Testing the accuracy of the DRNNAGE software for age estimation in a modern Greek sample.

Estimation of age-at-death from human skeletal remains is fundamental in forensic anthropology as part of the construction of the biological profile of the individual under study. At the same time, skeletal age-at-death estimation in adults is problematic due to the disparity between chronological and biological age, the important inter-individual variability at the rate of skeletal aging, and inherent biases in the available methodologies (e.g., age mimicry). A recent paper proposed a method for skeletal age-at-death estimation based on multiple anatomical traits and machine learning. A software was also created, DRNNAGE, for the easy implementation of this method. The authors of that study supported that their methods have very high repeatability and reproducibility, and the mean absolute error of the age estimation was ~6 years across the entire adult age span, which is particularly high and promising. This paper tests the proposed methodology on a modern documented Greek sample of 219 adult individuals from the Athens Collection, with age-at-death from 19 to 99 years old. The sample was split into males and females as well as into individuals under and over 50 years old. We also divided the sample in 10-year intervals. First, intra- and inter-observer error was estimated in order to assess repeatability and reproducibility of the variables employed for age-at-death estimation. Then, the validity (correct classification performance) of DRNNAGE for each anatomical region individually, as well as all combined, was evaluated on each demographic separately and on the pooled sample. According to the results, some of the variables showed very low repeatability and reproducibility, thus their use should be cautious. The DRNNAGE software showed overall highly accurate age-at-death estimates for individuals older than 50 years, but poor on younger adults, with only exception the cranial sutures, which performed surprisingly well for all age groups. Overall, these results support the importance of cross-validation and the use of population-specific methods in forensic anthropology.

The impact of age on the morphology of the 12th thoracic vertebral endplates.

The current article explores the aging effects on the overall morphology of the endplates of the 12th thoracic vertebra (T12), while screening for sex differences. It further evaluates the suitability of T12 for estimating age-at-death in bioarcheaological contexts. We captured the morphology of the vertebral endplates, including the formation of osteophytes, in a novel continuous quantitative manner using digital photography. 168 Greek adults from the Athens Collection were used for modeling the aging effects and another 107 individuals from two Danish archaeological assemblages for evaluation. Regression analysis is based on generalized additive models for correlating age-at-death and morphological variation. Our proposed measurement method is highly reliable (R>0.98) and the main differences observed between sexes are size related. Aging has considerable effect on the endplate morphology of the T12 with the total area of the endplate, the area of the epiphyseal rim, and the shape irregularities of the endplate's external boundary being mostly affected. Multivariate regression shows that aging effects account up to 46% of the observed variation, although with differential expression between sexes. Correct age prediction on archaeological remains reached 33% with a prominent tendency for overestimation. The morphology of the T12 endplates is influenced by age and it can provide some insight with respect to the age-at-death of unidentified individuals, especially when other skeletal age markers are unavailable. Our proposed method provides an age-estimation framework for bioarchaeological settings, especially for estimating broader age ranges, such as discriminating between young and old adults.

Advancements in sex estimation using the diaphyseal cross-sectional geometric properties of the lower and upper limbs.

This paper introduces an automated method for estimating sex from the lower and upper limbs based on diaphyseal CSG properties. The proposed method was developed and evaluated using 389 femurs, 412 tibias, and 404 humeri of adult individuals from a modern Greek reference sample, the Athens Collection. The skeletal properties, which were extracted with the CSG-Toolkit, were analyzed with step-wise DFA (evaluated with LOOCV) and subsequently with RBF kernel SVM supervised learning. SVM cross-validation was based on a 20-fold stratified random sample splitting as well as a chronological split based on year of birth to further assess the effect of secular change in sex estimation capacity. Maximum cross-validated classification accuracy from step-wise DFA reached 94.8% for the femur, 94.7% for the tibia, and 97.3% for the humerus, whereas SVM cross-validated results were similar although slightly lower, mainly due to the more strict cross-validation scheme. Our results suggest that the proposed sex estimation method is reasonably robust to secular change, since there was limited loss in classification accuracy between different chronological groups, despite the presence of secular change in stature of the Greek population during the examined period. The proposed method has been implemented as a function for the GNU Octave environment, named estimate_sex, which comprises a self-intuitive graphical user interface for facilitating sex estimation and is freely available under a suitable license.

Forensic sex estimation using the vertebrae: an evaluation on two European populations.

Sex estimation is one of the primary steps for constructing the biological profile of skeletal remains leading to their identification in the forensic context. While the pelvis is the most sex diagnostic bone, the cranium and other post-cranial elements have been extensively studied. Earlier research has also focused on the vertebral column with varying results regarding its sex classification accuracy as well as the underlying population specificity. The present study focuses on three easily identifiable vertebrae, namely T1, T12, and L1, and utilizes two modern European populations, a Greek and a Danish, to evaluate their forensic utility in sex identification. To this end, 865 vertebrae from 339 individuals have been analyzed for sexual dimorphism by further evaluating the effects of age-at-death and population affinity on its expression. Our results show that T1 is the best sex diagnostic vertebra for both populations reaching cross-validated accuracy of almost 90%, while age-at-death has limited effect on its sexual dimorphism. On the contrary, T12 and L1 produced varying results ranging from 75 to 83% accuracy with the Greek population exhibiting distinctively more pronounced sexual dimorphism. Additionally, age-at-death had significant effect on sexual dimorphism of T12 and L1 and especially in the Greek female and Danish male groups. Our results on inter-population comparison suggest that vertebral sex discriminant functions, and especially those utilizing multiple measurements, are highly population specific and optimally suitable only for their targeted population. An open-source software tool to facilitate classifying new cases based on our results is made freely available to forensic researchers.