Tardivo Delphine, Sastre Julien, Catherine Jean-Hugues, Leonetti Georges, Adalian Pascal, Foti Bruno
Unité Mixte de Recherche 7268 ADES, Aix-Marseille Université-EFS-CNRS, Faculté de Médecine de Marseille, 51 Boulevard Pierre Dramard, 13344, Marseille Cedex 15, France.
UFR d'Odontologie, 27 Boulevard Jean Moulin, 13385, Marseille Cedex 5, France.
J Forensic Sci. 2015 Sep;60(5):1341-5. doi: 10.1111/1556-4029.12821. Epub 2015 Aug 10.
Gender determination is a fundamental issue in forensic anthropology. Many techniques based on bone and dental remains have been proposed. It is not always possible to implement the techniques using bones, but teeth are often perfectly preserved. It has been demonstrated that the canine has the greatest sexual dimorphism, and the aim of this work was to provide an easy and accurate dental technique for determining the gender in the absence of other skeletal elements. The sample was composed of 210 CT scans with four healthy canines. The 840 canines were modeled using MIMICS® 10.01 software. The total volume of each tooth was determined. Seven mathematical models were determined by binary logistic regressions and ranked in order of relative performance. The seven proposed predictive models thus performed (0.910≤AUC≤0.938), with overall rates of correct predictions between 82.38 and 85.24%. The 4-canine model is the most powerful for predicting the gender.
性别鉴定是法医人类学中的一个基本问题。人们已经提出了许多基于骨骼和牙齿遗骸的技术。使用骨骼实施这些技术并非总是可行，但牙齿往往保存得非常完好。已经证明犬齿具有最大的性别二态性，这项工作的目的是提供一种简单而准确的牙齿技术，用于在没有其他骨骼元素的情况下确定性别。样本由210例包含四颗健康犬齿的CT扫描组成。使用MIMICS® 10.01软件对840颗犬齿进行建模。确定了每颗牙齿的总体积。通过二元逻辑回归确定了七个数学模型，并按相对性能顺序进行排名。因此，所提出的七个预测模型的表现（0.910≤AUC≤0.938），正确预测的总体率在82.38%至85.24%之间。四颗犬齿模型在预测性别方面最有效。
