{"title":"A geometric morphometric assessment of the hard tissue external auditory meatus and soft tissue ear of South Africans","authors":"Meg-Kyla Erasmus, Ericka Noelle L’Abbé, Alison Fany Ridel","doi":"10.1016/j.fsir.2023.100331","DOIUrl":null,"url":null,"abstract":"<div><p>Research on how to reliably reconstruct the shape of the ear for facial approximations is limited, especially in countries such as South Africa where standard ear casts are still used in manual methods. To improve objectivity, computer aided methods are being developed for facial approximations – which require extensive population specific datasets for facial feature morphology. This study aims to assess variations in the shape of the ear and the underlying external auditory meatus (EAM) through the analysis of cone-beam computed tomography (CBCT) scans of 40 black South Africans (males n = 17; females n = 23) and 76 white South Africans (males n = 29; females n = 47) between the ages of 18 and 90 years. Shape data was collected by placing 19 capulometric landmarks on the 3D reconstructions of the ear and 46 sliding craniometric landmarks along the EAM. Geometric morphometric analysis revealed highly significant variation in ear shape between groups for population affinity (p-value = 0.001), while sex and age were only significant between the white South Africans (p-value < 0.05). Only population affinity significantly influenced shape in the EAM (p-value = 0.001), and both the ear and EAM showed significant levels of symmetry (p-value = 0.007). While an ear will never be exactly recreated, basing facial estimates on the decedent’s biological profile can lead towards the highest possible accuracies. For the ear shape specifically, sex and age will not be a priority when creating predictive models, but population affinity will greatly influence the output.</p></div>","PeriodicalId":36331,"journal":{"name":"Forensic Science International: Reports","volume":"8 ","pages":"Article 100331"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forensic Science International: Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665910723000269","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Research on how to reliably reconstruct the shape of the ear for facial approximations is limited, especially in countries such as South Africa where standard ear casts are still used in manual methods. To improve objectivity, computer aided methods are being developed for facial approximations – which require extensive population specific datasets for facial feature morphology. This study aims to assess variations in the shape of the ear and the underlying external auditory meatus (EAM) through the analysis of cone-beam computed tomography (CBCT) scans of 40 black South Africans (males n = 17; females n = 23) and 76 white South Africans (males n = 29; females n = 47) between the ages of 18 and 90 years. Shape data was collected by placing 19 capulometric landmarks on the 3D reconstructions of the ear and 46 sliding craniometric landmarks along the EAM. Geometric morphometric analysis revealed highly significant variation in ear shape between groups for population affinity (p-value = 0.001), while sex and age were only significant between the white South Africans (p-value < 0.05). Only population affinity significantly influenced shape in the EAM (p-value = 0.001), and both the ear and EAM showed significant levels of symmetry (p-value = 0.007). While an ear will never be exactly recreated, basing facial estimates on the decedent’s biological profile can lead towards the highest possible accuracies. For the ear shape specifically, sex and age will not be a priority when creating predictive models, but population affinity will greatly influence the output.