Unveiling the third dimension of tooth shape: 2D versus 3D geometric morphometry of human post-canine dentition.

Introduction: Geometric morphometry is an effective tool for studying teeth morphology for quantifying variations in dental shape across individuals and populations. This study aims to analyse the dimorphism of human post-canine maxillary and mandibular tooth shape by utilising 2D and 3D landmark data and compare the effectiveness of both methods in detecting allometry and shape characteristics.

Methods: Pre-treatment dental casts (N = 160) from patients aged 13-20 were digitised, and 2D and 3D anatomic landmarks on maxillary and mandibular post-canine teeth were marked. The data were evaluated using principal component analysis, discriminant function analysis, and regression analysis of shape coordinates with centroid size using MorphoJ morphometric software.

Results: Principal component analysis revealed that 20-30% of the principal components explained 80% variation in tooth shape. The maxillary second molar and mandibular second premolar had the largest differences in variance between 2D and 3D data. The two-cusp type mandibular second premolar and maxillary second molar displayed the highest variation in 3D analysis. The mandibular second premolar (two-cusp type) had the highest overall accuracy in classifying sex, followed by the maxillary first and second molars.

Conclusion: 3D data collection offers advantages over 2D methods, but it has limitations and trade-offs. It can be time-consuming and expensive and require specialized equipment or software. 2D methods may miss important depth axis variation or capture biological variation. Researchers must carefully consider the benefits and limitations of both methods before choosing. This study provides valuable insight into post-canine tooth shape dimorphism and contributes to existing knowledge in the field.