Accuracy Of Sex Estimation Research Articles

A new metric method for sex estimation using three-dimensional imaging of the nuchal crest.

In Walker's nonmetric method, the nuchal crest serves as the representative region for indicating sexual dimorphism in cranial bones. However, the accuracy of sex estimation using the nuchal crest is lower than that using other anatomical regions. Furthermore, because of the protruding processes and structurally challenging features characterized by uneven and rough surfaces, there is a lack of metric methods for sex estimation, making quantification challenging. In this study, we aimed to validate a derived metric method for sex estimation by reconstructing the nuchal crest region in three-dimensional (3D) images obtained from computed tomography scans of cranial bones and compare its accuracy with that of the nonmetric method. A total of 648 images were collected, with 100 randomly selected for use in the nonmetric method. We applied our metric method to the remaining 548 images. Our findings showed that the surface area of the nuchal crests was greater in male individuals than in female individuals. The nuchal crest surface area quantified by the metric method increased the accuracy of sex estimation by 48% compared with that by the nonmetric method. Our metric method for sex estimation, which quantifies the nuchal crest surface area using 3D images of the skull, led to a high sex estimation accuracy of 93%. Future studies should focus on proposing and quantifying new measurement methods for areas showing sexual characteristics in the skull that are difficult to measure, thereby enhancing the accuracy and reliability of sex estimation in human skeletal identification across various fields.

Enhancing Sex Estimation Accuracy with Cranial Angle Measurements and Machine Learning.

The development of current sexing methods largely depends on the use of adequate sources of data and adjustable classification techniques. Most sex estimation methods have been based on linear measurements, while the angles have been largely ignored, potentially leading to the loss of valuable information for sex discrimination. This study aims to evaluate the usefulness of cranial angles for sex estimation and to differentiate the most dimorphic ones by training machine learning algorithms. Computed tomography images of 154 males and 180 females were used to derive data of 36 cranial angles. The classification models were created by support vector machines, naïve Bayes, logistic regression, and the rule-induction algorithm CN2. A series of cranial angle subsets was arranged by an attribute selection scheme. The algorithms achieved the highest accuracy on subsets of cranial angles, most of which correspond to well-known features for sex discrimination. Angles characterizing the lower forehead and upper midface were included in the best-performing models of all algorithms. The accuracy results showed the considerable classification potential of the cranial angles. The study demonstrates the value of the cranial angles as sex indicators and the possibility to enhance the sex estimation accuracy by using them.

Sex estimation based on glabella morphology in contemporary Brazilian human skulls

BackgroundEstimating sex from a dry skull depends on studying validated and specific traits. One such reference area exhibiting sexual dimorphism is the glabella, located on the frontal bone. This anatomical landmark is easily classified and shows promising results in sexual identification due to its magnitude variations between sexes. The present study is methodologically based on Walker’s approach, which visually analyzes cranial traits and scores them according to their morphology. This study aimed to investigate the sex estimation of dry skulls from Brazilian human skeletons for human identification through macroscopic analysis of the glabella. This analytical, quantitative, cross-sectional study utilized a sample of 471 skulls from both sexes, aged 25 years or older, belonging to the contemporary collection of the Center for Studies in Forensic Anthropology at the Faculty of Dentistry, University of Pernambuco (CEAF/FOP/UPE), Brazil. Data were recorded in an Excel spreadsheet and subsequently subjected to statistical analysis using IBM© SPSS (version 22.0).ResultsInitial observation of the skeletons excluded 52 (11.0%) due to age below 25 years, absence of a skull, or compromised glabella region, resulting in a final sample of 419 skulls. The mean age was 66.6 years, with a median of 67, a minimum of 25, and a maximum of 109 years. Regarding glabella types, score 2 showed the highest frequency (35.6%), while score 5 had the lowest percentage (7.9%). A statistically significant association was found between female sex and glabella scores 1 and 2. Also, individuals aged over 60 presented more glabella scores 1 and 2. The sex estimation accuracy for the sample was 76.1%, with females having a higher percentage of correct observations than males.ConclusionsThe morphology of the glabella provides useful information for estimating sex in the biological profile. However, further studies on this morphological trait in other Brazilian osteological collections are encouraged to establish a national profile and contribute to human identification procedures in the country.

Estimating osteological sex using predictive geometric morphometric analyses of the greater sciatic notch

Accurately estimating the biological sex of human skeletal remains is crucial in both forensic and archaeological contexts for constructing biological profiles. Presently, one of the most commonly used methods involves an ordinal scale describing the shape of the greater sciatic notch (GSN). However, this approach is limited by variations influenced by temporal, geographic, and ancestral factors affecting pelvic morphology. Consequently, its reliable applicability is restricted to populations resembling the original reference group. Recent advancements in quantitative analyses offer a promising alternative by enabling detailed measurement of subtle morphological changes, thus enhancing the accuracy of sex estimation using skeletal pelvic remains. In this study, we employ 2D landmark-based geometric morphometrics (GMM) to develop a protocol for pelvic sex estimation by quantifying the curve and angle of the GSN. These techniques are applied to both a contemporary population of adult European-Americans of known biological sexes (33 females, 38 males) and an archaeological population (n = 73) from south-west England. Our analysis reveals that our GMM approach achieves a 90 % accuracy rate in modern populations. Results indicate that both GSN morphology and angle are highly indicative of biological sex, allowing confidence in sex estimations of archaeological remains using these features.

Sex estimation from mandibular morphometry using discriminant analysis–CT scan based retrospective study

It is well known that skeletal characteristics vary among different populations. Sex dimorphic characteristics of the mandible have been reported from studies using either mandible bone or computer tomography (CT) scan images of the mandible to test its efficacy in estimating sex. Mandibular studies for estimating sex in any particular population group may not hold well for different populations owing to inherent geographical variations. With this background, we assessed the validity of mandible measurements from CT scan images to determine sex in the South Indian population. As a part of our study, 11 metric parameters and 1 angular parameter were measured and analyzed. The mean values of all the parameters were significantly higher for males as compared to females. Bigonial breadth indicated the best discriminatory ability of the study. Mandibular angle had the least predictive accuracy among all the discriminant functions studied. We further observed that a combination of parameters gave the best overall classification rate (92.3 %). When the same functions were tested on an independent testing data set, a combination of parameters and bigonial breadth gave the best classification rate (82.1 %) which was consistent. We concluded that the mandible has a high accuracy for sex estimation. All the parameters studied demonstrated statistically significant differences between the two sexes except the mandibular angle.

Nonmetric population‐specific sex estimation based on the skull using logistic regression for Flemish samples

AbstractThere are very few sex estimation methods specifically designed for or tested on Belgian skulls. The currently used methods for European populations have been developed using North American collections where individuals are categorized as White and/or having European ancestry. These frequently show discordance between the pelvic sex and cranial sex estimations highlighting the need for population specific methods. To fill this gap in our knowledge, several sex estimation methods, using 15 qualitative skull features, were tested on two Flemish (northern Belgium) skeletal collections; one archaeological (15th–17th century) and one forensic (20th century). The features were tested by themselves as well as in different combinations using logistic regression. The glabella is considered the best lone feature with a minimal accuracy of 78.4% and a sex bias of −5.2%. Furthermore, four sex estimation equations were developed for the skull, the cranium, the mandible, and the frontal bone separately. The skull has an accuracy of 89.3% and a bias of 0.8%. For the cranium, this is 87.5% and −0.3%, respectively, for the mandible 85.1% and −0.1%, and for the frontal bone it is 80.4% and −4.6%. The various tests confirm that many skull features can be used for sex estimation and can generate high sex estimation accuracy.

Different machine learning methods based on maxillary sinus in sex estimation for northwestern Chinese Han population.

Sex estimation is a critical aspect of forensic expertise. Some special anatomical structures, such as the maxillary sinus, can still maintain integrity in harsh environmental conditions and may be served as a basis for sex estimation. Due to the complex nature of sex estimation, several studies have been conducted using different machine learning algorithms to improve the accuracy of sex prediction from anatomical measurements. In this study, linear data of the maxillary sinus in the population of northwest China by using Cone-Beam Computed Tomography (CBCT) were collected and utilized to develop logistic, K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and random forest (RF) models for sex estimation with R 4.3.1. CBCT images from 477 samples of Han population (75 males and 81 females, aged 5-17 years; 162 males and 159 females, aged 18-72) were used to establish and verify the model. Length (MSL), width (MSW), height (MSH) of both the left and right maxillary sinuses and distance of lateral wall between two maxillary sinuses (distance) were measured. 80% of the data were randomly picked as the training set and others were testing set. Besides, these samples were grouped by age bracket and fitted models as an attempt. Overall, the accuracy of the sex estimation for individuals over 18 years old on the testing set was 77.78%, with a slightly higher accuracy rate for males at 78.12% compared to females at 77.42%. However, accuracy of sex estimation for individuals under 18 was challenging. In comparison to logistic, KNN and SVM, RF exhibited higher accuracy rates. Moreover, incorporating age as a variable improved the accuracy of sex estimation, particularly in the 18-27 age group, where the accuracy rate increased to 88.46%. Meanwhile, all variables showed a linear correlation with age. The linear measurements of the maxillary sinus could be a valuable tool for sex estimation in individuals aged 18 and over. A robust RF model has been developed for sex estimation within the Han population residing in the northwestern region of China. The accuracy of sex estimation could be higher when age is used as a predictive variable.

Prioritizing a high posterior probability threshold leading to low error rate over high classification accuracy: the validity of MorphoPASSE software for cranial morphological sex estimation in a contemporary population.

An increasing number of software tools can be used in forensic anthropology to estimate a biological profile, but further studies in other populations are required for more robust validation. The present study aimed to evaluate the validity of MorphoPASSE software for sex estimation from sexually dimorphic cranial traits recorded on 3D CT models (n = 180) from three populations samples (Czech, French, and Egyptian). Two independent observers performed scoring of 4 cranial traits (2 of them bilateral) in each population sample of 30 males and 30 females. The accuracy of sex estimation using traditional posterior probability threshold (pp = 0.5) ranged from 85.6% to 88.3% and overall classification error from 14.4% to 11.7% for both observers, and corresponds to the previously published values of the method. The MorphoPASSE method is also affected by the subjectivity of the observers, as both observers show agreement in sex assignment in 83.9% of cases, regardless of the accuracy of the estimates. Applying a higher posterior probability threshold (pp 0.95) provided classification accuracy of 97.9% and 93.3% of individuals (for observer A and B respectively), minimizing the risk of error to 2.1% and 6.7%, respectively. However, sex estimation can only be applied to 54% and 66% of individuals, respectively. Our results demonstrate the validity of the MorphoPASSE software for cranial sex estimation outside the reference population. However, the achieved classification success is accompanied by a high risk of errors, the reduction of which is only possible by increasing the posterior probability threshold.

Retrospective evaluation of the morphometric properties of intact maxillary sinus using cone-beam computed tomography for sex estimation in an Indian population.

Sex estimation is crucial to forensic examinations. In order to estimate sex, intact bones are used if the majority of bones are severely deformed and recovered in fragments. This study aims to analyze sexual dimorphism in intact maxillary sinuses using CBCT scanning to evaluate morphometric properties for sex identification. A total of 318 subjects, consisting of 159 males and 159 females, aged between 20 and 60 years without sinus pathology were included in this diagnostic, retrospective cross-sectional study. Bilateral measurements of the volume, height, width, and length of the maxillary sinuses were obtained and compared to evaluate the differences between sexes. Subsequently, a descriptive analysis using mean and standard deviation was performed, followed by a comparison between sexes with a p-value being less than 0.05 and Student's t-test. Finally, a discriminant analysis was performed separately for the right and left maxillary sinuses. Males and females showed statistically significant variations in the length, width, and volume of the maxillary sinuses. Specifically, on the right side, males had longer maxillary sinuses than females (t=5.6203, p<0.0001). Meanwhile, on the left side, females had wider maxillary sinuses than males (t=8.621, plt0.0001). In addition, males had greater volumes of maxillary sinuses on the right (t=6.373, p<0.0001) and left (t=3.091, p<0.0001) sides than females. The results of the discriminant analysis showed that the left width parameter had the highest accuracy of sex estimation (74.21%), followed by the Right Length (70.07%) and left volume (66.66%) parameters. The left height parameter had the lowest accuracy of sex estimation (49.37%). In forensic odontology, the volume of maxillary sinus can serve as a valid radiographic indicator of sex estimation.

Sex estimation using maxillary sinus volume for Chinese subjects based on cone-beam computed tomography.

Sex estimate is a key stage in forensic science for identifying individuals. Some anatomical structures may be useful for sex estimation since they retain their integrity even after highly severe events. However, few studies are focusing on the Chinese population. Some researchers used teeth for sex estimation, but comparison with maxillary sinus were lack. As a result, the objective of this research is to develop a sex estimation formula for the northwestern Chinese population by the volume of the maxillary sinus and compare with the accuracy of sex estimation based on teeth through cone-beam computed tomography (CBCT). CBCT images from 349 samples were used to establish and verify the formula. The volume of both the left and right maxillary sinuses was measured and examined for appropriate formula coefficients. To create the formula, we randomly picked 80% of the data as the training set and 20% of the samples as the testing set. Another set of samples, including 20 males and 20 females, were used to compare the accuracy of maxillary sinuses and teeth. Overall, sex estimation accuracy by volume of the left maxillary sinus can reach 78.57%, while by the volume of the right maxillary sinus can reach 74.29%. The accuracy for females, which can reach 91.43% using the left maxillary sinus, was significantly higher than that for males, which was 65.71%. The result also shows that maxillary sinus volume was higher in males. The comparison with the available results using measurements of teeth for sex estimation performed by our group showed that the accuracy of sex estimation using canines volume was higher than the one using maxillary sinus volume, the accuracies based on mesiodistal diameter of canine and first molar were the same or lower than the volume of maxillary sinus. The study demonstrates that measurement of maxillary sinus volume based on CBCT scans was an available and alternative method for sex estimation. And we established a method to accurately assess the sex of the northwest Chinese population. The comparison with the results of teeth measurements made the conclusion more reliable.

Comparing Walker's (2008) skull trait sex estimation standard to proteomic sex estimation for a group of South Asian individuals

This research assesses the potential for misidentification of sex in individuals of South Asian ancestry using the Walker (2008) morphological skull sex estimation standard [1]. Chromosomal sex was assessed using proteomic analysis targeting sex chromosome-specific amylogenic peptides. Results showed that the Walker method produced incorrect classification for 36.7 % of individuals. Overwhelmingly, those incorrectly assigned were chromosomally male. Misidentification was due to males within the group having lower trait scores (i.e., more gracile traits) than the standard would predict. There was also a high level of overlap in trait scores between male and females indicating reduced expression of sexual dimorphism. The use of established multivariate statistical techniques improved accuracy of sex estimation in some cases, but larger osteological data sets from South Asian individuals are required to develop population-specific standards. We suggest that peptide analysis may provide a useful tool for the forensic anthropologist when assessing sex in populations without population specific osteological standards.

Sex Estimation Using Humerus Volume of CT Images in Korean Population: A Metric Study

This study aimed to explore the use of three-dimensional reconstructed computed tomography images of the adult humerus for forensic anthropological sex estimation in the Korean population. In forensic anthropology, the skull and pelvic bone show high accuracy in sex estimation; however, when they are impaired, other bones should be available for sex estimation. Six hundred images of the right and left humerus pair were used. A logistic regression analysis was performed by measuring the volumes of 500 images and the remaining 100 images were used in the metric sex estimation. Both the logistic regression and metric measurements were performed separately on three regions of the right and left humerus: the head, mid-shaft, and digital regions, The accuracy of sex estimation in the right humerus was 93% (91% for men and 96% for women), 92% (93% for men and 91% for women), and 87% (85% for men and 89% for women) for the head, mid-shaft, and digital regions, respectively. Sex estimation accuracy in the left humerus was 92% (89% for men and 96% for women), 93% (96% for men and 89% for women), and 91% (91% for men and 91% for women) for the head, mid-shaft, and digital regions, respectively. These results contribute to high accuracy and reliability in sex estimation using three-dimensional images of the humerus in Koreans, whereas the two-dimensional metric method provided limited information on bone measurements.

Sex estimation using angular measurements of nasion, sella, and glabella on lateral cephalogram among Indonesian adults in Yogyakarta

BackgroundSex estimation gives the probability that someone is classified as a male or a female. Lateral cephalogram analysis can be used for sex estimation due to the resistance and dimorphism of the skull. Glabella has been known to have dimorphic characteristic in male and female, while nasion and sella have been widely used as a standard point in many craniometric measurements. This study aimed to develop an equation using nasion–sella–glabella (NSG), sella–glabella–nasion (SGN), and glabella–nasion–sella (GNS) angles on lateral cephalograms for sex estimation among Indonesian adults in Yogyakarta, Indonesia.ResultsA total of 138 adults (aged 20–40 years) digital lateral cephalograms were taken from the dental records at Universitas Gadjah Mada Dental Hospital (108 used to form the equation of sex estimation; 30 used to test the equation), and the parameters were measured with EzDent-i Vatech. An independent t-test was used to analyze the differences in the angles between male and female adults. The equation for sex estimation was determined using discriminant function analysis. The average measurements of the NSG angles in male and female adults were 9.64° ± 1.36° and 11.21° ± 1.57°, respectively, the SGN angles were 54.65° ± 4.19° and 60.83° ± 4.13°, respectively, whereas the GNS angles were 118.33° ± 4.61° and 109.84° ± 5.19°, respectively. The independent t-test revealed a significant difference (p < 0.05) between male and female adults. Discriminant function analysis yielded an equation for sex estimation using the NSG, SGN, and GNS angles with an accuracy of up to 75.9%, with the accuracy of sex estimation based on the testing sample being 70%.ConclusionBased on the findings of this study, male Indonesian adults have a smaller NSG and SGN angles but a bigger GNS angle than female adults. Related to the accuracy, the study’s findings indicate that the discriminant function of NSG, SGN, and GNS angles for sex estimation should not be generalized in wider population. More cephalogram parameters must be investigated in future studies on sex estimation.

Size and shape of human mandible: Sex differences and influence of age on sex estimation accuracy

The degree of sexual dimorphism expressed by human bones is of primary importance for the development of accurate methods for sex estimation. The objective of the present study was to investigate sex differences in shape and size of the mandible using geometric morphometric methods. The study also aimed to examine the impact of age on the sex classification ability of the size and shape of the mandible. Computed tomography images of 190 Bulgarians (98 males and 92 females) were used in the study. Polygonal surface models of the skulls were generated and used for digitizing 45 landmarks located on the mandible. The raw three-dimensional coordinates of the landmarks were processed via generalized Procrustes superimposition. The sex differences in mandibular size and shape were evaluated for statistical significance. Multivariate regression was applied for correction of the allometric effect. Principal component analysis, discriminant analysis, and canonical variate analysis were also used in the study. Mandibular size differed significantly between males and females and achieved a sex classification accuracy of 87%. The significance of the sex differences in mandibular shape depended on the type of shape variables used in the analysis. The shape variables provided different classification accuracy: 78% using the Procrustes coordinates and 53% using the regression residuals. The male and female mandibles differed significantly in size and shape, including the allometric component. Mandibular size is a more effective sex indicator than shape. Age has an ambiguous effect on the classification accuracy of the size and shape variables of the mandible.

What we see is what we touch? Sex estimation on the pelvis in virtual anthropology

BackgroundComputed tomography (CT) scans are a convenient means to study 3D reconstructions of bones. However, errors associated with the different nature of the observation, e.g. visual and tactile (on dry bone) versus visual only (on a screen) have not been thoroughly investigated.Materials and methodsWe quantified the errors between modalities for sex estimation protocols of nonmetric (categorical and ordinal) and metric data, using 200 dry pelves of archaeological origin and the CT reconstructions of the same bones. In addition, we 3D surface scanned a subsample of 39 pelves to compare observations with dry bone and CT data. We did not focus on the sex estimation accuracy but solely on the consistency of the scoring, hence, the interchangeability of the modalities.ResultsMetric data yielded the most consistent results. Among the nonmetric protocols, ordinal data performed better than categorical data. We applied a slightly modified description for the trait with the highest errors and grouped the traits according to consistency and availability in good, intermediate, and poor.DiscussionThe investigated modalities were interchangeable as long as the trait definition was not arbitrary. Dry bone (gold standard) performed well, and CT and 3D surface scans performed better. We recommend researchers test their affinity for using virtual modalities. Future studies could use our consistency analysis and combine the best traits, validating their accuracy on various modalities.

Sex Estimation From the Paranasal Sinus Volumes Using Semiautomatic Segmentation, Discriminant Analyses, and Machine Learning Algorithms.

The aims of this study were to determine whether paranasal sinus volumetric measurements differ according to sex, age group, and right-left side and to determine the rate of sexual dimorphism using discriminant function analysis and machine learning algorithms. The study included paranasal computed tomography images of 100 live individuals of known sex and age. The paranasal sinuses were marked using semiautomatic segmentation and their volumes and densities were measured. Sex determination using discriminant analyses and machine learning algorithms was performed. Males had higher mean volumes of all paranasal sinuses than females ( P < 0.05); however, there were no statistically significant differences between age groups or sides ( P > 0.05). The paranasal sinus volumes of females were more dysmorphic during sex determination. The frontal sinus volume had the highest accuracy, whereas the sphenoid sinus volume was the least dysmorphic. In this study, although there was moderate sexual dimorphism in paranasal sinus volumes, the use of machine learning methods increased the accuracy of sex estimation. We believe that sex estimation rates will be significantly higher in future studies that combine linear measurements, volumetric measurements, and machine-learning algorithms.

Automatic sex estimation using deep convolutional neural network based on orthopantomogram images

Sex estimation is very important in forensic applications as part of individual identification. Morphological sex estimation methods predominantly focus on anatomical measurements. Based on the close relationship between sex chromosome genes and facial characterization, craniofacial hard tissues morphology shows sex dimorphism. In order to establish a more labor-saving, rapid, and accurate reference for sex estimation, the study investigated a deep learning network-based artificial intelligence (AI) model using orthopantomograms (OPG) to estimate sex in northern Chinese subjects. In total, 10703 OPG images were divided into training (80%), validation (10%), and test sets (10%). At the same time, different age thresholds were selected to compare the accuracy differences between adults and minors. The accuracy of sex estimation using CNN (convolutional neural network) model was higher for adults (90.97%) compared with minors (82.64%). This work demonstrated that the proposed model trained with a large dataset could be used in automatic morphological sex-related identification with favorable performance and practical significance in forensic science for adults in northern China, while also providing a reference for minors to some extent.

The influence of age on greater sciatic notch morphology: testing the Walker method in an Australian population.

Sex estimation is an integral aspect of a forensic biological profile. The pelvis, being the most dimorphic part of the skeleton, has been studied in considerable detail relative to morphological and metric variation. However, empirical data on the effect of age on pelvic morphology relative to sex-specific morphological variation is limited, especially in regard to the estimation of skeletal sex. This study assesses whether there are age-related differences in the distribution of the Walker (2005) morphological scores for the greater sciatic notch (GSN) in an Australian population. Three-dimensional volumetric reconstructions derived from multi-detector computed tomography (MDCT) scans of 567 pelves of 258 females and 309 males aged 18 to 96years were scored following Walker (2005). Differences in score distributions and means by sex and age group were tested using Pearson's chi-squared test and ANOVA, respectively. The accuracy of sex estimates derived from logistic regression equations was explored using leave-one-out cross-validation. Significant differences were found in score distribution and means among age groups in females, but not in males. There was a tendency toward higher scores in older females. The overall sex estimation accuracy was 87.5%. When comparing age groups 18-49 and 70 + years, estimation accuracy decreased in females (99% vs. 91%), while the opposite was found for males (79% vs. 87%). These findings suggest that age affects GSN morphology. Higher mean scores in older females imply that, on average, the GSN becomes narrower with increasing age. It is thus recommended due consideration of estimated age when assessing sex based on the GSN in unidentified human remains.

Accuracy of sex estimation by morphometric evaluation of foramen magnum using computed tomography - a systematic review and meta-analysis.

The objective of this study is to determine whether the morphometric evaluation of the foramen magnum using computed tomography can be used as an accurate tool in estimating the sex of an individual. An extensive search of the databases, PubMed, ProQuest, Google Scholar, and Scopus, was carried out to procure articles that fulfilled the inclusion criteria. The AQUA tool was used to assess the quality of the included studies. A random effects model was used for the meta-analysis of the eligible studies using the STATA software, version 16, 2019 at 95% CI and p ≤ 0.05. Eleven eligible articles that measured the transverse and sagittal diameters of the foramen magnum using computed tomography were included in this study. The sagittal diameter of the foramen magnum was greater than the transverse diameter, and both the diameters were greater in males than in females. Meta-analysis revealed that both transverse and sagittal diameters were more reliable for male sex estimation. Since there is a dimensional variation between the male and female foramen magnum, it can be used for initial sex identification and also as an auxiliary to other advanced methods of sex estimation.

Sex Estimation of Han Adults in Western China Based on Three-Dimensional Cranial CT Reconstruction.

To examine the reliability and accuracy of Walker's model for estimating the sex of Han adults in western China by using cranium three-dimensional (3D) CT reconstruction, and to study the suitable cranial sex estimation model for Han people in western China. A total of 576 cranial CT 3D reconstructed images from Hanzhong Hospital in Shaanxi Province from 2017 to 2021 were collected. These images were divided into the experimental group with 486 samples and the validation group with 90 samples. Walker's model was used by observer 1 to estimate the sex of experimental group samples. The logistic function applicable to Han people in western China was corrected by observer 1. The 90 samples in the validation group were scored and substituted into the modified logistic function to complete the back substitution test by observer 1, 2 and 3. The accuracy of sex estimation of Han adults in western China was 63.2%-77.2% by applying Walker's model. The accuracy of modified logistic function was 82.9%. The accuracy of sex estimation through back substitution test by 3 observers was 75.6%-91.1%, with a Kappa value of 0.689 (P<0.05) for inter-observer consistency and 0.874 (P<0.05) for intra-observer consistency. There are great differences in bone characteristics among people from different regions. The modified logistic function can achieve higher accuracy in Han adults in western China.