Edinburgh Unit for Forensic Anthropology, University of Edinburgh, Edinburgh, UK.
Forensic Medicine Unit, Department of Forensic Sciences, University of Crete, Heraklion, Greece.
Adv Exp Med Biol. 2019;1205:55-69. doi: 10.1007/978-3-030-31904-5_4.
Forensic anthropologists are frequently faced with the challenge of individualizing and sorting commingled remains in a variety of scenarios. A number of protocols have been proposed to standardize the methodological approach to individuating commingled remains, some of which are focused on pair-matching. A recent study by Karell et al. (2016) proposed a virtual method for pair-matching humeri using a semi-automatic procedure that gave encouraging results. With regards to the phalanges, there are only a handful of studies focusing on identifying and siding phalanges, as well as exploring their directional and functional asymmetry. Yet, they are still as important as every other bone when sorting commingled human remains in various situations, such as archaeological common burials and mass graves, commingled decomposed remains resulting from atrocities, accidents or natural disasters. This study investigates a new method for pair-matching, a common individualization technique, using digital three-dimensional models of bone: mesh-to-mesh value comparison (MVC) as proposed by Karell et al. (2016). The MVC method digitally compares the entire three-dimensional geometry of two bones using an iterative closest point (ICP) algorithm to produce a single value as a proxy for their similarity. The method is automated with the use of Viewbox software 4.1 beta for a simultaneous comparison of all possible pairs. For this study, 515 phalanges from 24 individuals of mixed ancestry were digitized using CT scans and the 3D modeling program AMIRA 5.3.3. The models were also hollowed (internal information of compact and trabecular bone removed) to test the method with simulated surface scan models. The subsequent data-over 73,000 comparisons-were assessed using sensitivity and specificity rates via ROC analysis to indicate how well the automated version of MVC pair-matched phalanges. The best bone in terms of pair-matching was the proximal phalanx of Digit 3 with 87.5% sensitivity and 92.4% specificity rates at a threshold value of 0.488 for the unhollowed bones. The specificity drops slightly (91.1%) when the hollowed models are compared. To compare the performance of the method in all phalanges, the specificity was set to 95%-allowing for a 5% acceptable error-and the adjusted sensitivity was compared. The highest sensitivity, namely 68.8%, was noted for Digit 2 proximal phalanx for both unhollowed and hollowed models. Thus far, our preliminary results indicate that the MVC method performs well when pair-matching phalanges, though it is less accurate than pair-matching other types of bones. The introduction of 95% specificity threshold allows for rejecting pairs in great confidence, which could, for instance, significantly reduce the number of DNA comparisons required for the remaining possible matches. In addition, the similar results obtained from hollowed and unhollowed models indicate that the internal information included in the unhollowed models adds little to the identification of true pairs. This means that if a CT scan is not available, the method could be applied to surface models produced by light and laser scanners as well. While additional work needs to be done to verify these preliminary results, this research has the potential to expand the repertoire of individualization methods.
法医人类学家经常面临在各种情况下对混杂遗骸进行个体识别和分类的挑战。已经提出了许多协议来标准化鉴别混杂遗骸的方法,其中一些协议侧重于配对匹配。最近,Karell 等人(2016 年)提出了一种使用半自动程序对肱骨进行虚拟配对匹配的方法,该方法取得了令人鼓舞的结果。关于指骨,只有少数研究集中在识别和侧指骨上,以及探索它们的方向性和功能性不对称性。然而,当在各种情况下对混杂的人类遗骸进行分类时,它们仍然与其他骨骼一样重要,例如考古学中的普通埋葬和乱葬坑、因暴行、事故或自然灾害而混杂分解的遗骸。本研究探讨了一种新的配对匹配方法,这是一种常见的个体识别技术,使用骨骼的数字三维模型:Karell 等人提出的网格到网格值比较(MVC)。MVC 方法使用迭代最近点(ICP)算法对两个骨骼的整个三维几何形状进行数字比较,生成一个单一的值作为它们相似性的代表。该方法使用 Viewbox 软件 4.1 beta 进行自动化,以便同时比较所有可能的对。在这项研究中,使用 CT 扫描对 24 名混合血统个体的 515 个指骨进行了数字化,并使用 AMIRA 5.3.3 三维建模程序。还对模型进行了镂空(去除致密骨和小梁骨的内部信息),以使用模拟表面扫描模型测试该方法。随后的数据-超过 73000 次比较-使用 ROC 分析评估了敏感性和特异性率,以表明自动化 MVC 配对匹配指骨的方法的效果如何。在未镂空骨骼的情况下,第 3 指的近端指骨的阈值为 0.488 时,配对匹配的最佳骨骼为 87.5%的敏感性和 92.4%的特异性率。当比较镂空模型时,特异性略有下降(91.1%)。为了比较该方法在所有指骨中的性能,将特异性设置为 95%-允许 5%的可接受误差-并比较调整后的敏感性。对于未镂空和镂空模型,近端指骨的最高敏感性均为 68.8%,第 2 指。到目前为止,我们的初步结果表明,MVC 方法在配对匹配指骨时表现良好,尽管它不如配对匹配其他类型的骨骼准确。引入 95%特异性阈值可以极大地增强拒绝配对的信心,例如,这可以显著减少对剩余可能匹配所需的 DNA 比较数量。此外,从镂空和未镂空模型中获得的相似结果表明,未镂空模型中包含的内部信息对识别真正的对几乎没有帮助。这意味着,如果没有 CT 扫描,该方法可以应用于光和激光扫描仪生成的表面模型。虽然还需要做更多的工作来验证这些初步结果,但这项研究有可能扩展个体识别方法的范围。