Quantifying human mandibular asymmetry using dense surface mapping

Background: Mild facial asymmetry is common in orthodontic patients, particularly within the mandible. However, its quantification is challenging due to reliance on subjective assessment and traditional methods that depend on reference planes and sparse landmark measurements. The Dense Correspondence Analysis (DeCA) enables surface-based comparison of three-dimensional structures and may provide a more comprehensive approach to quantifying mandibular asymmetry. Purpose: To quantify global and regional mandibular asymmetry in a pre-orthodontic pediatric population using DeCA and to evaluate its association with age, sex, and Angle’s classification of malocclusion. Research Design: CBCT scans from 163 orthodontic patients aged 7–11 years were analyzed. Mandibles were segmented from CBCT volumes and annotated with key anatomical landmarks, before applying the DeCA pipeline to generate asymmetry heatmaps and regional asymmetry scores for the condyle, coronoid process, ramus, body, gonial angle, and chin. Principal component analysis (PCA) was used to identify dominant patterns of asymmetry, and statistical analyses were performed to evaluate associations with demographic and occlusal variables. Results: Mandibular asymmetry demonstrated a positively skewed distribution, with most individuals exhibiting mild to moderate asymmetry and a smaller subset showing higher asymmetry scores. Regional analysis revealed the greatest mean asymmetry in the coronoid process and gonial angle, while the ramus and midbody were comparatively stable. PCA identified distinct patterns of asymmetry: PC1 (32% variance) reflected global asymmetry across the mandible, whereas PC2 (18% variance) contrasted ramus–body asymmetry with condylar–coronoid asymmetry. No significant differences were found between global asymmetry or PCA-derived components and age, sex, or Angle’s malocclusion classification. However, a mild association was observed between higher mandibular asymmetry scores and dental asymmetry ≥1 cusp width. Conclusion: DeCA provides a reproducible framework for high-resolution quantification of mandibular asymmetry. In the pre-orthodontic population studied here, asymmetry appears to represent a skew-distributed biological trait rather than being strongly associated with demographic or occlusal variables. Regional differences suggest that asymmetry may be influenced by localized growth and functional factors, particularly in areas associated with muscle attachment. The data also suggests that occlusal asymmetry may reflect underlying right-left dental variations, in some patients.