Forensic pathologists commonly use computed tomography (CT) images to assist in determining the cause and manner of death as well as for mass disaster operations.Even though the design of the CT machine does not inherently produce distortion, most techniques within anthropology rely on metric variables, thus concern exists regarding the accuracy of CT images reflecting an object's true dimensions. Numerous researchers have attempted to validate the use of CT images, however the comparisons have only been conducted on limited elements and/or comparisons were between measurements taken from a dry element and measurements taken from the 3D-CT image of the same dry element.A full-body CT scan was performed prior to autopsy at the Office of the Chief Medical Examiner for the State of Maryland. Following autopsy, the remains were processed to remove all soft tissues and the skeletal elements were subject to an additional CT scan. Percent differences and Bland-Altman plots were used to assess the accuracy between osteometric variables obtained from the dry skeletal elements and from CT images with and without soft tissues. An additional seven crania were scanned, measured by three observers, and the reliability was evaluated by technical error of measurement (TEM) and relative technical error of measurement (%TEM).Average percent differences between the measurements obtained from the three data sources ranged from 1.4% to 2.9%. Bland-Altman plots illustrated the two sets of measurements were generally within 2mm for each comparison between data sources. Intra-observer TEM and %TEM for three observers and all craniometric variables ranged between 0.46 mm and 0.77 mm and 0.56% and 1.06%, respectively. The three-way interobserver TEM and %TEM for craniometric variables was 2.6 mm and 2.26%, respectively. Variables that yielded high error rates were orbital height, orbital breadth, inter-orbital breadth and parietal chord. Overall, minimal differences were found among the data sources and high accuracy was noted between the observers, which prove CT images are an acceptable source to collect osteometric variables.

Pattern-expressions of morphoscopic cranial traits vary across populations with classification accuracies being highly dependent on the reference collection to which unknown skulls are compared. Despite recent developments in population-specific standards for South Africans, researchers have not addressed the accuracy of morphological methods. Several studies demonstrate differences in sexual dimorphism between South Africans and North Americans, warranting a need to re-evaluate sex estimation methods in South Africa. The purpose of this study was to test the reliability and accuracy of the Walker (2008) method and to examine patterns of sexual dimorphism among South Africans.A total of 245 modern black and white South African male and female crania from the Pretoria Bone Collection, University of Pretoria, were scored using the Walker (2008) methodology. Cohen's Kappa was used to evaluate reliability of the method and percent correct assessed validity of the method. Logistic regression was utilised to create modified population-specific formulae.Inter-and intra-observer agreement was moderate to excellent (0.60-0.90), except for the mental eminence (0.40). The percent correct results for sex were 80% or higher for combinations of glabella, mastoid and menton and between 68% and 73% for menton, mastoid, orbital and nuchal margin using logistic equations 2 of Walker (2008). White males had the highest (94-97%) and white females had the lowest (31-62%) percent correct.The low accuracies obtained when using Walker (2008) emphasized the need for population-specific sex estimation models. Modified formulae for South Africans were created, yielding higher classification rates (84-93%) than when North American standards were employed.

Subadult age estimation is considered the most accurate parameter estimated in a subadult biological profile, even though the methods are deficient and the samples from which they are based are inappropriate. The current study addresses the problems that plague subadult age estimation and creates age estimation models from diaphyseal dimensions of modern children.The sample included 1,310 males and females between the ages of birth and 12 years.Eighteen diaphyseal length and breadth measurements were obtained from Lodox Statscan radiographic images generated at two institutions in Cape Town, South Africa between 2007 and 2012. Univariate and multivariate age estimation models were created using multivariate adaptive regression splines (MARS). K-fold cross-validated 95% prediction intervals (PIs) were created for each model and the precision of each model was assessed.

Population history and positive assortative mating directs gene flow in such a way that biological differences are recognized among groups. In turn, forensic anthropologists quantify biological differences to estimate ancestry. Some anthropologists argue that highly admixed population groups, such as South African coloureds, cannot achieve acceptable accuracies because within group variance is too large. Whereas ancestry estimation in South Africa has been limited to craniometric data from South African 2 blacks and whites, the current study integrates craniometric and geometric morphometric data from the three largest South African groups.Crania from 377 South African individuals (black = 158, white =112, and coloured = 107) comprised the sample. Standard measurements were collected and the coordinate data were subjected to Generalized Procrustes Analysis (GPA), which resulted in size-free shape variables (ProCoords). A principal component analysis was used to combine the shape variation captured in the ProCoords (ProCoords PC). Linear discriminant analysis (LDA), using equal priors, stepwise variable selection and leaveone-out cross-validation, was conducted on the ProCoords, the ProCoords PCs, and the traditional craniometric data.The LDA using 18 stepwise selected ProCoords resulted in the highest crossvalidated accuracy (89%). Utilization of geometric morphometric data emphasized that the relative location of cranial landmarks was more discriminating than simple linear distances. Regardless of high levels of genetic admixture, South African coloureds are a homogeneous group and morphologically distinct from other contemporaneous South African populations. Furthermore, the present study demonstrated a correspondence between peer-reported race and morphological differences in the crania of black, white, and coloured South Africans.

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Best scientific practice for sex estimation incorporates accurate techniques that employ appropriate standards and population- and period-specific data. Single measurements provide accurate sex estimations, but multiple measurements and multivariate techniques offer greater validity to biological profile assessments. Appropriate, modern standards for sex estimation are limited to the cranium in South Africans (SA), which warrants the examination of the potential for sex estimation using the postcrania of socially defined SA blacks, whites and coloureds through multivariate models and advanced statistical techniques. A total of 39 standard osteometric measurements were taken from the postcrania of 360 socially defined SA blacks, whites and coloureds (equal sex and ancestry). Univariate and multivariate models were evaluated. Multivariate models, with cross-validation and equal priors, were explored with linear and flexible discriminant analysis (LDA and FDA, respectively). Classification accuracies associated with univariate models ranged from 56 to 89%, whereas multivariate classification accuracies using bone models (i.e. all measurements from one element) ranged from 75 to 91%. The highest correct classifications were achieved with multivariate subsets (i.e. combinations of measurements from different bones) and ranged from 90 to 98%. Overall, FDA and LDA yielded similar accuracy rates. Postcranial bones achieve comparable classification accuracies to the pelvis and higher accuracies than metric or morphological techniques using the cranium. While LDA is the most commonly used classification statistic in biological anthropology, FDA provides a good alternative for classification.

It is currently unknown whether morphological sex estimation traits are accurately portrayed on virtual bone models, and this hampers the use of virtual bone models as an alternative source of contemporary skeletal reference data. This study determines whether commonly used morphological sex estimation traits can be accurately scored on virtual 3D pelvic bone elements. Twenty-seven intact cadavers from the body donation program of the Amsterdam UMC, University of Amsterdam, were CT scanned; this data was used to produce virtual bone models. Thereafter, the dry bones were obtained. Three traits by Klales (2012) and five traits from the Workshop of European Anthropologists (WEA) (1980) were scored on the virtual bone models and their dry skeletal counterparts. Intra- and inter-observer agreement and the agreement between the scores for each virtual bone model-dry bone pair were calculated using weighted Cohen’s kappa (K). For all Klales (2012) traits, intra- and inter-observer agreement was substantial to almost perfect for the virtual- and dry bones (K = 0.62–0.90). The agreement in scores in the virtual-dry bone pairs ranged from moderate to almost perfect (K = 0.58–0.82). For the WEA (1980) traits, intra-observer agreement was substantial to almost perfect (K = 0.64–0.91), but results were less unambiguous for inter-observer agreement (K = 0.24–0.88). Comparison of the scores between the virtual bone models and the dry bones yielded kappa values of 0.42–0.87. On one hand, clinical CT data is a promising source for contemporary forensic anthropological reference data, but the interchangeability of forensic anthropological methods between virtual bone models and dry skeletal elements needs to be tested further.

Recently, Drs. Bethard and DiGangi opened a dialogue on the application of ancestry estimation as part of the biological profile in forensic anthropology [1]. Ancestry estimation of human skeletal remains is routinely used to predict a probable social race based on metric and morphological data from the skeleton. Anthropologists accept the social construction of race and are acutely aware of its harmful impact in American society, particularly with respect to the historic use of anthropology to promote scientific racism. When scientists fail to 'call out' racist ideas in their field, these ideas can become embedded within institutions and society, further reifying racist ideology [2]. In this context, we wish to respond to Bethard and DiGangi's request to open a conversation regarding the use of ancestry estimation in forensic anthropology and how it contributes to the identification process. In this letter, we provide a foundation for a conversation about ancestry as a means to encourage thoughtful discussion moving forward on the issues of redress, diversity, and multidisciplinary collaboration.