Mandibular sexual dimorphism analysis in CBCT scans

• The logistic regression was used to selection of measures: RL, GA, BicBr, BigBr.
• Combining the four variables, a concordance index of 95.1% was found.
• The success of estimating the sex was 92.96% for females and 85.45% for males.
• Values used to test the formula had an accuracy of 93.33% (males) 94.74% (females).

The aim of this study was to evaluate sexual dimorphism using anthropometric measurements on mandibular images obtained by cone beam computed tomography (CBCT). The sample consisted of 160 CT scans collected from a Brazilian population (74 males, 86 females) aged 18–60 years. The CBCT images were analyzed by five reviewers. Six measurements (ramus length, gonion–gnathion length, minimum ramus breadth, gonial angle, bicondylar breadth, and bigonial breadth) were collected for the sexual prediction analysis. For the statistical analysis, intraclass correlation was used to evaluate intra- and inter-reviewers, analysis of variance was used to compare the mean values of these measurements, binary logistic regression equations were created to predict sex. Using these four variables, the rate of correct sex classification was 95.1%. After, the discriminant function was used to validate the formula built. Accuracy of 93.33% and 94.74% was found for estimating male and females, respectively. Thus, the formula developed in this study can be used for sex estimation in forensic settings.