Oriasotie M Ujaddughe , Jenny Haberfeld , Mubarak A Bidmos , Oladiran I Olateju
{"title":"Cranial measurements obtained by three-dimensional computed tomography technique in the estimation of sex of contemporary Black South Africans","authors":"Oriasotie M Ujaddughe , Jenny Haberfeld , Mubarak A Bidmos , Oladiran I Olateju","doi":"10.1016/j.fri.2024.200585","DOIUrl":null,"url":null,"abstract":"<div><p>Human identification forms an integral part of forensic and biological anthropology. For proper identification, a biological profile made up of biodata such as age, sex, ancestry, antemortem stature, and factors of individualization, is obtained and stored for use by anthropologists. A correct sex estimation can help unravel other anthropological parameters. South Africa has a multi-dimensionally high crime rate and its largest distinct population group (Black South Africans) is most affected by such crimes. Several authors have in the past used cranial measurements to carry out sex discrimination among South Africans, such attempts have largely been done using direct assessment of post-mortem specimens and on subjects of European Descent. This study, therefore, attempted to overcome these drawbacks by using a non-invasive method, the three-dimensional computed tomography (3DCT) to obtain population-specific data from a contemporary Black South African population group. It obtained measurements from cranial CT records of 350 Black South Africans (50 % sex ratio) housed in the Radiology Department of Charlotte Maxeke Johannesburg Academic Hospital. The Xiris and IntelliSpace software were used to reconstruct the images into three-dimensional forms from which measurements were taken. Evaluation of previously derived equations using data from the current study yielded low average classification accuracies which necessitated the formulation of new equations. Discriminant function analysis yielded acceptably high average classification accuracies for sex estimation which ranged from 78.3 % to 82.9 %.</p></div>","PeriodicalId":40763,"journal":{"name":"Forensic Imaging","volume":"37 ","pages":"Article 200585"},"PeriodicalIF":0.8000,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forensic Imaging","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666225624000095","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Human identification forms an integral part of forensic and biological anthropology. For proper identification, a biological profile made up of biodata such as age, sex, ancestry, antemortem stature, and factors of individualization, is obtained and stored for use by anthropologists. A correct sex estimation can help unravel other anthropological parameters. South Africa has a multi-dimensionally high crime rate and its largest distinct population group (Black South Africans) is most affected by such crimes. Several authors have in the past used cranial measurements to carry out sex discrimination among South Africans, such attempts have largely been done using direct assessment of post-mortem specimens and on subjects of European Descent. This study, therefore, attempted to overcome these drawbacks by using a non-invasive method, the three-dimensional computed tomography (3DCT) to obtain population-specific data from a contemporary Black South African population group. It obtained measurements from cranial CT records of 350 Black South Africans (50 % sex ratio) housed in the Radiology Department of Charlotte Maxeke Johannesburg Academic Hospital. The Xiris and IntelliSpace software were used to reconstruct the images into three-dimensional forms from which measurements were taken. Evaluation of previously derived equations using data from the current study yielded low average classification accuracies which necessitated the formulation of new equations. Discriminant function analysis yielded acceptably high average classification accuracies for sex estimation which ranged from 78.3 % to 82.9 %.