Estimation of sex from femoral bone using radiological imaging methods in Turkish population.

Abstract

Sex estimation is leading to determine the biological profile in forensic medicine. The aim of this study is to research the effectiveness of logistic regression (LogR) and discriminant function analysis (DFA) to create sex estimation models on femur images obtained with Computed Tomography (CT) angiography and to address the differences of femur, which show sexual dimorphism, among populations. All parameters were measured on three planes by adjusting the 300 CT angiography images from 150 women and 150 men that focused on the left femur to the orthogonal plane with standard magnification. The subgroup, which included 30 images randomly generated from these images, was measured twice with an interval of 3 weeks by the first radiologist and once by the second radiologist. According to the Fisher's Linear Discriminant analysis, which was evaluated with ten parameters in the study, it was concluded that the power of discriminating women was 96.7%, the power of discriminating men was 98.7%, and the total discrimination power was 97.7%; these results were 98%, 99.3%, and 98.7%, respectively according to LogR. In this study, DFA and LogR analysis showed that femur provided a very good rate of sexual dimorphism. A database belonging to the Turkish population was created for the femur, allowing for comparison between populations.