of the model on the full-face photograph of the model at smile position. The results of the previous study and the results of the present study for the 2D group without the inclination of the dental midline were similar. The authors are unaware of a previous dental esthetic perception evaluation that compared 2D with 3D simulations. Based on the results obtained in the present study, all the groups presented significant perception discrepancies between the 2D and 3D simulations. The dental disparities performed on 3D simulations obtained a higher rating than the same discrepancy performed on a 2D image, but the positive effect of the 3D versus 2D was decreased in the dental student population and was even further decreased in laypersons. The higher rating on the 3D simulations could be because the esthetic discrepancy was more difficult to detect as all the participants lacked experience visualizing a 3D facial representation. Owing to interaction between the observer group and tilt, dentists and, to a lesser degree, dental students gave higher ratings than laypersons at smaller tilt values but gave lower ratings than laypersons at higher tilt values in
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group: midline
3.49
2
.174
sex: image type
1.13
1
.288
age: midline
0.52
1
.472
Terms sorted in increasing order of P values.
3D simulations (Fig. 7A). Small perception differences were encountered on 3D simulations between dentist and dental students, with dental students providing lower ratings than dentists at the same OP tilt. This could be explained by a generational difference or earlier adaptation of the technology on a daily basis. Nevertheless, layperson perception results should be interpreted carefully, as all the simulations presented were rated as esthetically pleasant. This could have 2 explanations: laypersons did not detect those disparities because of their esthetically pleasant perception of 4 degrees of occlusal plane inclination with 4 degrees of maxillary dental midline inclination, or laypersons provided a high rating because they lacked experience perceiving such disparities. The inclination of the maxillary dental midline led to higher ratings but also resulted in worsening of the odds ratio for the tilt. Participants gave relatively worse ratings to the images with increased tilt when the midline was altered versus when it was not. Furthermore, dental students provided consistently lower ratings than dentists throughout most of the range of occlusal plane inclinations whether the maxillary dental midline was modified or not in the 3D simulations (Fig. 7). This can be interpreted again as the dental students’ ability to perceive disparities at smaller OP inclinations than dentists on the 3D simulations.
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Table 5. Analysis of deviance (Type II) for reduced ordinal logistic regression model P
Term
Df
Deviance
Group
2
238.56
<2e-16
Tilt
1
1487.22
<2e-16
Image type
1
158.56
<2e-16
Age
1
114.32
<2e-16
Midline
1
1.13
group: tilt
2
232.83
<2e-16
group: image.type
2
175.28
<2e-16
tilt: age
1
5.28
tilt: midline
1
17.48
.288
.022 2.90E-05
Table 6. Odds ratios (ORs) and their 95% CIs based on regression coefficient ordinal logistic regression from Table 3 Term
OR
Lower 2.5% Bound
group-student
1.1087
0.8776
Upper 2.5% Bound 1.4
groupelayperson
1.3454
1.0894
1.662
Tilt
0.4747
0.4326
0.521
Image typee3D
1.1978
1.0366
1.384
Age
1.0114
1.006
1.017
midlineemodified
1.3699
1.1799
1.59
groupestudent: tilt
1.1238
1.0487
1.204
groupelayperson: tilt
1.5846
1.4906
1.685
groupestudent: image. type-3D
0.4824
0.3931
0.592
groupelayperson: image type-3D
0.2448
0.199
0.301
tilt: age
1.0021
1.0003
1.004
tilt: midline-modified
0.8996
0.8565
0.945
Reference levels: group: dentist, image type: 2D, midline: unchanged.
Evaluating the entire face and personality of a patient is important when planning treatment with extensive restorations.27,34 Psychological factors and subjective preferences of the patient should be considered and incorporated into the treatment planning procedures.27,34 The 3D representations may have eliminated the emotional aspect, while the 2D photograph maintain the emotional component as participants may identify themselves better in a conventional photograph. The objective of incorporating digital technologies such as facial and intraoral scanners and CAD software programs into private practice might be increasing patient communication, facilitating interdisciplinary dialogue, and diagnostic waxing. However, training is needed to visualize 3D representations of patients, and even though 3D representation may provide a powerful diagnostic tool for the clinician, patients may not be able to interpret and visualize the 3D simulation appropriately. Consequently, a more understandable technology selection may be recommended based on the goal of the simulation. However, as 3D representations are more frequently adopted, individual perception will also evolve and adapt to the technology. Interestingly, all the participants preferred the 2D simulations compared
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with the 3D simulations for private practice applications. Further studies are recommended to analyze the differences in dimensional perception differences between dental professionals and laypersons when evaluating different esthetic disparities. CONCLUSIONS Based on the findings of this observational study, the following conclusions were drawn: 1. Dentists, dental students, and laypersons decreased their ratings with increased inclination of the occlusal plane. Observer group ratings gradually diverged from the layperson group, giving consistently higher ratings than the dentists and dental students. 2. Overall, 3D simulations obtained higher ratings than 2D images in dentist and dental student populations, but the positive effect was reversed at higher occlusal plane tilt angles. 3. Dentists provided lower ratings for a lower inclination of the maxillary dental midline in the 2D simulations than dental students, but dental students detected disparities at smaller occlusal plane inclinations than dentists in the 3D simulations. 4. Laypersons graded all the 2D and 3D images as esthetically pleasant. 5. Significant interaction of age and tilt was slight and of little consequence. However, the higher the age of the participants, the higher the ratings.
REFERENCES 1. The glossary of prosthodontic terms. Ninth edition. J Prosthet Dent 2017;117(5S):e1-105. 2. Miller CJ. The smile line as a guide to anterior esthetics. Dent Clin North Am 1989;33:157-64. 3. Chiche GJ, Pinault A. Esthetic of anterior fixed prosthodontics. 1st ed. Batavia: Quintessence Publishing Co Inc; 1994. p. 6-13. 4. Magne P, Magne M, Belser U. The diagnostic template: a key element to the comprehensive esthetic treatment concept. Int J Periodontics Restorative Dent 1996;16:560-9. 5. Kois DE, Schmidt KK, Raigrodski AJ. Esthetic templates for complex restorative cases: rationale and management. J Esthet Restor Dent 2008;20: 239-50. 6. Marzola R, Derbabian K, Donovan TE, Arcidiancono A. The science of communicating the art of esthetic dentistry: part I: patient-dentist-patient communication. J Esthet Dent 2000;12:131-8. 7. Joda T, Brägger U, Gallucci G. Systematic literature review of digital threedimensional superimposition techniques to create virtual dental patients. Int J Oral Maxillofac Implants 2015;30:330-7. 8. Cattoni F, Mastrangelo F, Gherlone EF, Gastaldi G. A new total digital smile planning technique (3D-DSP) to fabricate CAD-CAM mockups for esthetic crowns and veneers. Int J Dent 2016;2016:6282587. 9. Mangano C, Luongo F, Migliario M, Mortellaro C, Mangano FG. Combining intraoral scans, cone beam computed tomography and face scans: the virtual patient. J Craniofac Surg 2018;29:2241-6. 10. Revilla-León M, Sánchez-Rubio JL, Besné-Torre A, Özcan M. A report on a diagnostic digital workflow for esthetic dental rehabilitation using additive manufacturing technologies. Int J Esthet Dent 2018;13:184-96. 11. Revilla-León M, Besné-Torre A, Sánchez-Rubio JL, Fábrega JJ, Özcan M. Digital tools and 3D printing technologies integrated into the workflow of restorative treatment: a clinical report. J Prosthet Dent 2019;121:3-8.
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12. Revilla-León M, Raney L, Cascón-Piedra W, Barrington J, Zandinejad A, Özcan M. Digital workflow for an esthetic rehabilitation using a facial and intraoral scanner and an additive manufactured silicone index: a dental technique. J Prosthet Dent 2019. doi: 10.1016/j.prosdent.2019.03.014. [Epub ahead of print]. 13. Piedra-Cascón W, Hsu VT, Revilla-León M. Facially driven digital diagnostic waxing: New software features to simulate and define restorative outcomes. Clin Oral Health Rep 2019. doi: 10.1007/s40496-019-00233-6. [Epub ahead of print]. 14. Peck S, Peck L. Selected aspects of the art and science of facial esthetics. Semin Orthod 1995;1:105-26. 15. Padwa BL, Kaiser MO, Kaban LB. Occlusal cant in the frontal plane as a reflection of facial asymmetry. J Oral Maxillofac Surg 1997;55:811-7. 16. Kokich VO, Kiyac HA, Shapiro PA. Comparing the perception of dentists and laypeople to altered dental esthetic. J Esthet Dent 1999;11:311-24. 17. Johnston DC, Burden DJ, Stevenson MR. The influence of dental to facial midline discrepancies on dental attractiveness ratings. Eur J Orthod 1999;21: 517-22. 18. Thomas JL, Hayes C, Zawaideh S. The effect of axial midline angulation on dental esthetics. Angle Orthod 2003;73:359-64. 19. Roden-Johnson D, Gallerano R, English J. The effects of buccal corridor spaces and arch form on smile esthetics. Am J Orthod Dentofacial Orthop 2003;127:343-50. 20. Flores-Mir C, Silva E, Barriga MI, Lagravere MO, Major PW. Lay person’s perception of smile esthetics in dental and facial views. J Orthod 2004;31: 204-9. 21. LaVacca MI, Tarnow DP, Cisneros GJ. Interdental papilla length and the perception of esthetics. Pract Proced Aesthet Dent 2005;17: 405-12. 22. Moore T, Southard KA, Casko JS, Qian F, Southard TE. Buccal corridors and smile esthetics. Am J Orthod Dentofacial Orthop 2005;127:208-13. 23. Geron S, Atalia W. Influence of sex on the perception of oral and smile esthetics with different gingival display and incisal plane inclination. Angle Orthod 2005;75:778-84. 24. Kokich VO, Kokich VG, Kiyak HA. Perceptions of dental professionals and laypersons to altered dental esthetics: asymmetric and symmetric situations. Am J Orthod Dentofacial Orthop 2006;130:141-51.
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25. Kerr AJ, Chan R, Fields HW, Beck M, Rosenstiel S. Esthetics and smile characteristics from the layperson’s perspective: a computer-based survey study. J Am Dent Assoc 2008;139:1318-27. 26. Del Monte S, Afrashtehfar KI, Emami E, Abi Nader S, Tamimi F. Lay preferences for dentogingival esthetic parameters: a systematic review. J Prosthet Dent 2017;118:717-24. 27. Magne P, Salem P, Magne M. Influence of symmetry and balance on visual perception of a white female smile. J Prosthet Dent 2018;120: 573-82. 28. Revilla-León M, Meyer MJ, Barrington JJ, Sones A, Umorin MP, Taleghani M, et al. Perception of occlusal plane that is nonparallel to interpupillary and commissural lines but with the maxillary dental midline ideally positioned. J Prosthet Dent 2019. doi: 10.1016/j.prosdent.2019.01.023. [Epub ahead of print]. 29. McGill R, Tukey JW, Larsen WA. Variations of box plots. Am Stat 1978;32: 12-6. 30. Agresti A. Analysis of ordinal categorical data. New Jersey: 2nd ed. Wiley; 2010. p. 88-117. 31. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2019. Available at: https://www.R-project.org/. Accessed June 1, 2018. 32. Yee TW. Vector generalized linear and additive models: with an implementation in R. New York: Springer; 2015. p. 33-90. 33. McKelvey RD, Zavoina W. A statistical model for the analysis of ordinal level dependent variables. J Math Sociol 1975;4:103-20. 34. Paolucci B, Calamita M, Coachman C, Gurel G, Shayder A, Hallawell P. Visagism: the art of dental composition. QDT 2012;35:1-14. Corresponding author: Dr Marta Revilla-León 3302 Gaston Avenue Room 713 Dallas, TX 75246 Email: [email protected] Copyright © 2019 by the Editorial Council for The Journal of Prosthetic Dentistry. https://doi.org/10.1016/j.prosdent.2019.11.015
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Esthetic dental perception comparisons between 2D- and 3D-simulated dental discrepancies Marta Revilla-León, DDS, MSD,a Hayley E. Campbell,b Matthew J. Meyer,c Mikhail Umorin, PhD,d Amerian Sones, DDS, MS,e and Amirali Zandinejad, DDS, MSf
ABSTRACT Statement of problem. Intraoral scanners (IOSs), facial scanners (FSs), and computer-aided design (CAD) software programs have become powerful tools for treatment planning. However, discrepancies in perception regarding 2-dimensional (2D) or 3-dimensional (3D) simulations by dentists, dental students, and laypeople have not been analyzed. Purpose. The purpose of this observational study was to analyze the perceptions of laypersons, dental students, and dentists regarding disparities of the maxillary dental midline and the occlusal plane when analyzing the dental discrepancies on 2D- and 3D-clinical simulations. Material and methods. A female model was digitized by using an FS, IOS, and a full-face smile photograph. Dental discrepancies were simulated by using a 2D photograph (2D group) and 3D scan (3D group) of the model. In both simulation groups, 2 subgroups were produced. The occlusal plane of the first subgroup was modified in 1-degree increments without changing the dental midline or the position of the maxillary dental incisors. In the second subgroup, the occlusal plane was modified by using the same increments, but the maxillary central incisors and dental midline were altered to match the inclination of the occlusal plane. A total of 300 participants (N=300) were asked to rate the 2D images (N=12) and 3D videos (N=12) on a 1-to-6 scale and answer a questionnaire. Ordinal logistic regression was used to analyze the ratings. Results. The ratings decreased with the increased tilt of the occlusal plane, and the layperson group gave consistently higher ratings than the other 2 groups. For dentists, the odds of giving a higher versus lower rating decreased by almost a half for each degree of tilt. However, for students, that effect was diminished by a positive interaction term, and for laypersons, the effect was even less. Students gave similar ratings to dentists, but laypersons gave higher ratings. As the age of the participants increased, however, the ratings also increased. The use of 3D versus 2D images had a positive effect on the ratings, but the effect decreased for the student observers and decreased even further for laypersons. Furthermore, midline alteration led to higher ratings but also resulted in worsening of the odds ratio for the tilt. Seventy percent of the dentists, 57% of the dental students, and 52% of the laypersons preferred 2D simulations to 3D simulations. Conclusions. Dentists, dental students, and laypersons decreased their ratings with increased inclination of the occlusal plane; however, laypersons still graded all the 2D and 3D images as esthetically pleasant, giving consistently higher ratings than the dentists and dental students. Overall, 3D simulations obtained higher ratings than 2D images, but the positive effect decreased for the student observers and decreased even further for laypersons. (J Prosthet Dent 2019;-:---)
The integration of digital technologies such as facial scanners (FSs), intraoral scanners (IOSs), and computeraided design (CAD) software programs into restorative treatment planning procedures1-6 allows the production
of virtual diagnostic waxing.7-13 Digital technologies facilitate the superimposition of 3D digital waxing into the 2D or 3D image of the patient,7-12 which represents a powerful diagnostic tool and may improve patient
a
Assistant Professor and Assistant Program Director AEGD, Comprehensive Dentistry Department, College of Dentistry, Texas A&M University, Dallas, Texas; and Affiliate Assistant Professor, Graduate Prosthodontics, University of Washington, Seattle, Wash; and Researcher, Revilla Research Center, Madrid, Spain. b Predoctoral student, College of Dentistry, Texas A&M University, Dallas, Texas. c Predoctoral student, College of Dentistry, Texas A&M University, Dallas, Texas. d Assistant Professor, Department of Biological Sciences, College of Dentistry, Texas A&M University, Dallas, Texas. e Director, Continuing Education, College of Dentistry, Texas A&M University, Dallas, Texas. f Associate Professor and Program Director AEGD, Comprehensive Dentistry Department, College of Dentistry, Texas A&M University, Dallas, Texas.
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Clinical Implications The esthetic perception of dental parameters may vary among dentists, dental students, and laypersons depending on the technological combination selected, namely 2D (photography) or 3D (facial scan) for superimposition with the digitized dentition.
visualization of the outcome of the proposed treatment.7,8,12,13 Dental professionals and laypersons have been reported to detect discrepancies in smile characteristics at differing levels, and for many reasons, laypersons were less discriminating than practitioners.14-28 Those studies used 2D images from a single smile of an unknown model modified with photograph-editing software programs.16 However, the ideal symmetric model virtually created with a specific esthetic parameter as an evaluating target does not represent an actual clinical situation.17 Moreover, survey studies using digitally modified 2D images are limited in the number of parameters they can assess, and none can give sufficient information to provide a comprehensive definition of an appealing smile.16 Furthermore, a layperson’s awareness of esthetic dental discrepancies when considering the same dental discrepancies on 2D and 3D simulations has not been evaluated. The subjective perception of esthetics has been analyzed with step-wise discrepancies between the occlusal plane and the facial references of the facial and maxillary dental midline.16-18,24-27 The majority of these protocols displayed only the lower third of the face, and the studies’ respective protocols for manipulating the maxillary occlusal plane also altered the maxillary dental midline. In these studies, laypersons only recognized deviations exceeding 3 degrees15,16 or 4 degrees.25 If the occlusal plane was tilted without altering the maxillary dental midline, however, laypersons rated a tilt of 5 degrees or less as esthetically pleasant.28 Even so, these studies did not compare discrepancies between the 2D and 3D perception of the occlusal plane and alterations in the maxillary dental midline inclination. The purpose of this observational study was to measure differences in esthetic perception among laypersons, dental students, and dentists regarding disparities between the occlusal plane and dental midline when simulations were presented on a full-face photograph (2D image) and a digitized face (3D video). The null hypothesis was that no significant differences in perception of disparities between the occlusal plane and dental midline existed among laypersons, dental students, or dentists or between 2D and 3D digital simulations.
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Three subpopulations, each containing 100 individuals, participated in the study: laypersons, dental students, and dentists. All participants were recruited at the Texas A&M Health Science Center. The protocol was approved by the Institutional Review Board (IRB) committee of the College of Dentistry at Texas A&M University (IRB 20190570-CD-EXM). The participants were all over 18 years of age, but non-English speakers, pregnant women, individuals with physical disabilities, individuals with cognitive disabilities, prisoners, individuals with psychiatric disorders, emotional or social impairments, and individuals with depression were all excluded. A woman was selected as the model (Fig. 1A). No digital modification of the face was performed. The model presented facial asymmetries, but the facial midline was coincident with the maxillary dental midline, and the occlusal plane was parallel to both the interpupillary line and the commissural line (Fig. 1B). A medium lip line and convex smile line were present. Furthermore, the gingival margins of the model’s maxillary teeth were even and bilaterally symmetric, no dental restorations were present in her dentition, and her oral health was good. Two groups of simulated dental discrepancies were created: a 2D simulation with a full-face maximum smile photograph (2D group) and a 3D simulation with a facial scanner (3D group) (Table 1). For the 2D group, a full-face frontal smile of the model was obtained by using a digital camera (EOS 70D DSLR; Canon U.S.A., Inc). A digital scan was then obtained by using an intraoral scanner (IOS) (iTero Element; Cadent) under room light following the manufacturer’s recommended scanning protocol (1000 lux) for ambient light scanning conditions. When the digital scan was completed, the IOS device created a standard tessellation language (STL) file labeled as STL1. Once the STL1 file was imported into a dental CAD software program (Dental Systems; 3Shape), 2 groups of digital simulations were created. In 1 subgroup (Post subgroup), the occlusal plane was modified in incremental inclinations of 1 degree (0, 1, 2, 3, 4, and 5 degrees) rotating to the model’s left, but the maxillary dental midline and the position of both maxillary central incisors were not manipulated for this group (Fig. 2). In the second subgroup (Post+Midline subgroup), the occlusal plane was modified by the same increments as in the Post group; however, the position of both maxillary central incisors was modified to match the inclination of the occlusal plane by changing the inclination of the dental midline (Fig. 3). In both subgroups (Post and Post+Midline), the height of the clinical crowns of the maxillary arch was modified without altering the gingival margin. The digital
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Figure 1. A, Full-face frontal smile photograph of female model. B, Facial midline and maxillary dental midline coincident and interpupillary and commissural lines parallel.
Table 1. Description of data-capturing procedures and digitally performed simulations on 2D and 3D groups Data Capturing Model’s Facial Tissues 2D using full-face photograph (2D group)
3D using facial scanner (3D group)
Data Capturing Model’s Mouth Digital scan using intraoral scanner (iTero Element; Cadent)
CAD Software
Simulations
Post subgroup (0, 1, 2, 3, 4, and 5)
Occlusal plane tilted by 1-degree increments to model’s left without changing maxillary dental midline or position of maxillary central incisors.
exocad 2.3 Matera (exocad)
Post+Midline Subgroup (0, 1, 2, 3, 4, and 5)
Occlusal plane tilted by 1-degree increments to model’s left. Maxillary dental midline modified to follow tilting of occlusal plane.
diagnostic waxing casts were superimposed on the 2D photograph of the participant by using a specific CAD tool (Real View of Dental Systems; 3Shape). A total of 12 images were obtained. For the 3D group, a facial scanner (Bellus3D Face Camera PRO; Bellus3D) was used to digitalize the participant’s extraoral facial soft tissues. A reference and smile scans were obtained by using an extraoral (ScanBodyFace; AFT Dental System) and intraoral (ScanBodyMouth; AFT Dental System) scan bodies. The model was instructed to refrain from making facial expressions that would displace the forehead scan body. For the reference scan, the intraoral scan body was positioned in the participant’s mouth and stabilized by using high- and low-viscosity polyvinyl siloxane impression material (Virtual putty regular setting; Ivoclar Vivadent AG). A facial scan was made by using both scan bodies following the manufacturer’s instructions. For the smile scan, the intraoral scan body was removed, but the forehead scan body remained in the same position. When the facial scans were completed, the software created a geometry definition (OBJ) file for each reference (OBJR file) and smile (OBJS file) scan. The intraoral scan body was digitized by using a laboratory dental scanner (E2 scanner; 3Shape) following the Revilla-León et al
Subgroups
Dental systems (3Shape)
manufacturer instructions, and an STL file (STL2) was exported. The STL1, OBJR, OBJS, and STL2 files were imported into a dental CAD software program (exocad Dental CAD Matera 2.3; exocad GmbH). The facial and intraoral scans were superimposed by using the forehead and intraoral scan bodies as common references. The 3D group files were digitally manipulated in the same manner as with the 2D group to create 2 subgroups within the 3D group (Figs. 4, 5). Once the 3D simulations were created, a video for each simulation was obtained so that participants could visualize the model’s 3D face with 180 degrees of horizontal rotation. A total of 12 videos were prepared. The participants were asked to evaluate each image and video according to their own esthetic criteria by using a visual analog scale from 1 to 6, in which 1 was the least esthetically appealing and 6 was the most esthetically appealing. The sequence of presentation images and videos were randomized each time for each participant by using a shuffled deck of cards. After the participant evaluated the images and videos, they answered the questionnaire (Table 2). Medians were used to summarize the rating data, and 95% confidence intervals for the medians were calculated THE JOURNAL OF PROSTHETIC DENTISTRY
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Figure 2. Two-dimensional (2D) dental discrepancies simulations performed by using intraoral scan and full-face smile photography. In Post subgroup, occlusal plane modified in incremental inclinations of 1 degree (0, 1, 2, 3, 4, and 5 degrees) rotated to model’s left, but maxillary dental midline and position of both maxillary central incisors unaltered. A, 0 degrees. B, 1 degree. C, 2 degrees. D, 3 degrees. E, 4 degrees. F, 5 degrees.
as 1.78 times the interquartile range.29 The effects of the observer group, sex, age, image type (2D versus 3D), midline modification, occlusal plane tilt, and their interactions on the ratings were evaluated. Ordinal logistic regression was used to account for the ordinal nature of the response variable.30 As this was a repeated-measures design and as individuals were nested within observer group levels, confounding between individuals and observer group and inclusion of interaction between
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observer groups and other variables resulted in a none full-rank model matrix and singularity of intermediate matrices during numeric optimization of the regression coefficients. From the authors’ previous work, fitting a linear model to the raw rating responses had provided qualitatively the same results.28 Thus, to identify significant effects while accounting for repeated measures and random effects of individuals, a linear mixed model with all main effects and their pairwise interactions and a
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Figure 3. Two-dimensional (2D) dental discrepancy simulations performed by using intraoral scans and full-face smile photography. In Post+Midline subgroup, occlusal plane modified in incremental inclinations of 1 degree (0, 1, 2, 3, 4, and 5 degrees) down to model’s left, but maxillary dental midline and position of both maxillary central incisors unaltered. A, 0 degrees. B, 1 degree. C, 2 degrees. D, 3 degrees. E, 4 degrees. F, 5 degrees.
random individual component was used. Significant terms from the linear mixed model were then incorporated in the ordinal regression model. A proportional odds assumption was made because it allowed the estimation of the parameters of the logistic regression and the odds ratios (OR). Analysis was performed in R statistical environment31 (R Core Team 2019) with the VGAM software package.32 Revilla-León et al
RESULTS Table 3 presents the age and sex of the surveyed individuals. The results showed that the ratings became lower with increased tilt of the occlusal plane (Figs. 6, 7). Also, observer group ratings gradually diverged from those of the layperson group, giving consistently higher ratings than the other 2 groups.
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Figure 4. Three-dimensional (3D) dental discrepancies simulations performed by using intraoral scan and facial smile scan. In Post subgroup, occlusal plane was modified in incremental inclinations of 1 degree (0, 1, 2, 3, 4, and 5 degrees) rotated to model’s left, but maxillary dental midline and position of both maxillary central incisors unaltered. A, 0 degrees. B, 1 degree. C, 2 degrees. D, 3 degrees. E, 4 degrees. F, 5 degrees.
The results of fitting a linear mixed model with the observer group, sex, age, image type, midline modification, occlusal plane tilt, their pairwise interactions, and a random effect for individuals are presented in Table 4. Based on the significance of the terms (significance level after Bonferroni correction for 21 terms=0.05/21=0.0024), the observer group, tilt, image type, age, and midline and group: tilt, group: image type, tilt: age, and tilt: midline pairwise interactions THE JOURNAL OF PROSTHETIC DENTISTRY
were included in the ordinal logistic model of the image ratings (Table 5); odds ratios (OR) for corresponding terms and their 95% confidence intervals are presented in Table 6. The R2 of the linear predictor of the latent variable following the study by McKelvey and Zavoina33 was 0.2865. As the values in Table 6 represent the ratio of odds of giving higher rating versus lower rating (for example, 3 and above versus below 3) per unit change in the Revilla-León et al
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Figure 5. Three-dimensional (3D) dental discrepancy simulations performed by using intraoral scans and full-face smile photography. In Post+Midline subgroup, occlusal plane modified in incremental inclinations of 1 degree (0, 1, 2, 3, 4, and 5 degrees) rotated to model’s left, but maxillary dental midline and position of both maxillary central incisors unaltered. A, 0 degrees. B, 1 degree. C, 2 degrees. D, 3 degrees. E, 4 degrees. F, 5 degrees.
independent variable and keeping other variables constant, Table 6 can be interpreted to mean that the inclination of the occlusal plane had a significant negative effect on the ratings but that the degree of the effect varied across observer groups: for dentists, the odds of giving higher versus lower rating would decrease by almost a half for each degree of tilt (OR=0.4747). However, for students, that effect would be diminished by a positive interaction term Revilla-León et al
(OR(student: tilt)=1.1238), and for laypersons, the effect would be even less (OR(layperson: tilt)=1.5846). Group by itself affected the ratings: students gave similar ratings to dentists (OR students=1.1087, n.s. from 1.0), but laypersons gave higher ratings (OR laypersons=1.3454) on average. The significant interaction of age and tilt (OR(tilt: age) =1.0021) was so slight that it should be considered of no practical consequence. As the age of the participants THE JOURNAL OF PROSTHETIC DENTISTRY
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What method would you like to implement in your private practice? a. Photograph
a. Photograph
b. Facial scan
b. Facial scan
c. None
c. None
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Laypersons What method would you like to be used by your dentist?
Rating
Dentists
Issue
6
Table 2. Questionnaire given to dentists, dental students, and laypersons Dental Students
-
4 3 2 1 0
Table 3. Age and sex structure of survey sample
1
2
3
4
5
Tilt, Degrees
A
Sex Population Count
Dentists
N=100
Students
Laypersons
N=100
N=100
Age Group
F
M
18-25
3
2
26-35
18
15
36-45
10
8
46-55
10
9
56-65
6
10
Total:
49
51
18-25
54
29
26-35
8
8
36-45
0
1
46-55
0
0
56-65
0
0
Total:
62
38
18-25
31
8
26-35
7
3
36-45
5
6
46-55
8
4
56-65
8
4
Total
70
30
increased, however, they gave higher ratings (OR per year of age=1.0114). The use of 3D images versus 2D had a positive effect on the ratings (OR=1.1978), but the effect decreased in the student population (OR(student:3D-image.type)=0.4824) and was even further decreased in laypersons (OR(laypersons:3D-image.type) =0.2448). Interestingly, midline alteration led to higher ratings (OR=1.3699) but also resulted in worsening of the odds ratio for the tilt (OR(tilt: midline)=0.8996). That is, participants gave relatively worse ratings to the images with increased tilt when the midline was altered versus when it was not. Seventy percent of the dentists and 57% of the dental students preferred to incorporate the 2D simulations into their private practice, while 52% of the laypersons preferred that their dentists used the 2D simulations rather than the 3D simulations. DISCUSSION Dentists, dental students, and laypeople rated significantly differently the different disparities between the occlusal plane and the interpupillary and commissural lines with or without the alteration of the maxillary dental THE JOURNAL OF PROSTHETIC DENTISTRY
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Rating
Population Name
4 3 2 1 0
1
2
3
Tilt, Degrees
4
5
B
Figure 6. Observer group medians (solid lines) and 95% CI (error bars). A, As function of occlusal plane tilt for unchanged midline and 2D image type. B, As function of occlusal plane tilt for modified midline and 2D image type. Dentists: red line, dental students: green line, laypersons: blue line. Note: lines for dental students and those not in dental field groups offset by plus or minus 0.1 to prevent line overlap.
midline inclination on 2D and 3D simulations. Therefore, both null hypotheses were rejected. Overall, all participants decreased their ratings with increased inclination of the occlusal plane. Observer group ratings gradually diverged with those of the layperson group, giving consistently higher ratings than the dentists and dental students. Those results are consistent with those of previous studies.16,25,28 However, the results of those studies showed that deviations in occlusal plane inclinations were not noticeable by laypersons unless they exceeded 2 degrees,24 3 degrees,14 or 4 degrees.15,24,25 Most of those studies included only the display of the lower third and the alteration of the maxillary occlusal plane and maxillary midline together at different inclines. In a previous study by the authors of this study,28 the perception disparities among dentists, dental students, and laypersons regarding the inclination of the occlusal plane in relationship to the horizontal facial references such as the interpupillary and commissural line were evaluated. However, dental discrepancies on a perfectly symmetrical model were produced with a photographediting software program. In the present study, an actual female model was used, so both 2D and 3D simulations Revilla-León et al
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Table 4. Analysis of variance of the linear mixed regression model, including observer group, sex, age, image type, midline modification, occlusal plane tilt, all pairwise interactions as fixed effects, and individuals as random effects
Rating
5 4
Term tilt
3
Df
P
2425.27
1
<2.00E-16
group: tilt
266.14
2
<2.00E-16
2
mage type
248.08
1
<2.00E-16
group: image type
194.61
2
<2.00E-16
1
group
48.89
2
2.40E-11
midline: tilt
25.8
1
3.80E-07
age: image type
18.11
1
2.10E-05
age: tilt
17.53
1
2.80E-05
age
9.37
1
.002
mage type: midline
8.21
1
.004
mage type: tilt
8
1
.005
0
1
2
3
4
5
Tilt, Degrees
A
6 5
Rating
Chi Square
4
sex: midline
4.32
1
.038
sex
4.24
1
.039
3
group: sex
6.02
2
.049
sex: tilt
3.17
1
.075
2
midline
3.15
1
.076
group: age
4.94
2
.085
1
sex: age
2.07
1
.150
0
1
2
3
Tilt, Degrees
4
5
B
Figure 7. Observer group medians (solid lines) and 95% CI (error bars). A, As function of occlusal plane tilt for unchanged midline and 3D image type. B, As function of occlusal plane tilt for modified midline and 3D image type. Dentists: red line, dental students: green line, laypersons: blue line. Note: lines for dental students and those not in dental field groups offset by plus or minus 0.1 to prevent line overlap.
could be performed identically, and a dental CAD software program was used to superimpose the real dentition of the model on the full-face photograph of the model at smile position. The results of the previous study and the results of the present study for the 2D group without the inclination of the dental midline were similar. The authors are unaware of a previous dental esthetic perception evaluation that compared 2D with 3D simulations. Based on the results obtained in the present study, all the groups presented significant perception discrepancies between the 2D and 3D simulations. The dental disparities performed on 3D simulations obtained a higher rating than the same discrepancy performed on a 2D image, but the positive effect of the 3D versus 2D was decreased in the dental student population and was even further decreased in laypersons. The higher rating on the 3D simulations could be because the esthetic discrepancy was more difficult to detect as all the participants lacked experience visualizing a 3D facial representation. Owing to interaction between the observer group and tilt, dentists and, to a lesser degree, dental students gave higher ratings than laypersons at smaller tilt values but gave lower ratings than laypersons at higher tilt values in
Revilla-León et al
group: midline
3.49
2
.174
sex: image type
1.13
1
.288
age: midline
0.52
1
.472
Terms sorted in increasing order of P values.
3D simulations (Fig. 7A). Small perception differences were encountered on 3D simulations between dentist and dental students, with dental students providing lower ratings than dentists at the same OP tilt. This could be explained by a generational difference or earlier adaptation of the technology on a daily basis. Nevertheless, layperson perception results should be interpreted carefully, as all the simulations presented were rated as esthetically pleasant. This could have 2 explanations: laypersons did not detect those disparities because of their esthetically pleasant perception of 4 degrees of occlusal plane inclination with 4 degrees of maxillary dental midline inclination, or laypersons provided a high rating because they lacked experience perceiving such disparities. The inclination of the maxillary dental midline led to higher ratings but also resulted in worsening of the odds ratio for the tilt. Participants gave relatively worse ratings to the images with increased tilt when the midline was altered versus when it was not. Furthermore, dental students provided consistently lower ratings than dentists throughout most of the range of occlusal plane inclinations whether the maxillary dental midline was modified or not in the 3D simulations (Fig. 7). This can be interpreted again as the dental students’ ability to perceive disparities at smaller OP inclinations than dentists on the 3D simulations.
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Table 5. Analysis of deviance (Type II) for reduced ordinal logistic regression model P
Term
Df
Deviance
Group
2
238.56
<2e-16
Tilt
1
1487.22
<2e-16
Image type
1
158.56
<2e-16
Age
1
114.32
<2e-16
Midline
1
1.13
group: tilt
2
232.83
<2e-16
group: image.type
2
175.28
<2e-16
tilt: age
1
5.28
tilt: midline
1
17.48
.288
.022 2.90E-05
Table 6. Odds ratios (ORs) and their 95% CIs based on regression coefficient ordinal logistic regression from Table 3 Term
OR
Lower 2.5% Bound
group-student
1.1087
0.8776
Upper 2.5% Bound 1.4
groupelayperson
1.3454
1.0894
1.662
Tilt
0.4747
0.4326
0.521
Image typee3D
1.1978
1.0366
1.384
Age
1.0114
1.006
1.017
midlineemodified
1.3699
1.1799
1.59
groupestudent: tilt
1.1238
1.0487
1.204
groupelayperson: tilt
1.5846
1.4906
1.685
groupestudent: image. type-3D
0.4824
0.3931
0.592
groupelayperson: image type-3D
0.2448
0.199
0.301
tilt: age
1.0021
1.0003
1.004
tilt: midline-modified
0.8996
0.8565
0.945
Reference levels: group: dentist, image type: 2D, midline: unchanged.
Evaluating the entire face and personality of a patient is important when planning treatment with extensive restorations.27,34 Psychological factors and subjective preferences of the patient should be considered and incorporated into the treatment planning procedures.27,34 The 3D representations may have eliminated the emotional aspect, while the 2D photograph maintain the emotional component as participants may identify themselves better in a conventional photograph. The objective of incorporating digital technologies such as facial and intraoral scanners and CAD software programs into private practice might be increasing patient communication, facilitating interdisciplinary dialogue, and diagnostic waxing. However, training is needed to visualize 3D representations of patients, and even though 3D representation may provide a powerful diagnostic tool for the clinician, patients may not be able to interpret and visualize the 3D simulation appropriately. Consequently, a more understandable technology selection may be recommended based on the goal of the simulation. However, as 3D representations are more frequently adopted, individual perception will also evolve and adapt to the technology. Interestingly, all the participants preferred the 2D simulations compared
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with the 3D simulations for private practice applications. Further studies are recommended to analyze the differences in dimensional perception differences between dental professionals and laypersons when evaluating different esthetic disparities. CONCLUSIONS Based on the findings of this observational study, the following conclusions were drawn: 1. Dentists, dental students, and laypersons decreased their ratings with increased inclination of the occlusal plane. Observer group ratings gradually diverged from the layperson group, giving consistently higher ratings than the dentists and dental students. 2. Overall, 3D simulations obtained higher ratings than 2D images in dentist and dental student populations, but the positive effect was reversed at higher occlusal plane tilt angles. 3. Dentists provided lower ratings for a lower inclination of the maxillary dental midline in the 2D simulations than dental students, but dental students detected disparities at smaller occlusal plane inclinations than dentists in the 3D simulations. 4. Laypersons graded all the 2D and 3D images as esthetically pleasant. 5. Significant interaction of age and tilt was slight and of little consequence. However, the higher the age of the participants, the higher the ratings.
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