Anthropometric study using three-dimensional pelvic CT scan in sex determination among adult Indonesian population

Estimation of population affinity using proximal femoral measurements based on computed tomographic images in the Japanese and western Australian populations

The present study analyzes morphological differences femora of contemporary Japanese and Western Australian individuals and investigates the feasibility of population affinity estimation based on computed tomographic (CT) data. The latter is deemed to be of practical importance because most anthropological methods rely on the assessment of aspects of skull morphology, which when damaged and/or unavailable, often hampers attempts to estimate population affinity. The study sample comprised CT scans of 297 (146 females; 151 males) Japanese and 330 (145 females; 185 males) Western Australian adult individuals. A total of 10 measurements were acquired in two-dimensional CT images of the left and right femora; two machine learning methods (random forest modeling [RFM]) and support vector machine [SVM]) were then applied for population affinity classification. The accuracy of the two-way (sex-specific and sex-mixed) model was between 71.38 and 82.07% and 76.09-86.09% for RFM and SVM, respectively. Sex-specific (female and male) models were slightly more accurate compared to the sex-mixed models; there were no considerable differences in the correct classification rates between the female- and male-specific models. All the classification accuracies were higher in the Western Australian population, except for the male model using SVM. The four-way sex and population affinity model had an overall classification accuracy of 74.96% and 79.11% for RFM and SVM, respectively. The Western Australian females had the lowest correct classification rate followed by the Japanese males. Our data indicate that femoral measurements may be particularly useful for classification of Japanese and Western Australian individuals.

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.

No Bones About It: Sex Is Binary

Anthropologists have led the way in formulating techniques that reveal skeletal differences between males and females. Understanding of physical differences in the pelvis related to childbirth, hormonal impacts on bones, and extensive comparative studies have provided anthropologists with an array of traits and measurements that help them estimate sex using just bones. Forensic anthropologists and bioarcheologists are improving their ability to differentiate males and females by increasing research on a variety of postcranial bones and through the use of molecular data, especially new methods called proteomics, to identify sex in prepubescent juveniles. As remains from more cultures and time periods are studied, sex identification will continue to improve, because skeletal sex differences are in large part biologically determined. Yet, anthropologists have also been at the forefront of arguing that sex lies on a spectrum. Anthropologists who view sex as on a spectrum may deter sex identification progress; from their perspective, an individual of an undetermined sex may just be a nonbinary individual. Anthropologists who consider sex is on a spectrum are coming to this conclusion in part because they are looking for anatomical ideals, mistaking pathology for variation, and confusing independent variables with dependent variables. Nonetheless, anthropologists need to continue to improve sex identification techniques to reconstruct the past accurately, which may reveal less strict sex roles than previously presumed and help with the identification of crime victims. Forensic anthropologists should also increase their efforts to identify whether individuals have undergone medical procedures intended to change one's gender due to the current rise in transitioning individuals.

A novel method to estimate adult age from the lumbar vertebral body using 3D PMCT images in Japanese

This study evaluated the age-related changes in the vertebral body using 3D Postmortem CT (PMCT) images and proposed an alternative age estimation formula. The PMCT images of 200 deceased individuals aged 25 to 99 years (126 males, 74 females) were retrospectively reviewed and included in the study. Using the open-source software ITK-SNAP and MeshLab, a 3D surface mesh of the fourth lumbar vertebral body (L4) and its convex hull models were created from the PMCT data. Using their inbuilt tools, volumes (in mm3) of the L4 surface mesh and convex hull models were subsequently computed. We derived VD, defined as the difference in volumes between the convex hull and L4 surface mesh normalized by L4 mesh volume, and VR, defined as the ratio of L4 mesh volume to convex hull volume based on individual L4. Correlation and regression analyses were performed between VD, VR, and chronological age. A statistically significant positive correlation (P < 0.001) between chronological age and VD, (r_s = 0.764, males; r_s = 0.725, females), and a significant negative correlation between chronological age and VR (r_s = -0.764, males; r_s = -0.725, females) was obtained in both sexes. The lowest standard error of the estimate was demonstrated by the VR at 11.9 years and 12.5 years for males and females, respectively. As such, their regression models to estimate adult age were Age = 248.9-2.5VR years, males; Age = 258.1-2.5VR years, females. These regression equations may be useful for estimating age in Japanese adults in forensic settings.