Influence of Tooth Morphology on Local Mesh Density Distribution in Intraoral Scanner-Derived STL Models of Selected Maxillary Teeth

Background/Objectives: The quality of intraoral scanner-derived digital models depends not only on deviation-based accuracy, but also on how scanned surfaces are reconstructed into a polygonal mesh. The aim of this prospective within-subject observational study was to evaluate whether tooth morphology influences local mesh density distribution in intraoral scanner-derived STL models of selected maxillary teeth. Methods: Twenty participants underwent maxillary intraoral scanning using a Medit i900 wired intraoral scanner under standardized clinical conditions. For each participant, the buccal surfaces of the maxillary right central incisor (11), canine (13), first premolar (15), and first molar (16) were selected as regions of interest. Surface area (A), number of vertices (V), and number of faces (F) were recorded, and the surface-normalized mesh density parameters vertices per unit area (V/A) and faces per unit area (F/A) were calculated. Comparisons among tooth types were performed using repeated-measures analysis of variance (ANOVA) with Bonferroni post hoc correction. Results: Significant differences were found among tooth types for both V/A and F/A (p < 0.001). Mean V/A values were 18.2 ± 1.9 for tooth 11, 19.8 ± 1.4 for tooth 13, 23.8 ± 1.7 for tooth 15, and 22.9 ± 2.0 vertices/mm2 for tooth 16. Mean F/A values were 34.3 ± 3.6, 37.5 ± 2.7, 44.4 ± 3.3, and 42.9 ± 3.8 faces/mm2, respectively. Post hoc comparisons showed significant differences between teeth 11 and 13, 11 and 15, 11 and 16, 13 and 15, and 13 and 16, whereas no significant difference was observed between teeth 15 and 16. Conclusions: Tooth morphology significantly influenced local mesh density distribution in intraoral scanner-derived STL models of selected maxillary teeth. These findings suggest that local anatomical form affects STL mesh reconstruction under standardized in vivo scanning conditions and support local mesh density analysis as a useful complementary approach to conventional deviation-based digital assessment.