Age estimation in adults is a complicated task because of various external factors occur concurrently with increasing age. The geometric morphometric method (GMM) is an approach that focuses on shape analysis and is widely recognized for its high reliability and reproducibility. The aim of this study was to explore the variation of cervical vertebrae among different age groups of the Malaysian population by GMM. Lateral skull radiographs of 432 subjects comprising four adult age groups; young adult age group (20–30 years old), early middle age group (31–40 years old), late middle age group (41–50 years old) and, elder adult age group (51–60 years old) were selected. Fifty-three 2-dimensional (2D) landmarks were applied to the digitalized radiographs by TPSDig2 (Version 2.31) software. Geometric morphometric analysis was performed by MorphoJ software. Results showed that the first three principal components (PC) contributed to 47.71 % of the cervical vertebrae variation and were shown in both lollipop and wireframe graphs. Procrustes ANOVA indicated that the shape was significantly different among different age groups. Canonical variate analysis revealed significant differences of both mahalanobis and procrustes distances among age groups with substantial individual overlap within groups. Discriminant function analysis (DFA) showed a correct classification rate for 61.5 % of cases respective to age groups. In conclusion, this study found significant differences in the shape of cervical vertebrae among different age groups of the Malaysian population using the GMM.

Geometric morphometrics is a new approach for shape identification in diagnosis of malocclusion. Lateral cephalogram is an X-ray that taken for diagnosing malocclusion in dental setting. The aim of this study was to determine the differences of craniofacial shape in malocclusion by application of two-dimensional geometric morphometrics and to compile the database of malocclusion in adult Malaysian population. Lateral cephalogram radiographs of 381 adults Malaysia (age 18-45) were retrieved retrospectively and assigned to three groups according to their occlusion: class I, class II, and class III. The geometric morphometric shape study incorporated nine landmarks and was analyzed in details using tpsUtil p software. Geometric morphometric analysis such was done using MorphoJ software. The results of the principal component's analysis (PCA) yielded 14 main components responsible for 100% of the variation exhibited by the malocclusion with three highly significant PCA. The highest Mahalanobis distances were exhibited by the malocclusion class II and III population. The Procrustes ANOVA showed that the shape effect was highly significant (P<0.01). The discriminant function analysis showed the high percentage of 80% discriminate among the malocclusions after cross-validation. There are significant differences for ANB angle (A point-Nasion-B point) in all malocclusion groups. Class II has the widest ANB angle while class III has the most acute ANB angle. Skeletal shape was clearly associated with dental malocclusion and showed considerable variation. Geometric morphometrics is an alternative research tool and can be used for diagnosing individual classification of malocclusion.

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.