Dental Morphology in Restorative Dentistry: A Pilot Study on Morphological Consistency and Variability in Human Upper First Molars.

Abstract

Background: Geometric morphometric analysis, a methodology traditionally used in evolutionary studies, offers unprecedented precision in quantifying the morphological traits of human organs and tissues by identifying specific anatomical landmarks. Despite its potential, this approach has not yet been applied in medical or dental research. Materials and Methods: This pilot study analyzed 76 permanent upper first molars (M1) from Italian individuals (38 males and 38 females), selected for their completeness, minimal wear (stage 1), and absence of pathological conditions or non-metric traits. Each individual contributed two contralateral molars: the left molar (Group A) and the right molar (Group B). The molars were scanned using a Sinergia Scan Advanced Plus optical scanner with 5 μm accuracy. The scans were processed with the Dental Scan 7.0 software to generate high-resolution STL files, followed by refinement in Meshlab to preserve the morphological integrity of the 3D models. The geometric morphometric analysis was performed using the Viewbox software, thereby enabling the placement of anatomical landmarks and semilandmarks to quantify and compare molar morphology with exceptional precision. Results: The analysis confirmed that contralateral molars exhibit high morphological similarity, with significantly smaller variability compared to molars from different individuals. Among the specific traits analyzed, the distolingual cusp (hypocone) showed the greatest variation, followed by the mesiolingual cusp (protocone). No significant differences were observed between males and females in the degree of similarity between contralateral molars. Conclusions: This pilot study highlights the potential of geometric morphometric approaches to enhance our understanding of the dental variation between sexes and across human populations, thereby improving clinical applications and advancing toward personalized medicine.