Identification of the human body or remains after death is a forensic procedure which is difficult to perform and is mandatory by law and in compliance with social norms. Sexing the recovered human remains is an integral part of the identification process. The utilization of radiological imaging methods in anthropometric studies is being expanded by the application of modern imaging methods, leading to a decrease in costs, time, and the ability to create three-dimensional images. It is widely accepted that using population-specific criteria to estimate biological traits in the human skeleton improves accuracy. The present study investigated three-dimensional (3D) computed tomography images of 274 individuals (183 males and 91 females) within the 1884 years age group (Mean age: 43.13 ± 17.23) for sex determination. A total of 16 anthropometric parameters were taken into consideration. Logistic regression analysis (LRA), multiple logistic regression, univariate, multivariate, and stepwise discriminant function analysis (DFA) were generated to establish the accuracy of the cranial parameters. The morphometric measurements of the skull revealed that the most dimorphic structure was the bizygomatic breadth, which emerged as the best predictor of sex, with an accuracy of 80.7% with LRA and 81.2% with univariate DFA. Our study evaluates sexual dimorphism in an Indian population using CT skull images, incorporating cranial measurements, logistic regression, and univariate and multivariate analyses to develop an anthropometric approach for sex determination. The uniqueness of this research lies in its focus on the Indian population, where morphological variations may differ from other populations. By refining established CT-based sex determination methods and incorporating advanced quantification techniques, we aim to enhance the accuracy of sex determination in this population.
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Mohammed Akbar
Raghvendra Singh Shekhawat
Tanuj Kanchan
All India Institute of Medical Sciences
All India Institute of Medical Sciences Jodhpur
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Akbar et al. (Fri,) studied this question.
www.synapsesocial.com/papers/68c6df6933b72be0b5e43c7a — DOI: https://doi.org/10.1127/anthranz/1811
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