Evaluating the Accuracy of Cranial Indices in Ancestry Estimation Among South African Groups

Population affinity estimation using pelvic measurements based on computed tomographic data acquired from Japanese and Western Australian populations

The present study analyzes morphological differences in the pelvis of Japanese and Western Australian individuals and investigates the feasibility of population affinity classification based on computed tomography (CT) data. The Japanese and Western Australian samples comprise CT scans of 207 (103 females; 104 males) and 158 (78 females; 80 males) adult individuals, respectively. Following volumetric reconstruction, a total of 19 pelvic landmarks were obtained on each sample, and 11 measurements, including two angles, were calculated. Machine learning methods (random forest modeling [RFM] and support vector machine [SVM]) were used to classify population affinity. Classification accuracy of the two-way models was approximately 80% for RFM: the two-way sex-specific and sex-mixed models for SVM achieved > 90% and > 85%, respectively. The sex-specific models had higher accurate classification rates than the sex-mixed models, except for the Japanese male sample. The classification accuracy of the four-way sex and population affinity model had an overall classification accuracy of 76.71% for RFM and 87.67% for SVM. All the correct classification rates were higher in the Japanese relative to the Western Australian sample. Our data suggest that pelvic morphology is sufficiently distinct between Japanese and Western Australian individuals to facilitate the accurate classification of population affinity based on measurements acquired in CT images. To the best of our knowledge, this is the first study investigating the feasibility of population affinity estimation based on CT images of the pelvis, which appears as a viable supplement to traditional approaches based on cranio-facial morphology.

Estimation of ancestry from cranial measurements based on MDCT data acquired in a Japanese and Western Australian population

The estimation of ancestry is important not only towards establishing identity but also as a required precursor to facilitating the accurate estimation of other attributes such as sex, age at death, and stature. The present study aims to analyze morphological variation in the crania of Japanese and Western Australian individuals and test predictive models based on machine learning for their potential forensic application. The Japanese and Western Australian samples comprise computed tomography (CT) scans of 230 (111 female; 119 male) and 225 adult individuals (112 female; 113 male), respectively. A total of 18 measurements were calculated, and machine learning methods (random forest modeling, RFM; support vector machine, SVM) were used to classify ancestry. The two-way unisex model achieved an overall accuracy of 93.2% for RFM and 97.1% for SVM, respectively. The four-way sex and ancestry model demonstrated an overall classification accuracy of 84.0% for RFM and 93.0% for SVM. The sex-specific models were most accurate in the female samples (♀ 95.1% for RFM and 100% for SVM; ♂91.4% for RFM and 97.4% for SVM). Our findings suggest that cranial measurements acquired in CT images can be used to accurately classify Japanese and Western Australian individuals into their respective population. This is the first study to assess the feasibility of ancestry estimation using three-dimensional CT images of the skull.

Comparative morphometric study of the mimic facial muscles of brachycephalic and dolichocephalic dogs

Excessive breeding of dogs has led to a disadvantageous morphology in some breeds, for example extreme brachycephaly, which is responsible for many health issues. We hypothesize that alterations of the mimic muscular system are present in brachycephalic dogs and could contribute to behavioural problems due to a restricted mimic display. Therefore, the purpose of this paper was to compare the mimic muscular systems of brachycephalic with dolichocephalic dogs. Mimic muscles were measured and set in ratio to measurements of the head and calculated indices. When bringing the length of the muscles m(x) in proportion to the length of the head, highly significant differences (p < .0001) and significant difference (p < .05) were found in all but two of the examined muscles. Calculations of the m(x) divided by the cranial index and the square index showed significant differences for all muscles. For example, the musculus (m.) levator nasolabialis was morphologically different from the one of dolichocephalic dogs. Muscle fibres of the m. levator nasolabialis were localized in the fold over the nasal bridge of brachycephalic dogs. The raphe of the m. orbicularis oris was not always apparent in brachycephalic dogs. The proportions of the muscle lengths and the length of the eye slots to the size of the skull have shifted considerably in brachycephalic dogs. We conclude that many alterations contribute to the strong shift in the proportions of the head of brachycephalic dogs versus that of dolichocephalic dogs. Our findings suggest that brachycephalic dogs have reduced mimic skills that can lead to ambiguous communication.

The need to incorporate human variation and evolutionary theory in forensic anthropology: A call for reform

In 1992, Norm Sauer called for a language shift in which practitioners would move away from the socially loaded term "race" and replace it with the less provocative term "ancestry." While many heeded the call and moved towards ancestry in their research and reports, the actual approach to research and analysis did not change. In response to this change, there was a large growth in ancestry estimation method development in the early decade of the 2000s. However, the practice of ancestry estimation did not adequately incorporate evolutionary theory in interpretation or trait selection and continued with little critical reflection. In the past decade, there has been an increase in ancestry validation methods with little critique of the "race" concept or discussion of modern human variation or reference samples. To advance, forensic anthropologists need to reckon with the practice of ancestry estimation as it is currently practiced. We are calling for another reform in the axiom focusing on evolutionary theory, population history, trait selection, and population-level reference samples. The practice needs to abandon the terms ancestry and race completely and recalibrate to an analysis of population affinity. Population affinity is a statistical approach based on the underlying population structure that would allow the understanding of how microevolutionary forces act in concert with historical events (e.g., colonization, the Transatlantic Slave Trade, etc.) to shape modern human variation. This is not to be confused with geographic ancestry that all too often can be perceived as interchangeable with social race and as an affirmation of the biological concept of race. It is time to critically evaluate the social and scientific implications of the current practice of ancestry estimation, and re-frame our approach to studying and analyzing modern human variation through a population structure approach.

On the use of machine learning algorithms in forensic anthropology

The classification performance of the statistical methods binary logistic regression (BLR), multinomial and penalized multinomial logistic regression (MLR, pMLR), linear discriminant analysis (LDA), and the machine learning algorithms naïve Bayes classification (NBC), decision trees (DT), random forest (RF), artificial neural networks (ANN), support vector machines (linear, polynomial or radial) (SVM), multivariate adaptive regression splines (MARS), and extreme gradient boosting (XGB) is examined in skeletal sex/ancestry estimation. The datasets used to test the performance of these methods were obtained from a documented human skeletal collection, Athens Collection, and the Howells Craniometric data set. For their implementation, an R package has been written to search for the optimum tuning parameters under cross-validation and perform sex/ancestry classification. It was found that the classification performance may vary significantly depending on the problem. From the methods tested, LDA and the machine learning technique of linear SVM exhibit the best performance, with high prediction accuracy and relatively low bias in most of the tests. ANN and pMLR can generally be considered to give satisfactory predictions, whereas NBC when using metric traits and DT are the worst of the classification methods examined. The possibility of making the models developed via the machine learning algorithms applicable to other assemblages without the use of a training sample is also discussed.

Assessing zygomatic shape and size for estimating sex and ancestry in a South African sample

Unidentified, decomposed and skeletonised human remains are frequently found in South Africa, therefore, standardised, reliable and relevant sex and ancestry estimation methods are required for forensic identification. This study assessed sex and ancestral variation in zygomatic size and shape in a South African population using geometric morphometric analyses. The zygoma of 158 South African individuals were sampled. Eight zygomatic landmarks were captured in 3-dimensions using a Microscribe G2 digitiser and assessed using procrustean geometric morphometrics. Shape and size differences were analysed using multivariate linear regression, discriminant function and canonical variate analyses. Males had significantly larger zygomas than females. Significant shape variation was found between ancestral groups. Bantu-speaking and Mixed ancestry individuals had narrower, shorter and more anteriorly projecting orbital margins, whilst Europeans had vertically elongated and receded orbital margins. European ancestral groups were most discernible from Bantu-speakers and Mixed ancestral groups. Ancestry estimation accuracies improved when ancestry was aggregated with sex. Pairwise ancestry-linked comparisons in females were as follows; Bantu-speakers (76%) from Europeans (72%), Bantu-speakers (71%) from Mixed ancestry (59%) and European (72%) from Mixed ancestry (63%). Similarly, ancestry-linked comparisons in males were as follows; Bantu-speakers (77%) from Europeans (81%), Bantu-speakers (53%) from Mixed ancestry (59%) and European (72%) from Mixed ancestry (82%). Size differences are putatively linked to variations in hormone-regulated growth and muscular robusticity between males and females. Shape variations between ancestral groups are likely attributable to the heterogenous genetic and ancestral origins of the South African population. It is challenging to distinguish between South Africa Bantu speakers and Mixed ancestry people due to Mixed ancestry individuals having variable genetic contributions from Khoesan, Bantu-speakers, Europeans and Asians. Bantu-speaking and Mixed ancestry people had zygomatic morphologies consistent with historical thermoregulatory adaptations to sub-Saharan climates, reported in African-descendants. Zygomatic morphology in European descendants suggests ancestral origins from colder climatic regions. This study demonstrated the utility of the zygoma in distinguishing between ancestral groups in South Africa, but further research is required to develop population-specific standards to distinguish between South African populations with shared African ancestry. The zygoma shows a promising ability to estimate sex and ancestry in South Africans, suggesting population specific standards for this bone may be of forensic interest.

Evaluation of ancestry from human skeletal remains: a concise review

Ancestry assessment represents a major component of forensic anthropological analysis of recovered human remains. Interpretations of ancestry, together with other aspects of the biological profile, can help narrow the search of missing persons and contribute to eventual positive identification. Such information can prove useful to authorities involved in the identification and investigative process since many lists of missing persons have a reference to this parameter. Recent research has strengthened available methodologies involving metric, non-metric morphological as well as chemical and genetic approaches. This review addresses the new anthropological techniques that are now available, as well as the complex historical context related to ancestry evaluation.

Morphometric Analysis of the Neurocranium in an Adult South African Cadaveric Sample

Craniometric studies of South Africans yield high accuracies of sex and ancestry classification, but most assess only inter-group variation of Black and White individuals, excluding the highly heterogeneous Colored group, which constitute a significant proportion of the population. This study applied a geometric morphometric approach to the neurocrania of 774 Black, Colored, and White individuals to assess sex and ancestry estimation accuracy based on the detected morphological variation. Accuracies of 70% and 83% were achieved for sex and ancestry, respectively, with ancestry-related variation contributing the largest proportion of overall observed variation. Even when comparing the closely related Black and Colored groups, relatively high accuracies were obtained. It is thus recommended that a similar approach be used to develop a contemporary three-dimensional database, which can be used to objectively, reliably, and accurately classify unknown remains in the South African forensic context.

Morphometric analysis of the humerus in an adult South African cadaveric sample

Recent studies using geometric morphometrics have shown that estimations of demographic parameters can be made using skeletal elements previously not thought useful for such purposes. This study used geometric morphometrics to assess humeral morphological variation in an adult South African sample, and evaluated the accuracy of sex and ancestry estimations based on this variation. Humeri of 1046 adult South African individuals (464 females, 582 males) were digitized. Data sets were rotated and scaled to a common centroid using Generalized Procrustes Analysis. Mean centroid sizes between groups were compared using parametric tests, while morphological variation was evaluated using multivariate analyses. Discriminant Function Analysis coupled with leave-one-out cross-validation tests were used to assess the reliability of sex and ancestry classifications based on this variation. Male humeri were relatively larger and presented with morphological features indicative of larger muscle mass and smaller carrying angles than females. White individuals had relatively larger but morphologically less robust humeri than Black or Coloured individuals, likely a reflection of both genetic and socio-economic differences between the groups as enforced under Apartheid law. When sex and ancestry were assessed together, similar variations were detected than when either parameter was individually assessed. Classification accuracy was relatively low when sex was independently assessed (73.3%), but increased when considered in conjunction with ancestry, indicating greater variation between-groups (ancestry) than within-groups. Ancestry estimation accuracies exceeded 80%, even for the highly diverse Coloured group. Classification accuracies of sex-ancestry groups all exceeded 76%. These results show that humerus morphological variation is present and may be used to estimate parameters, such as sex and ancestry, even in complex groups such as the Coloured sample of this study.

Cranial index in a modern people of Thai ancestry

The present research aims to examine the cranial index in a modern people of Thai ancestry. Ultimately, this study will help to create a databank containing a cranial index for the classifications of the people from Asia. In this study, 185 modern crania of people of supposed Thai ancestry were examined. They were collected from the Department of Anatomy at Chulalongkorn University in Bangkok, Thailand. The maximum cranial length and breadth were measured using standard anthropometric instruments based on Martin's methods. The cranial index was calculated using the equation ([maximum cranial breadth/maximum cranial length]×100). The mean cranial indices for the male and female skulls examined were 81.81±4.23 and 82.99±4.37, respectively. The most common type of skull in the modern Thai people in this study was the brachycranic type with a frequency of 42.7%, followed by the mesocranic (27.03%) and hyperbrachycranic types (25.59%). The rarest type observed in this study was the dolichocranic type (4.32%). The present study provides valuable data pertaining to the cranial index in a modern Thai population and reveals that modern Thai males and females belong to the brachycranic group. The results of this study will be of forensic anthropological importance to populations in close proximity to the location where the skulls studied here were sourced.