Soft-Tissue Analysis of Different Sagittal Skeletal Patterns Using the Geometric Morphometric Method

Author:

Sazgar Tamana12,Al-Jaf Nagham M.3ORCID,Norman Noraina Hafizan1ORCID,Alias Aspalilah4

Affiliation:

1. Centre of Pediatric Dentistry and Orthodontic Studies, Faculty of Dentistry, Universiti Teknologi MARA, Selangor, Malaysia

2. Department of Orthodontics, Faculty of Dentistry, Kabul University of Medical Sciences, Kabul, Afghanistan

3. Centre of Comprehensive Care Studies, Faculty of Dentistry, Universiti Teknologi MARA, Selangor, Malaysia

4. Department of Basic Sciences and Oral Biology, Faculty of Dentistry, Universiti Sains Islam Malaysia, Kuala Lumpur, Malaysia

Abstract

Abstract Objectives This study aimed to investigate the size and shape variations of soft-tissue patterns in different sagittal skeletal patterns using the geometric morphometrics method (GMM) obtained from lateral cephalograms. Materials and Methods This is a retrospective study, where the sample comprised of 188 Malaysian Malay subjects aged between 18 and 40 years and with different sagittal skeletal patterns. Overall, 71 males and 117 females were gathered for all size and shape analyses. This study incorporated 11 soft-tissue landmarks, which underwent landmark application using tpsDig2 software version 2.31, while the shape analysis was done using MorphoJ software version 1.07a. Statistical Analysis Statistical analyses were performed using IBM SPSS Statistics 26. The result of the analysis of variance (ANOVA) test showed significant differences in some of the parameters between the landmarks. Length D, Length E, Length F, Length H, and Length I showed significant differences (p < 0.05), while other parameters showed no difference (p > 0.05). Results The shape variation of soft-tissue landmarks in different skeletal patterns existed in 18 different dimensions which showed by 18 principal components (PCs). Procrustes ANOVA and canonical variate analysis showed the size and shape differences of soft-tissue patterns between Class II and III and gender groups (p < 0.0001). In discriminant function analysis for Class II subjects, the classification accuracy was 98.4%, whereas subsequent to cross-validation, the classification accuracy was 90.6%. For Class III subjects, the classification accuracy was 96.6%, while after cross-validation, the classification accuracy was 90%. Conclusion Different sagittal skeletal patterns demonstrated different soft-tissue shape variations. Class III showed the most protrusive upper and lower lips, while Class II demonstrated the most retrusive lower lip.

Publisher

Georg Thieme Verlag KG

Subject

General Dentistry

Reference33 articles.

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