Cargando…

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

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 comprise...

Descripción completa

Detalles Bibliográficos
Autores principales: Sazgar, Tamana, Al-Jaf, Nagham M., Norman, Noraina Hafizan, Alias, Aspalilah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Thieme Medical and Scientific Publishers Pvt. Ltd. 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9949938/
https://www.ncbi.nlm.nih.gov/pubmed/35436793
http://dx.doi.org/10.1055/s-0042-1743149
Descripción
Sumario: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.