Virtual morphometric method using seven cervical vertebrae for sex estimation on the Turkish population

Sex estimation from skeletal remains is crucial for the estimation of the biological profile of an individual. Although the most commonly used bones for means of sex estimation are the pelvis and the skull, research has shown that acceptable accuracy rates might be achieved by using other skeletal elements such as vertebrae. This study aims to contribute to the development of sex estimation standards from a Turkish population through the examination of CT scans from the seven cervical vertebrae. A total of 294 individuals were included in this study. The CT scans were obtained from patients attending the Bakirkoy Training and Research Hospital (Turkey) and the data was collected retrospectively by virtually taking measurements from each cervical vertebrae. The full database was divided into a training set ( N = 210) and a validation set ( N = 84) to test the fit of the models. Observer error was assessed through technical error of measurement and sex differences were explored using parametric and non-parametric approaches. Logistic regression was applied in order to explore different combinations of vertebral parameters. The results showed low intra- and inter-observer errors. All parameters presented statistically significant differences between the sexes and a total of 15 univariate and multivariate models were generated producing accuracies ranging from a minimum of 83.30% to a maximum of 91.40% for a model including three parameters collected from four vertebrae. This study presents a virtual method using cervical vertebrae for sex estimation on the Turkish population providing error rates comparable to other metric studies conducted on the postcranial skeleton. The presented results contribute not only to the development of population-specific standards but also to the generation of virtual methods that can be tested, validated, and further examined in future forensic cases.