Sex prediction from the femur and hip bone using a sample of CT images from a Spanish population

Sex estimation from coxal bones using deep learning in a population balanced by sex and age

In the field of forensic anthropology, researchers aim to identify anonymous human remains and determine the cause and circumstances of death from skeletonized human remains. Sex determination is a fundamental step of this procedure because it influences the estimation of other traits, such as age and stature. Pelvic bones are especially dimorphic, and are thus the most useful bones for sex identification. Sex estimation methods are usually based on morphologic traits, measurements, or landmarks on the bones. However, these methods are time-consuming and can be subject to inter- or intra-observer bias. Sex determination can be done using dry bones or CT scans. Recently, artificial neural networks (ANN) have attracted attention in forensic anthropology. Here we tested a fully automated and data-driven machine learning method for sex estimation using CT-scan reconstructions of coxal bones. We studied 580 CT scans of living individuals. Sex was predicted by two networks trained on an independent sample: a disentangled variational auto-encoder (DVAE) alone, and the same DVAE associated with another classifier (Crecon). The DVAE alone exhibited an accuracy of 97.9%, and the DVAE + Crecon showed an accuracy of 99.8%. Sensibility and precision were also high for both sexes. These results are better than those reported from previous studies. These data-driven algorithms are easy to implement, since the pre-processing step is also entirely automatic. Fully automated methods save time, as it only takes a few minutes to pre-process the images and predict sex, and does not require strong experience in forensic anthropology.

Sex assessment using the radius bone in a French sample when applying various statistical models

Sex estimation of skeletal remains is one of the most important tasks in forensic anthropology. The radius bone is useful to develop standard guidelines for sex estimation across various populations and is an alternative when coxal or femoral bones are not available.The aim of the present study was to assess the sexual dimorphism from radius measurements in a French sample and compare the predictive accuracy of several modelling techniques, using both classical statistical methods and machine learning algorithms.A total of 78 left radii (36 males and 42 females) were used in this study. Sixteen measurements were made. The modelling techniques included a linear discriminant analysis (LDA), flexible discriminant analysis (FDA), regularised discriminant analysis (RDA), penalised logistic regression (PLR), random forests (RF) and support vector machines (SVM).The different statistical models showed an accuracy of classification that is greater than 94%. After selection of variables, the accuracies increased to 97%. The measurements made at the proximal part of the radius (sagittal and transversal diameters of the head, and sagittal diameter of the neck), at distal part (maximum width of the distal epiphysis) and of the entire bone (maximum length) stand out among the various models.The present study suggests that the radius bone constitutes a valid alternative for sex estimation of skeletal remains with comparable classification accuracies to the pelvis or femur and that the non-classical statistical models may provide a novel approach to sex estimation from the radius bone. However, the extrapolation of the current results cannot be made without caution because our sample was composed of very aged individuals.

Reconstruction of full femora from partial bone fragments for anthropological analyses using statistical shape modeling

OBJECTIVES

Due to taphonomic processes such as burial, fire, or animal activity, bones are often found incomplete, which can pose problematic for establishing the biological profile of the deceased using anthropological methods. The aim of this study is to test the feasibility of using statistical shape modeling (SSM) to reconstruct full femora from simulated partial femora and determine the accuracy of the reconstruction. Moreover, we assess the accuracy of sex estimation and the degree of stature error added based on the reconstructed femur using different anthropological methods.

METHODS

A total of 42 (28 female, 14 female) 3D models of left femora extracted from computed tomography (CT) scans were used. We performed a leave-one-out cross-validation (LOOCV) where 41 bones were used to build the SSM and one bone was used for testing. This bone was cut in 1 cm steps proximally, distally and from both ends up to 10 cm, reconstructed using SSM, and tested using the methods established by Stewart and Purkait (2005), Trotter and Gleser (1952), as well as a method based on SSM. with landmarks being automatically identified.

RESULTS

The error induced by reconstructing the femur to the length measurements was low, which translated into useful stature estimations (single sided cuts up to 10 cm: 0.4-1.1%, double sided<2% for cuts shorter than 6 cm). Using Purkaits method for sex estimation on reconstructed bones looked promising as well (single sided: 90.5% when compared to applying Purkaits method on the original bone, double sided 78.6% (10 cm cut) to 97.6% (1-3 cm cuts)) Using SSM for sex classification looked promising as well (single sided cut: 81-85.7%, double sided cut: 59.5-85.3%) CONCLUSION: SSM can be used to reconstruct fragmented femora. These reconstructions can be used for sex and stature estimations, at the cost of lower accuracy. Using SSM might give investigators an additional tool to gain information about the biological profile of a deceased in cases where the fragmentation of a femur does not allow for using other anthropological methods.

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.

Adult sex estimation from the minimum supero-inferior femoral neck diameter in a contemporary osteological sample from Buenos Aires, Argentina

Sex estimation of adult skeletons is an important step in forensic analysis. Although the femur has been metrically studied for sex assessment around the world, very limited information is actually available on modern populations of Argentina. In this paper, the estimation of sex based on the metric evaluation of the supero-inferior femoral neck diameter (SID) in a reference osteological collection from the contemporary Chacarita Cemetery of Buenos Aires City (Argentina), is evaluated. Protocols generated using SID in other three reference skeletal samples are also tested on this collection. One hundred and sixty-four individuals of both sexes and between 24 and 96 years old are analyzed. Inter and intra observer errors suggest that the replicability of the procedure is adequate. The sectioning point calculated from the direct measurements is 30.86 mm and results show a high degree of dimorphism. The proportions of correct sex discrimination and the likelihoods of correct allocation obtained with the direct measurements, along with the results of a discriminant function, a binary logistic regression and a Bayesian approach, are all higher than 0.85 (0.85-0.93 for females, 0.88-0.91 for males). When the formulae from other samples are used in the Chacarita Collection, the percentages of correct estimations range between 72.41% and 81.03% for females and between 80.46% and 88.50% for males, while the likelihoods are between 0.73 and 0.81 for females and between 0.79 and 0.82 for males. As the values for the estimations obtained using the statistical procedures generated in the present research are higher than those available for other collections, the method is more adequate to use in the analysis of contemporary skeletal remains from Buenos Aires and surrounding areas. The trends identified highlight the importance of population-specific metric methodologies in forensic contexts and deserve future testing in contemporary samples from neighbouring regions.

Sex estimation from morphology in living animals and dinosaurs

Sexual dimorphism is a prevalent feature of sexually reproducing organisms yet its presence in dinosaurs has recently been questioned. However, the inferred absence of sexual dimorphism may be a methodological artefact, rooted in the lack of systematic knowledge concerning how sexual dimorphism of living animals behaves statistically. To start building such knowledge, I re-analysed published data of 139 species of living animals that are sexually dimorphic. The previous method used for dinosaurs recognized only 5% of the living species correctly as dimorphic. This low rate is largely caused by the tilting of ordinated multivariate space due to interactions between size and shape dimorphisms, low signal/noise ratios and inclusion of outliers. The rate can be improved to 50% by modifying the method but not further, unless the information on the sex of individual specimens is used. Such information is unavailable in dinosaurs, so sexual dimorphism probably cannot be established for a large proportion of sexually dimorphic dinosaurs. At the same time, about 32% of the 139 are strongly sexually dimorphic, and can be re-sexed from shape with misclassification rates below 0.05. A reassessment of dinosaurian data suggests that sexual dimorphism likely existed at least in some species, such as Allosaurus fragilis.

Gender determination in adults using calcaneal diameters from lateral foot X-ray images in the Iranian population

Background: Using morphologic features of the bones is the basis of gender determination in anthropology and forensic medicine. In this study, we evaluated the calcaneus diameters for gender determination in the Iranian population.

Methods: This cross-sectional study was conducted on Iranians referring to Hazrat-e Rasool Hospital’s radiology ward for plain lateral X-ray of the foot. Lateral foot X-rays from 100 men and 100 women were gathered and evaluated for calcaneal indexes. These patients aged between 18 and 80 years old who did not suffer major trauma to the calcaneus bone were recruited. Using a picture archiving and communication system (PACS), four variables were calculated for each X-ray graph: Maximum anterior-posterior length of the calcaneus (MAXL), Maximum height of the bone (MAXH), Height of the cuboid facet (CFH) and Height the calcaneal body (BH). Cut off points for each index were calculated using the area under curve (AUC) in ROC curves.

Results: Lateral foot X-rays from 100 men and 100 women were gathered and evaluated for calcaneal indexes. The means of the four indexes were compared between the sexes which showed all four means are significantly different p value <0.001. AUC for MAXL in differentiating the genders was 0.824, which showed 86.8 as the cut off with a sensitivity of 80% and specificity of 69.0%. Cut off point for MAXH was set at 59.8 with sensitivity and specificity of 78.0% and 60.0%, respectively. For BH, 49.5 was set as the cut off point with a sensitivity of 79.0% and specificity of 64.0%. The best cut off point for CFH was 27.8 with 76.0% sensitivity and 63.0% specificity.

Conclusion: It can be concluded that the calcaneal diameters are reliable criteria for sex determination. Although the cutoff points are different between various races and populations, it is evident that these diameters can be used for sex determination in general.

Sex estimation from the femur using discriminant function analysis in a Central Indian population

Sexual dimorphism is one of the major factors responsible for apparent variations in human skeletal anatomy. Establishing the biological profile of the deceased is essential for personal identification in forensic and archaeological casework. To develop a reliable biological profile, sex allocation is an integral step required to determine age, race/ancestry and stature, given observable differences in aging and growth patterns and variations in morphological traits relating to ancestry. Sex estimation from long bones by visual examination is very difficult. However, metric observations are more objective and effective. This osteometric analysis focused on sex estimation from the femur using discriminant function analysis. Fourteen measurements were taken directly on 175 dry femora (117 males and 58 females), aged 20–60 years, from the Chhattisgarh region of Central India. Student’s t-test was applied to assess significant sex and size differences. Direct and stepwise discriminant function analyses were applied to derive discriminant function models for sex estimation. The three parameters that were selected for the discriminant function analysis included: transverse head diameter, bi-trochanteric distance and maximum shaft diameter. Males were more accurately classified than females. An overall accuracy of 80.6% was reported with direct discriminant function analysis and 76% with stepwise discriminant function analysis upon cross-validation. The transverse head diameter emerged to be the best predictor of sex. This study provides a database and standards for sex estimation from skeletal remains of an unknown nature based on discriminant function equations. This is one of the few studies conducted in India on dry bones, and we anticipate that it will guide forensic specialists in the identification of unknown skeletons from this region.

Virtual forensic anthropology: The accuracy of osteometric analysis of 3D bone models derived from clinical computed tomography (CT) scans

Clinical radiology is increasingly used as a source of data to test or develop forensic anthropological methods, especially in countries where contemporary skeletal collections are not available. Naturally, this requires analysis of the error that is a result of low accuracy of the modality (i.e. accuracy of the segmentation) and the error that arises due to difficulties in landmark recognition in virtual models. The cumulative effect of these errors ultimately determines whether virtual and dry bone measurements can be used interchangeably. To test the interchangeability of virtual and dry bone measurements, 13 male and 14 female intact cadavers from the body donation program of the Amsterdam UMC were CT scanned using a standard patient scanning protocol and processed to obtain the dry os coxae. These were again CT scanned using the same scanning protocol. All CT scans were segmented to create 3D virtual bone models of the os coxae ('dry' CT models and 'clinical' CT models). An Artec Spider 3D optical scanner was used to produce gold standard 'optical 3D models' of ten dry os coxae. The deviation of the surfaces of the 3D virtual bone models compared to the gold standard was used to calculate the accuracy of the CT models, both for the overall os coxae and for selected landmarks. Landmark recognition was studied by comparing the TEM and %TEM of nine traditional inter-landmark distances (ILDs). The percentage difference for the various ILDs between modalities was used to gauge the practical implications of both errors combined. Results showed that 'dry' CT models were 0.36-0.45mm larger than the 'optical 3D models' (deviations -0.27mm to 2.86mm). 'Clinical' CT models were 0.64-0.88mm larger than the 'optical 3D models' (deviations -4.99mm to 5.00mm). The accuracies of the ROIs were variable and larger for 'clinical' CT models than for 'dry' CT models. TEM and %TEM were generally in the acceptable ranges for all ILDs whilst no single modality was obviously more or less reliable than the others. For almost all ILDs, the average percentage difference between modalities was substantially larger than the average percentage difference between observers in 'dry bone' measurements only. Our results show that the combined error of segmentation- and landmark recognition error can be substantial, which may preclude the usage of 'clinical' CT scans as an alternative source for forensic anthropological reference data.

CT-based sex estimation on human femora using statistical shape modeling

OBJECTIVES

Estimating the sex of decomposed corpses and skeletal remains of unknown individuals is one of the first steps in the identification process in forensic contexts. Although various studies have considered the femur for sex estimation, the focus has primarily been on a specific single or a handful of measurements rather than the entire shape of the bone. In this article, we use statistical shape modeling (SSM) for sex estimation. We hypothesize that the accuracy of sex estimation will be improved by using the entire shape.

MATERIALS AND METHODS

For this study, we acquired a total of 61 femora from routine postmortem CT scans at the Institute for Forensic Medicine of the University of Zurich. The femora were extracted using segmentation technique. After building a SSM, we used the linear regression and nonlinear support vector machine technique for classification.

RESULTS

Using linear logistic regression and only the first principal component of the SSM, 76% of the femora were correctly classified by sex. Using the first five principal components, this value could be increased to 80%. Using nonlinear support vector machines and the first 20 principal components increased the rate of correctly classified femora to 87%.

DISCUSSION

Despite some limitations, the results obtained by using SSM for sex estimation in femur were promising and confirm the findings of other studies. Sex estimation accuracy, however, is not significantly improved over single or multiple linear measurements. Further research might improve the sex determination process in forensic anthropology by using SSM.

Reliability of palatal rugoscopy for sexual dimorphism in forensic dentistry: A systematic literature review and meta-analysis

OBJECTIVE

This study aimed to assess the validity of palatal rugoscopy for sexual dimorphism in the casework routine of forensic dentistry.

DESIGN

A systematic literature reviews was established following the Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) and Cochrane guidelines. Six electronic databases were searched as the primary source of information. "Grey literature" was included to avoid selection and publication bias. As a secondary source of information, the reference lists of the eligible studies were also consulted to increase the search spectrum. Methodological quality and risk of bias were assessed with Joanna Briggs Institute Critical Appraisal Tools for Systematic Reviews. Statistic tests, namely the meta-analysis of diagnostic accuracy, Cochran Q test, and I2 test, were performed to verify the heterogeneity between the eligible studies.

RESULTS

The systematic search resulted in 263 studies, out of each 8 fulfilled the inclusion criteria. An additional eligible article was included after the search in reference lists. From the 9 studies that underwent qualitative data extraction, six were selected for quantitative analysis. The meta-analysis of grouped sex estimates showed sensitivity and specificity rates of 89% and 83%, respectively. The Area Under the Curve reached 0.93. High heterogeneity and important methodological limitations were detected among the studies.

CONCLUSION

Palatal rugoscopy seems to have discriminant power for sexual dimorphism. However, the limitations found specifically in each study and the strong heterogeneity across studies suggest that palatal rugoscopy lacks evidence-based confirmation for reliable application as a sole tool for sexual dimorphism in practice.

Sex estimation with the total area of the proximal femur: A densitometric approach

The estimation of sex is a central step to establish the biological profile of an anonymous skeletal individual. Imaging techniques, including bone densitometry, have been used to evaluate sex in remains incompletely skeletonized. In this paper, we present a technique for sex estimation using the total area (TA) of the proximal femur, a two-dimensional areal measurement determined through densitometry. TA was acquired from a training sample (112 females; 112 males) from the Coimbra Identified Skeletal Collection (University of Coimbra, Portugal). Logistic regression (LR), linear discriminant analysis (LDA), reduce error pruning trees (REPTree), and classification and regression trees (CART) were employed in order to obtain models that could predict sex in unidentified skeletal remains. Under cross-validation, the proposed models correctly estimated sex in 90.2-92.0% of cases (bias ranging from 1.8% to 4.5%). The models were evaluated in an independent test sample (30 females; 30 males) from the 21st Century Identified Skeletal Collection (University of Coimbra, Portugal), with a sex allocation accuracy ranging from 90.0% to 91.7% (bias from 3.3% to 10.0%). Overall, data mining classifiers, especially the REPTree, performed better than the traditional classifiers (LR and LDA), maximizing overall accuracy and minimizing bias. This study emphasizes the significant value of bone densitometry to estimate sex in cadaveric remains in diverse states of preservation and completeness, even human remains with soft tissues.

The geometrical precision of virtual bone models derived from clinical computed tomography data for forensic anthropology

Almost all European countries lack contemporary skeletal collections for the development and validation of forensic anthropological methods. Furthermore, legal, ethical and practical considerations hinder the development of skeletal collections. A virtual skeletal database derived from clinical computed tomography (CT) scans provides a potential solution. However, clinical CT scans are typically generated with varying settings. This study investigates the effects of image segmentation and varying imaging conditions on the precision of virtual modelled pelves. An adult human cadaver was scanned using varying imaging conditions, such as scanner type and standard patient scanning protocol, slice thickness and exposure level. The pelvis was segmented from the various CT images resulting in virtually modelled pelves. The precision of the virtual modelling was determined per polygon mesh point. The fraction of mesh points resulting in point-to-point distance variations of 2 mm or less (95% confidence interval (CI)) was reported. Colour mapping was used to visualise modelling variability. At almost all (>97%) locations across the pelvis, the point-to-point distance variation is less than 2 mm (CI = 95%). In >91% of the locations, the point-to-point distance variation was less than 1 mm (CI = 95%). This indicates that the geometric variability of the virtual pelvis as a result of segmentation and imaging conditions rarely exceeds the generally accepted linear error of 2 mm. Colour mapping shows that areas with large variability are predominantly joint surfaces. Therefore, results indicate that segmented bone elements from patient-derived CT scans are a sufficiently precise source for creating a virtual skeletal database.

Sex estimation based on tooth measurements using panoramic radiographs

BACKGROUND

Sex determination is an important step in establishing the biological profile of unidentified human remains.

AIM

The aims of the study were, firstly, to assess the degree of sexual dimorphism in permanent teeth, based on digital tooth measurements performed on panoramic radiographs. Secondly, to identify sex-related tooth position-specific measurements or combinations of such measurements, and to assess their applicability for potential sex determination.

MATERIALS AND METHODS

Two hundred digital panoramic radiographs (100 males, 100 females; age range 22-34 years) were retrospectively collected from the dental clinic files of the Dentomaxillofacial Radiology Center of the University Hospitals Leuven, Belgium, and imported in image enhancement software. Tooth length- and width-related variables were measured on all teeth in upper and lower left quadrant, and ratios of variables were calculated. Univariate and multivariate analyses were performed to quantify the sex discriminative value of the tooth position-specific variables and their combinations.

RESULTS

The mandibular and maxillary canine showed the greatest sexual dimorphism, and tooth length variables had the highest discriminative potential. Compared to single variables, combining variables or ratios of variables did not improve substantially the discrimination between males and females.

DISCUSSIONS AND CONCLUSIONS

Considering that the discriminative ability values (area under the curve (AUC)) were not higher than 0.80, it is not advocated to use the currently studied dental variables for accurate sex estimation in forensic practice.

Sexual determination based on multidetector computed tomographic measurements of the second cervical vertebra in a contemporary Japanese population

Accurate sex estimation is important in forensic investigation to determine the identity of unknown individuals. The aim of this study was to investigate the accuracy of sex assessment based on measurements of the second cervical vertebra (C2) using computed tomographic (CT) images in a Japanese population and to develop discriminant function formulae. The data were collected from 224 Japanese cadavers (112 male subjects, 112 female subjects) on which postmortem CT scanning and subsequent forensic autopsy were performed. Nine CT measurements of the C2 were performed for CT images of each subject. The measurements were assessed using descriptive statistics and discriminant function analyses (DFA). All of the measurements demonstrated significant sexual dimorphism. Multiple DFA with stepwise variable selection resulted in multivariable models; a five-variable model reached an accuracy rate of 92.9%. Our results suggest that metric analysis based on CT images of the C2 can accurately determine the sex from the human skeletal remains in a contemporary Japanese population and may be useful for sex estimation in forensic anthropology.