How Does the Mandible Age? Comprehensive Artificial Intelligence-Assisted Shape Analysis in the White Population.

Abstract

Background: Mandible contour significantly influences facial appearance, framing the lower facial silhouette. Redefining mandibular contour is key for facial and neck rejuvenation. Yet, there is limited facial aging research across different lifespans and sexes. Here, we utilize artificial intelligence and advanced 3-dimensional (3D) analysis to elucidate mandibular aging patterns in male and female subjects.

Methods: A retrospective analysis of facial computed tomography scans in White patients was conducted, categorizing subjects into 3 age groups (20-79 y) and stratifying them by sex. Artificial intelligence-assisted segmentation into 3D mandibles was done in Mimics v.25, and statistical shape modeling was used to create an average mandible for each group. Volume and linear measurements were assessed via 3D overlays.

Results: Analysis of 280 mandibles demonstrated statistically significant aging changes in both sexes. Ramus height showed a marked decrease with age, by approximately 5.3 mm in women and 4.2 mm in men (P < 0.001). Interrami and intercondylar widths increased by a mean of 4-5 mm (P < 0.01). Women exhibited an increase in mandibular angle (P < 0.01), and bony resorption over the chin compared to men, who exhibited concentrated bone resorption at the gonion projection.

Conclusions: Mandibular aging, independent of tooth loss, exhibits specific bone remodeling patterns by sex. Posteriorly, mandibular widths increase in both sexes, whereas ramus height decreases. Women experience more resorption at the anterior alveolar surface and chin than men. Statistical shape modeling effectively visualizes these patterns on a population level, bridging the gap between traditional aging research and current understanding.