Osteometric sex estimation from the os coxa in a Thai population

Comparison of sex determination using three methods applied to the greater sciatic notch of os coxae in a Thai population: Dry bone morphology, 2-dimensional photograph morphometry, and deep learning artificial neural network

The os coxa is commonly used for sex and age estimation with a high degree of accuracy. Our study aimed to compare the accuracy among three methods, which include a deep learning approach to increase the accuracy of sex prediction. A total sample of 250 left os coxae from a Thai population was divided into a 'training' set of 200 samples and a 'test' set of 50 samples. The age of the samples ranged from 26 to 94 years. Three methods of sex determination were assessed in this experiment: a dry bone method, an image-based method and deep learning method. The intra- and inter-observer reliabilities were also assessed in the dry bone and photo methods. Our results showed that the accuracies were 80.65%, 90.3%, and 91.95% for the dry bone, image-based, and deep learning methods, respectively. The greater sciatic notch shape was wide and symmetrical in females while narrow and asymmetrical in males. The intra- and inter-observer agreements were moderate to almost perfect level (Kappa = 0.67-0.93, ICC = 0.74-0.94). Conclusion: The image-based and deep learning methods were efficient in sex determination. However, the deep learning technique performed the best among the three methods due to its high accuracy and rapid analysis. In this study, deep learning technology was found to be a viable option for remote consultations regarding sex determination in the Thai population.

Three-dimensional geometric morphometric sex determination of the whole and modeled fragmentary human pubic bone

Sex determination of the human pelvis has traditionally been done through visual analyses of morphoscopic traits and there are limited metric methods available to forensic anthropologists to add metric credibility to these analyses. The goal of this research was to create an improved metric method using three-dimensional geometric morphometrics to determine sex from both whole and modeled fragmented human pubic bones. The sample consisted of n = 378 pubic bones from the University of New Mexico’s Maxwell Museum Documented Skeletal Collection and eight landmarks were collected from each bone. Statistical analyses and machine learning algorithms were used to predict the accuracy of the method’s ability to classify a bone as male or female on both whole and simulated fragmented remains; this included tests run on each possible landmark combination of three or more landmarks to simulate fragmented bones (218 combinations). The results of the whole bone analysis resulted in 95.35% testing accuracy. The results of the modeled fragmentary analysis consisted of 164 combinations which exhibit a 90% or higher accuracy in sex prediction; and twelve combinations which exhibit 96% or higher accuracy in sex prediction. In particular, two landmarks clustered around the ventral arc of the pubic bone performed the best, indicating this is the most sexually dimorphic portion of the bone. These results indicate that three-dimensional geometric morphometrics is a valid method to be applied to sex determination in forensic anthropology.

Sex estimation from the greater sciatic notch: a comparison of classical statistical models and machine learning algorithms

The greater sciatic notch (GSN) is a useful element for sex estimation because it is quite resistant to damage, and thus it can often be assessed even in poorly preserved skeletons. This study aimed to develop statistical models for sex estimation based on visual and metric analyses of the GSN, and additional variables linked to the GSN. A total of 60 left coxal bones (30 males and 30 females) were analysed. Fifteen variables were measured, and one was a morphologic variable. These 16 variables were used for the comparison of six statistical models: linear discriminant analysis (LDA), regularized discriminant analysis (RDA), penalized logistic regression (PLR) and flexible discriminant analysis (FDA), and two machine learning algorithms, support vector machine (SVM) and artificial neural network (ANN). The statistical models were built in two steps: firstly, only with the GSN variables (group 1), and secondly, with the whole variables (group 2), in order to see if the models including all the variables performed better. The overall accuracy of the models was very close, ranging from 0.92 to 0.97 using specific GSN variables. When additional variables starting from the deepest point of GSN are available, it is worth to use them, because the accuracy increases. PLR (after optimization of parameters) stands out from other statistical models. The position of the deepest point of GSN (Fig. 2) probably plays a crucial role for the sexual dimorphism, as stated by the good performance of the visual assessment of this point and the fact that the A2 angle (posterior angle with the deepest point of the GSN as the apex) is included in all models.

Sacral morphometrics for sex estimation of dead cases in Central Thailand

Sex estimation by various forensic anthropology approaches is a crucial factor for identification of human skeletal remains. However, inexpensive, uncomplicated and reliable methods are still required, especially in a remote crime scene and a high crime incidence area. Here, we examined 13 sacral parameters from 78 independent skeletons derived from deceases found in Central Thailand (male, n = 46; female, n = 32) using simple standard anthropometric techniques for sex allocation. Discriminant analysis exhibited that anterior-posterior diameter of S₁ vertebra corpus (APS) is the most accurate sacral parameter for sex determination in our study with 82.1% of correct discrimination rate. The accuracy could be improved up to 97.4% when additional three sacral variables including the length of sacrum measured from the medial anterior-superior sacral promontory to the medial anterior-inferior S₅ vertebra (ASL), alar index (ALI), and the maximum anterior breadth of sacrum measured across sacral alar (ABS) were computed together with APS. These encourage the use of sacral morphometrics for sex assessment of human sacrum remains in Central Thailand. However, further investigation with broadening sacral morphometric data across the country might provide a promising sex determination equation from a sacral skeleton for Thai population.

Pelvic bone morphometric analysis in the dugong (Dugong dugon)

The dugong (Dugong dugon Müller) is recognized as an endangered marine mammal. There is limited available anatomical data on the dugong's skeletal system, while what is available has not been well established due to the limited number of archived samples and limited access to them. Importantly, there are certain key questions that should be answered when examining the bones and/or remains of animals such as; what kind of bone is it?; what species does it belong to?; what sex was the animal?; how old was the animal? or how big was it?, etc. In this study, we have focused on the pelvic bone of the dugong by asserting the hypothesis that pelvic bone morphology is related to age, sex, and body size. Here, we have established certain morphometric data encompassing 8 parameters and 5 indexes to analyze the morphology of the pelvic bones obtained from 88 specimens (45 dugongs). We will present three main findings: (1) the pelvic bone in mature male subjects is larger than it is in female subjects, (2) a high rate of accuracy can be established for sex identification using morphometric data obtained from the pelvic bone, and (3) the pelvic bone has the highest degree of correlation with body length, followed by body weight and age. Notably, the important data on the pelvic bone of the dugong acquired in this study can be reliable and extremely useful in sex identification and body size estimation.

Sex estimation from upper limb bones in a Thai population

Sex estimation from skeletal remains is an important practice for forensic human identification. The aims of this study were to assess sexual dimorphism and to develop discriminant function equations for sex estimation using 12 measurements of upper limb bones (humerus, ulna, and radius) in a Thai population. The sample consisted of 228 Thai skeletons (114 males and 114 females) from the Forensic Osteology Research Center, Chiang Mai University, Chiang Mai, Thailand. All skeletal length variables were measured according to the Standards for Data Collection from Human Skeletal Remains. The values of measurements were used to develop the sex estimation equations using univariate and multivariate discriminant function analyses. The results of sexual dimorphism showed that upper limb bone lengths of males were statistically significantly longer than those of females in all dimensions (P<0.05). For univariate discriminant function analysis, the results showed that the epicondylar breadth of the humerus, the physiological length of the ulna, and the antero-posterior diameter at the midshaft of the radius were the best indicators for sex estimation in the humerus, ulna, and radius, respectively. Moreover, the multivariate discriminant function equation using all variables of the ulna and radius was the best indicator for sex estimation. In conclusion, the discriminant function equations derived from upper limb bone measurements provided highly accurate sex estimation in Thai samples. Therefore, these equations using humerus, radius, and ulna measurements can be applied for sex estimation with good accuracy in Thais.

Sex estimation using subpubic angle from reconstructed three-dimensional computed tomography pelvic model in a contemporary Malaysian population

Research in forensic anthropology is recent in Malaysia due to limited access to documented skeletal collections. However, advanced imaging techniques provide virtual bone samples for use in morphometric studies to establish population-specific standards by virtual anthropology. This study examined sexual dimorphism in the subpubic angle using a three-dimensional computed tomography model of the pelvis, in a contemporary Malaysian population. The sample comprised multidetector computed tomography (MDCT) scans of 50 male and 50 female adults. Segmentation of the MDCT scans was performed using 3D Slicer, and four landmarks were acquired using Stratovan Checkpoint for the subpubic angle measurement. The technical error of measurement (TEM), relative TEM, and coefficient of reliability (R) exhibited high reliability in measurements. Results showed that the subpubic angle in males was 68.6°±7.6° and in females 87.4°±6.5°. The subpubic angle in females was significantly larger than in males (P<0.001). Inverse correlation was found between the subpubic angle and age, in both males (r=−0.449, P<0.01) and females (r=−0.385, P<0.01). The overall accuracy of sex estimation using the subpubic angle was 94% (P<0.001). The subpubic angle, with a demarcating point of 78.6°, showed a sensitivity and specificity of 94% in the classification of female individuals. In conclusion, sex estimation using the subpu bic angle is highly accurate, with a high degree of expected sensitivity and specificity in the Malaysian population.

CADOES: An interactive machine-learning approach for sex estimation with the pelvis

The pelvis is consistently regarded as the most sexually dimorphic region of the human skeleton, and methods for sex estimation with the pelvic bones are usually very accurate. In this investigation, population-specific osteometric models for the assessment of sex with the pelvis were designed using a dataset provided by J.A. Serra (1938) that included 256 individuals (131 females and 125 males) from the Coimbra Identified Skeletal Collection and 38 metric variables. The models for sex estimation were operationalized through an online application and decision support system, CADOES. Different classification algorithms generated high accuracy models, ranging from 85% to 92%, with only three variables; and from 85.33% to 97.33%, with all 38 variables. CADOES conveys a probabilistic prediction of skeletal sex, as well as a suite of attributes with educational applicability in the fields of human skeletal anatomy and statistics. This study upholds the value of the pelvis for the estimation of skeletal sex and provides models for that can be applied with high accuracy and low bias.

Testing landmark redundancy for sex-based shape analysis of the adult human os coxa

OBJECTIVES

To test the individual effectiveness of common landmarks used in sex estimation of whole adult coxal bones in sex-based shape analysis and propose a method to determine how many principal components of sex-based shape to include for discriminant function analysis.

METHODS

Three-dimensional models (NextEngine desktop laser scanner) of left and right os coxae from 396 individuals (William Bass Skeletal Collection, Forensic Anthropology Centre, University of Tennessee, Knoxville, TN) were subjected to shape analysis using 32 landmarks (Landmark 3.6, Institute for Data Analysis and Visualization). Each landmark was individually removed and subjected to a new principal component analysis to identify the effect omitting a landmark has on PC1/PC2 ordination. Landmarks that poorly discriminated sex-based shape were considered redundant for analysis on sex estimation.

RESULTS

This study identified 17 landmarks that represent sex-based shape of right and left coxal bones most effectively, these are: the anterior superior iliac spine; posterior superior iliac spine; posterior inferior iliac spine; iliac crest; apex of the auricular surface; greater sciatic notch; ischial spine; superior, inferior and distal points on ischial tuberosity; superior, inferior and midpoint on the symphyseal face; arcuate eminence; ischiopubic ramus; posterosuperior and anterosuperior points on the acetabular rim. The first and second PCs of the 17-landmark configuration correctly predicted sex in 98.5% of cases; better than a 32-landmark configuration (96%) and better than previous landmark studies on whole coxal bone sex-based shape.

CONCLUSIONS

These 17 landmarks represent more meaningful data for sex-based shape analysis in PC1 and 2 and concentrate meaningful sex-based shape data to the first five PCs that make up over 50% of the total shape variance.

Dimensions around the nutrient foramina of the tibia and fibula in the estimation of sex

Sex estimation from skeletal remains is one of the key components in establishing a biological profile and consequent identification of an individual in a forensic and medico-legal practice. The use of dimensions around the nutrient foramen in instances where long bones may be fragmented and damaged is of benefit due to the fact that the nutrient foramen is easily identifiable and may be preserved on the shaft of long bones. This study is an investigation of the usefulness of various measurements around the nutrient foramen of the tibia and fibula of South Africans in an attempt to develop osteometric standards for sex estimation. The sample included 206 tibiae and 204 fibulae of South African Africans (SAA) and South African whites (SAW) procured from the Raymond A. Dart Collection of Human Skeletons based at the University of the Witwatersrand. Sex was correctly classified for the tibia with an accuracy ranging between 79-82% in SAA and 84-88% in SAW, with the circumference at the level of the nutrient foramen as the single best predictor of sex in both populations. An accuracy ranging from 69 to 74% in SAA and 70-77% in SAW was observed for the combined measurements on the fibula. The current study confirms the usefulness of measurements around the nutrient foramen of the tibia in the assignment of sex. However functions of the fibula generally performed poorly and should be used with caution.