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• Sexual dimorphism in a South African Black sample of cone beam computed tomography (CBCT)-derived lateral cephalograms • Multivariate discriminant function analysis on linear distances using imaging • Cephalometric techniques as complementary tools for forensic sex estimation : Identification of unknown individuals is a fundamental role of forensic anthropology, particularly in contexts where traditional methods such as DNA, fingerprints, and dental records are unavailable. Cephalometry is an alternative contemporary technique used to estimate sex, having high classification accuracy compared to conventional osteometric methods. This is the first study aimed to explore sexual dimorphism in a South African Black sample of cone beam computed tomography (CBCT)-derived lateral cephalograms. : This cross-sectional quantitative study analysed 79 CBCT-derived lateral cephalograms of adult Black South Africans. Lateral cephalograms were reconstructed in Avizo software. Ten 2D landmarks were identified and 12 linear distances derived. Univariate tests, as well as multivariate discriminant function analysis (direct and jackknifed) on linear distances and 2D landmarks were performed using Past software. : Linear distances were larger in males than females for all variables and significant for Ba-Pr, Ba-N, S-N, N-ANS, ANS-PNS, S-Ba, A-point to B-point, A-point to Go, B-point to Go. Discriminant analysis of six variables with greater loadings achieved 72.15% jackknifed classification accuracy while four key 2D landmarks (S, Me, Go, Ba) yielded a 74.68% jackknifed classification accuracy. Wireframe analysis confirmed male mandibles as larger and more anteriorly projecting, with a more anteriorly positioned nasion. : CBCT-derived lateral cephalograms effectively demonstrate sexual dimorphism in a Black South African population. Classification accuracies improved when focusing on variables with the highest discriminative power. These findings highlight the potential of cephalometric techniques as complementary tools for forensic sex estimation, with implications for building population-specific reference databases.
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Kobedi et al. (2026) studied this question.
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