Determination of Gender from Sternal Measurements Using Computed Tomography Imaging in a Sample of Sohag Governorate Population.

Elsayed, Reda Mohammed; Soliman, Soheir Ali; Said, Ahmed Mohammed; Allam, Shimaa Ali

doi:10.21608/zjfm.2022.127310.1109

Determination of Gender from Sternal Measurements Using Computed Tomography Imaging in a Sample of Sohag Governorate Population.

Document Type : Original Article

Authors

¹ department of forensic medicine and clinical toxicology, faculty of medicine, Sohag university

² department of forensic medicine and clinical toxicology, faculty of medicine, sohag university

³ department of forensic medicine and clinical toxicology , faculty of medicine, sohag university

10.21608/zjfm.2022.127310.1109

Abstract

Personal identification of unknown human remains is one of the most important roles in any forensic investigation. Sex identification can be determined either from their anthropometry or radiography especially in complicated cases as dismemberments, disfigurement and explosions. Objectives: The present work was performed to investigate the probability of determination of sex from various sternal measurements through Multi- detector Computed Tomography imaging. Methodology: The present work included 100 adult participants attended Sohag University Hospitals during the period from January 2020 to December 2020, 50 were males, and 50 were females who performed chest Computed Tomography (C.T. ). Results: A significant statistical increase in the mean values of all sternal measurements in males as compared to females except sternal index. Discriminant function equations and cross-validated classification accuracies is calculated to predict correct percentage of sex. The correct percentage of sex prediction was 88% in males and 92% in females and 90% of overall sex percent. For each measurement, determination of the cut-off value between sensitivity and specificity showed that sternal body length and combined length were the most specific and sensitive with accuracy 100% to discriminate between both genders. Conclusion: Multi- detector Computed Tomography imaging revealed that the sternal body length and combined length were the best discriminate variables between genders with overall accuracy of 100% both females and males.

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