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马来西亚未成年人的颅测量性别估计:一项计算机断层扫描研究。

Sex estimation of Malaysian sub-adults using craniometrics: A computed tomography study.

机构信息

Department of Oral and Craniofacial Sciences, Faculty of Dentistry, Universiti Malaya, Malaysia.

Department of Oral and Maxillofacial Clinical Sciences, Faculty of Dentistry, Universiti Malaya, Malaysia.

出版信息

Leg Med (Tokyo). 2023 Sep;64:102275. doi: 10.1016/j.legalmed.2023.102275. Epub 2023 May 21.

Abstract

Sex estimation is crucial in biological profiling of skeletal human remains. Methods used for sex estimation in adults are less effective for sub-adults due to varied cranium patterns during the growth period. Hence, this study aimed to develop a sex estimation model for Malaysian sub-adults using craniometric measurements obtained through multi-slice computed tomography (MSCT). A total of 521 cranial MSCT dataset of sub-adult Malaysians (279 males, 242 females; 0-20 years old) were collected. Mimics software version 21.0 (Materialise, Leuven, Belgium) was used to construct three-dimensional (3D) models. A plane-to-plane (PTP) protocol was utilised to measure 14 selected craniometric parameters. Discriminant function analysis (DFA) and binary logistic regression (BLR) were used to statistically analyze the data. In this study, low level of sexual dimorphism was observed in cranium below 6 years old. The level was then increased with age. For sample validation data, the accuracy of DFA and BLR in estimating sex improved with age from 61.6% to 90.3%. All age groups except 0-2 and 3-6 showed high accuracy percentage (≥75%) when tested using DFA and BLR. DFA and BLR can be utilised to estimate sex for Malaysian sub-adult using MSCT craniometric measurements. However, BLR showed higher accuracy than DFA in sex estimation of sub-adults.

摘要

性别鉴定对于骨骼遗骸的生物特征分析至关重要。由于在生长期间颅骨模式存在差异,用于成年人的性别鉴定方法对于未成年人的效果较差。因此,本研究旨在使用多层螺旋计算机断层扫描(MSCT)获得的颅骨测量值,为马来西亚未成年人开发一种性别鉴定模型。共收集了 521 名马来西亚未成年颅骨 MSCT 数据集(男性 279 名,女性 242 名;0-20 岁)。Mimics 软件版本 21.0(Materialise,比利时鲁汶)用于构建三维(3D)模型。采用平面到平面(PTP)协议测量 14 个选定的颅骨测量参数。判别函数分析(DFA)和二项逻辑回归(BLR)用于对数据进行统计分析。在本研究中,观察到 6 岁以下颅骨的性别二态性水平较低。然后随着年龄的增长而增加。对于样本验证数据,DFA 和 BLR 估计性别的准确性从 61.6%提高到 90.3%,随着年龄的增长而提高。除 0-2 和 3-6 岁组外,所有年龄组在使用 DFA 和 BLR 进行测试时,准确率均较高(≥75%)。DFA 和 BLR 可用于使用 MSCT 颅骨测量值对马来西亚未成年人进行性别鉴定。然而,BLR 在未成年人的性别鉴定中比 DFA 具有更高的准确性。

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