|Year : 2022 | Volume
| Issue : 4 | Page : 857-863
Comparative evaluation of various parameters of spontaneous smile captured by conventional photographic method, video clip method, and direct biometric method
Department of Orthodontics and Dentofacial Orthopaedics, K. M. Shah Dental College and Hospital, SVDU, Vadodara, Gujarat, India
|Date of Submission||09-Apr-2021|
|Date of Acceptance||10-Jun-2022|
|Date of Web Publication||10-Feb-2023|
Dr. Romilkumar Shah
5/A Kalrav, Panchratna Society, Gorwa Refinery Road, Vadodara - 390 016, Gujarat
Source of Support: None, Conflict of Interest: None
Introduction: Facial and dental attractiveness can significantly impact one's life. As per Kiekens, smile esthetics contributed 25%–31% to facial attractiveness. Smile is one of the most effective means by which people convey their emotions. People have more positive acceptance and better behavior against attractive faces; this phenomenon is called “attractiveness halo”. The records needed for contemporary smile visualization and quantification can be static records (static photograph and/or lateral cephalogram), dynamic record (digital videography), and direct biometric/clinical measurements. Previous studies examining smile esthetics had used static photographs. Recently, a method of capturing and analyzing the smile using videography and computer software becomes need of an hour. Aim: Comparative evaluation of various parameters of spontaneous smile captured by conventional photography method (CPM), video clip method (VCM), and direct biometric method (DBM). Materials and Methods: The subjects were screened clinically and based on normal soft tissue profile angle in the profile photographs. Smile photographs of the subjects were obtained using conventional photography technique. VCM was used to capture spontaneous smiles of the subjects using the same camera. Finally, the parameters of the smile were directly measured on the subjects using Vernier calipers. Images were standardized and subjected to appropriate analyses to evaluate smile arc, buccal corridor, lower incisal display, upper gingival display, smile index, Morley's ratio, and smile line. Results: Measurements of smile arc, buccal corridor, lower incisal display, upper gingival display, smile index, Morley's ratio, and smile line on the photographs obtained from CPM showed statistically significant differences when compared to both VCM and DBM. Conclusion: As VCM is better able to capture and assess spontaneous smile when compared to CPM, it is the preferred method along with DBM as additional confirmation.
Keywords: Conventional photographic method, direct biometric method, spontaneous smile, video clip method
|How to cite this article:|
Shah R. Comparative evaluation of various parameters of spontaneous smile captured by conventional photographic method, video clip method, and direct biometric method. J Datta Meghe Inst Med Sci Univ 2022;17:857-63
| Introduction|| |
Facial and dental attractiveness can significantly impact one's life. As per Maniyar, smile esthetics contributed 25%–31% to facial attractiveness. According to Hulsey, smile is one of the most effective means by which people convey their emotions. The desire for an attractive smile and improved esthetics often motivate persons in modern society to seek orthodontic treatment. People have a positive acceptance and better behavior against attractive faces; this phenomenon is called “attractiveness halo.”
Smile analysis is a part of a facial analysis and allows recognizing positive and negative elements in each patient's smile. Since most of the patient's decision to undertake orthodontic treatment is based primarily on the esthetic considerations, the evaluation of factors that influence their smile is the necessity of the present time.
The records needed for contemporary smile visualization and quantification can be static records (static photograph and/or lateral cephalogram), dynamic record (digital videography), and direct biometric/clinical measurements.
Previous studies,,, examining smile esthetics had used static photographs. Recently, a method of capturing and analyzing the smile using videography and computer software was described. Ackerman and Ackerman and Sarver and Ackerman, were the first to use videography to analyze smile. Tarantili et al. conducted a video graphic study to record dynamic nature of spontaneous smile. Maulik and Nanda established dynamic norms using a videographic method.
The aim of the present study was to evaluate and compare various parameters [Table 1] of spontaneous smile captured by conventional photography method (CPM), video clip method (VCM), and direct biometric method (DBM).
Need of the study
After appraising the literature, very few studies, were found evaluating and comparing various parameters of spontaneous smile captured by CPM, VCM, and DBM within the same subjects. As smile esthetics has a very important role in orthodontic diagnosis and treatment planning, assessment of predictable, standardized, and spontaneous smile by most reliable method becomes a need of the hour.
Comparative evaluation of various parameters of spontaneous smile captured by CPM, VCM, and DBM.
- To evaluate various parameters of spontaneous smile captured by CPM
- To evaluate various parameters of spontaneous smile captured by VCM
- To evaluate various parameters of spontaneous smile captured by DBM
- To compare various parameters of spontaneous smile captured by CPM, VCM, and DBM.
| Materials and Methods|| |
Place of the study
Department of Orthodontics and Dentofacial Orthopaedics, K. M. Shah Dental College and Hospital (KMSDC&H), Sumandeep Vidyapeeth.
Source of sample
Dental students, KMSDC&H, SVDU.
The sample size was estimated, following pilot study assessment of inclusion criteria (normal overjet and overbite, well-aligned anteriors, and pleasing profile) among the eligible subjects, using the following formula:
- Zα is value of Z for α = 0.05 (95% confidence interval)
- Zβ is value of Z, when power of study is assumed to be 80%
- p is the proportion of subjects eligible for the study according to the inclusion criteria in the population (obtained from pilot study sample - 44%)
- d is the assumed difference in percentage of flat smile arcs for the three different techniques of smile assessment (20% in this case)
As all the three methods of assessment were used in all the participants, the minimum sample size required for the study was 97. The total number of participants of this study was 100.
- Age: 17–25 years
- Well-aligned anterior teeth
- Presence of all permanent teeth except third molars
- Normal overjet and overbite
- Pleasing profile.
- History of previous orthodontic treatment
- Congenital anomalies/defects
- Facial asymmetry/disharmony
- Periodontal disease
- Facial muscular imbalances
- History of facial trauma, plastic surgery, or orthognathic surgery.
Subjects for the study were selected from the students of K. M. Shah Dental College and Hospital, Sumandeep Vidyapeeth. The subjects were screened for the inclusion criteria. The subjects fulfilling the criteria were introduced to the aim, objectives, and need of the study with the help of participant information sheet. If the subject agreed to participate in the study, a signed informed consent form was obtained from the subject.
Determination of overjet and overbite
The subjects were screened clinically to check for the overjet and overbite. Subjects having normal overjet (2–4 mm) and normal overbite (2–4 mm) were considered for this study.
Determination of pleasing profile
A photograph of the subject was obtained in the profile view [Figure 1] and analyzed for the soft tissue profile angle using the Burstone's method. The analysis was done using the soft tissue points: glabella (G), subnasale (Sn), and soft tissue pogonion (Pg). The subjects having values in normal range (165°–175°) were shortlisted as fit for the study.
Materials/Equipment required for the study
- CanonEOS 200D DSLR with 18–55 macro lens
- Check retractor
- Vernier caliper
- Adobe Photoshop Software
- Samsung Gear VR (SM-R322) [Figure 2].
Conventional photography method
A standardized photograph of spontaneous smile was obtained in the photographic area of the department under quality lighting. As shown in [Figure 3], the participant was made to sit erect on a stool. The position of the camera was fixed on a tripod and positioned such that the distance between the camera lens and the subject was 36 inches. The vertical positioning of the tripod was adjusted according to the subject in such a way the lens of the camera was parallel to their apparent occlusal plane and would be focused only on dentofacial complex. Photographic umbrella was utilized for adequate illumination. The photographs were taken using CanonEOS 200D DSLR with 18–55 macrolens having 24.2 megapixels and CMOS-type image sensor having a size of 22.3 × 14.9 mm with a maximum output resolution of 6000 × 4000. All the images were captured in portrait mode without zoom. A ruler was fixed vertically on the wall behind the subject, within the photographic field, for image calibration. The subjects were instructed to hold the head in natural head position by making them wear glasses having fluid level device. Before clicking the smile photograph, subjects were instructed to smile to the maximum. All the standardized photographs captured were transferred to the computer software (Adobe Photoshop, version 8, Adobe system, San Jose, CA, USA).
Video clip method
The standardized setup used for clicking the smile photographs was utilized to record dynamic range of spontaneous smile for each subject. To obtain this smile, the subjects were asked to wear the Samsung Gear VR (SM-R322), which was a virtual reality eye gearbox. While the gear was on, a funny video clip was played in the box to initiate smile in the subject. A 1 min video clip, when in the act of smile, was recorded for each subject on the same camera as used for capturing the standardized photographs. The captured video clip was transferred to the video editing software program. A frame from the video showcasing widest commissure-to-commissure smile was selected as posed smile for the further analysis, as depicted in [Figure 4].
Direct biometric method,
The patients were made to sit in a comfortable position, and the required parameters of spontaneous smile were measured clinically with the help of a Vernier caliper.
Standardization of image
The present study used the method given by Desai et al. to standardize the image. First, the resolution was changed to 300 pixels per inch by going to “Image > Image Size.” Then, the ruler function was chosen and set to millimeter which can measure a minimum of 0.1 mm length. The image ratio of 1:1 was maintained for the calibration of all images.
Ethical Approval- SVIEC/ON/Dent/RP/19027 was provided by Sumandeep Vidyapeeth Institutional Ethical Committee (SVIEC) on 12-11-2019.
| Observations and Results|| |
[Table 2] and [Chart 1] show that VCM (26%) and DBM (29%) recorded flatter smiles more than CPM (14%). Reverse smile of 16% was recorded by VCM, 17% by DBM and 12% by CPM as shown in [Table 2] and [Chart 1]. The Buccal Corridor percentage was recorded more in VCM (19.63%) and DBM (19.42%) compared to CPM (16.33%). [Chart 2], [Chart 3] and [Chart 4] depicts that VCM records more vertical dimension as the lower incisor display is greater in smiles recorded via VCM (2.56 mm) and DBM (2.08 mm). And the least vertical dimension was recorded in CPM (1.45 mm). The Smile Index readings were highest for VCM 6.47, followed by DBM 6.34 and least in photographs obtained by CPM 4.48.
|Table 2: Comparison of smile arc between conventional photographic method, video clip method, and direct biometric method|
Click here to view
| Discussion|| |
Smile assessment becomes an integral part of orthodontic diagnosis and treatment planning. For smile capturing, an orthodontist has to use the most accurate and reliable method in day-to-day practice. In CPM, only one frame is available at a time; it is difficult to ensure that that particular frame has captured the best spontaneous smile. In contrast, in digital VCM, since many frames are captured, it becomes possible to choose the frame with widest spontaneous smile with the help of computer software. In the present study, there was no separate comparative evaluation between males and females.
According to [Table 2] and [Chart 1], the number of consonant smile in CPM (74%) decreased to 58% in VCM and 54% in DBM. The number of flat smile in CPM (14%) increased to 26% in VCM and 29% in DBM. The number of reverse smile in CPM (12%) increased to 16% in VCM and 17% in DBM. This result indicates that the smile arcs had become flatter with VCM and DBM compared to CPM. This agrees with the findings of Tjan et al. and Dong et al. (CPM) and Tarantili et al. (VCM), who found the consonant smile/parallel smile arc to be most frequent in their subjects. Thus, we were in agreement with flatter smile arc using VCM and DBM. In contrast, our percentages of flat smile arc with VCM were lower than that reported by Maulik and Nanda.
According to [Table 3] and [Chart 2], the buccal corridor percentage in CPM (16.33%), VCM (19.63%), and DBM (19.42%) indicates a statistically significant difference between CPM with other two methods. Moore et al. observed that having minimal buccal corridor is a preferred esthetic feature. They classified buccal corridor percentage as narrow (28%), medium-narrow (22%), medium (15%), medium-broad (10%), and broad (2%). The BC% in their study ranged between 28% and 2%. In our study, it ranged from 23% to 13% that is between medium-narrow to medium as per Moore's Classification.
|Table 3: Comparison of linear measurements between Conventional Photographic Method, Video Clip Method and Direct Biometric Method|
Click here to view
According to [Table 3] and [Chart 3], [Chart 4], the lower incisor display increased from CPM (0.7 mm) to VCM (2.29 mm) and DBM (1.80 mm), indicated more vertical smile recording with VCM. Similar findings were recorded with upper gingival display. It increased from CPM (1.45 mm) to VCM (2.56 mm) and DBM (2.08 mm), indicated more vertical smile recording with VCM. Our results were similar with the study done by Singh et al. and Husain et al..
According to [Table 3] and [Chart 5], the smile index showed a highly significant difference between CPM with other two methods. The SI increased from 4.48 in CPM to 6.47 in VCM and 6.34 in DBM. Our results concur with those of Desai et al., who reported SI (6.73) with VCM.
According to [Table 4] and [Chart 6], when we estimated smile line with all three methods, the results showed more gingival recording of smile line with VCM, followed by DBM and finally photographic method. This indicates more vertical smile recording with VCM.
|Table 4: Comparison of smile line between conventional photographic method, video clip method, and direct biometric method|
Click here to view
One of the vertical aspects of smile anatomy is degree of maxillary anterior tooth display, called Morley's ratio. In a youthful smile, 75%–100% of the maxillary central incisors should be positioned below an imaginary line drawn between the commissure. It can be inadequate, acceptable, or excessive. According to [Table 5] and [Chart 7], the VCM recorded more youthful smile compared to other two methods, made it preferable.
|Table 5: Comparison of Morley's ratio between conventional photographic method, video clip method, and direct biometric method|
Click here to view
| Conclusion|| |
It was found that all the measured parameters (smile arc, buccal corridor ratio, lower incisor display, upper gingival display, modified smile index, Morley's ratio, and smile line) showed differences when assessed by CPM, VCM, and DBM.
Many orthodontic treatment modalities are based on an analysis of the full spontaneous smile, and since the VCM is better able to capture that smile, it may be a preferred method for smile assessment along with DBM for additional confirmation.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Maniyar M, Kalia A, Mirdehghan N, Nene S, Bhagwagar P. Evaluation of the influence of gingival display on smile esthetics in Indian females – A computer-aided photographic analysis. J Indian Orthod Soc 2018;52:100-5. [Full text]
Tarvade SM, Agrawal G. Smile analysis: A review Part I. Int J Contemp Dent Med Rev 2015;2015:1-4.
Singla S, Lehl G. Smile analysis in orthodontics. Indian Journal of Oral Sciences 2014;5:49-54.
Hulsey CM. An esthetic evaluation of lip-teeth relationships present in the smile. Am J Orthod 1970;57:132-44.
Tjan AH, Miller GD. Some esthetic factors in a smile. J Prosthet Dent 1984;51:24-8.
Peck S, Peck L, Kataja M. The gingival smile line. Angle Orthod 1992;62:91-100.
Dong JK, Jin TH, Cho HW, Oh SC. The esthetic of the smile: A review of some recent studies. Int J Prosthodont 1998;11:246-54.
Ackerman JL, Ackerman MB, Brensinger CM, Landis JR. A morphometric analysis of the posed smile. Clin Orthod Res 1998;1:2-11.
Sarver DM, Ackerman MB. Dynamic smile visualization and quantification: Part 1. Evolution of the concept and dynamic records for smile capture. Am J Orthod Dentofacial Orthop 2003;124:4-12.
Sarver DM, Ackerman MB. Dynamic smile visualization and quantification: Part 2. Smile analysis and treatment strategies. Am J Orthod Dentofacial Orthop 2003;124:116-27.
Tarantili VV, Halazonetis DJ, Spyropoulos MN. The spontaneous smile in dynamic motion. Am J Orthod Dentofacial Orthop 2005;128:8-15.
Maulik C, Nanda R. Dynamic smile analysis in young adults. Am J Orthod Dentofacial Orthop 2007;132:307-15.
Singh N, Abdulla R, Sable R, Bhosale V, Halli R. Smile analysis: A comparison between photographic and Videographic methods. J Indian Orthod Soc 2016;50:8-13. [Full text]
Desai S, Upadhyay M, Nanda R. Dynamic smile analysis: Changes with age. Am J Orthod Dentofac Orthop 2009;136:310-e1-10.
Schabel BJ, Baccetti T, Franchi L, McNamara J. A clinical photography vs. digital videoclips for the assessment of smile esthetics. Angle Orthod 2010;80:490-6.
Morley J, Eubank J. Macro-esthetic elements of smile design. J Am Dent Assoc 2001;132:39-45.
Liébart MF, Fouque-Deruelle C, Santini A, Dillier FL, Monnet-Corti V, Glise JM, Borghetti A. Smile line and periodontium visibility. Periodontal practice today 2004;1:17-25.
Moore T, Southard KA, Casko JS, Qian F, Southard TE. Buccal corridor and smile aesthetics. Am J Orthod Dentofac Orthop 2005;127:208-13.
Husain A, Makhija P, Ummer A, Marie A, Mette AR. Three-camera setup to record simultaneously standardized high-definition video for smile analysis. Am J Orthod Dentofac Orthop 2017;152:711-6.
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]