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Updated: Jan 9, 2026

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
Published on: September 8, 2023
Sex Determination Based on Posterior Mandibular Measurements using Three-Dimensional Cone-Beam Computed Tomography
Nikolaos Christoloukas1, Anastasia Mitsea2, Leda Kovatsi3
1Department of Oral Diagnosis and Radiology, School of Dentistry, National and Kapodistrian University of Athens, 2 Thivon Str, 115 27, Athens, Greece.
Abstract:
The objective of this study was to evaluate the reliability and predictive ability of specific anthropometric mandibular measurements on three-dimensional (3D) reconstructed surfaces of cone-beam computed tomography (CBCT) records for sex determination. The study sample analyzed volumetric data from cone-beam computed tomography (CBCT) records of 204 Greek individuals aged 18-70 years, who sought general dental treatment at the School of Dentistry, National and Kapodistrian University of Athens, Greece. Patient records were screened for eligibility based on predefined inclusion criteria. The sample was distributed by sex and further categorized into four distinct age groups. Volumetric data of 204 patients (equally distributed between sexes) were reprocessed with the ViewBox 4 software, according to inclusion-exclusion criteria. Ten anatomical landmarks visible on three-dimensional CBCT reconstructions were digitally traced using the ViewBox 4 software, including superior points of the right and left condyles, the most proximal points of the inner poles of the right and left condyles, the inferior points of the right and left sigmoid notches, the superior points of the right and left coronoid processes and the right and left Gonion. This cross-sectional study employed a binary logistic regression (BLR) model for statistical analysis. All linear parameters exhibited statistically significant differences between sexes whereas angular measurements did not demonstrate a statistically significant difference. The developed model yielded an accuracy of 83.4% in predicting sex. Specific linear measurements are reliable predictors of sex and may be applied in forensic science as a supplementary method.

