Sex estimation based on mandibular measurements.

Medical imaging and machine learning are beneficial approaches in physical and forensic anthropology. They are particularly useful for the development of models for sex identification based on bone remains. The present study uses machine learning algorithms to create models for sex estimation based on mandibular measurements. The sample included head CT scans of 239 adult Bulgarians (116 males and 123 females). Three-dimensional coordinates of 45 landmarks of the mandible were acquired from segmented polygonal models of the skulls of these individuals. Two datasets of mandibular measurements were assembled. The first dataset included 51 measurements: linear, projective, and angular measurements. The second dataset included 990 interlandmark distances. Seven machine learning algorithms (Support Vector Machines, Neural Network, Naïve Bayes, Random Forest, J48, JRip, and Logistic Regression) were applied to the two datasets, and the classification accuracy was evaluated by 10x5-cross-validation. The selection of the best subsets of attributes specific to each of the abovementioned algorithms was done based on the attribute importance evaluated by an attribute selection scheme. In general, the sub-symbolic algorithms achieved higher results than the symbolic ones, except for the logistic regression. The best classification model was learnt by the Support Vector Machines algorithm, which achieved an accuracy of 95.3% on a dataset described by 19 interlandmark distances. In both datasets, the application of advanced attribute selection has led to an increase in the classification accuracy of all algorithms used in the experiments.

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.

Osseous Bridges of the Sphenoid Bone: Frequency, Bilateral and Sex Distribution.

Sellar (caroticoclinoid and interclinoid), pterygospinous and pterygoalar bridges are osseous bars of the sphenoid bone, which enclose additional foramina in the skull base and could cause entrapment of nerves, occlusion of vessels and obstruction of surgical corridors. This study aimed to investigate the frequency of sphenoid bone bridges in Bulgarians and to assess the bilateral and sex differences in their distribution. This study was performed on head CT scans of 315 Bulgarians, 148 males and 167 females. The sellar bridges were the most common type of sphenoid bridging; particularly the caroticoclinoid bridge. The pterygospinous bridge was a relatively common finding and the pterygoalar bridge was the most infrequent type of bridging. The total frequency of sellar bridges did not differ significantly between both sides and sexes. The pterygospinous bridge did not indicate significant bilateral differences but showed considerable sex differences concerning the left-side occurrence, which was significantly higher in the male series. There were no considerable bilateral and sex differences in the distribution of the pterygoalar bridging. There were no significant correlations between the different types of sphenoid bone bridges, but each type of bridging showed significant positive correlations between the right and left side co-occurrence in males and females.

Second trimester fetal MRI of the brain: Through the ground glass.

Fetal MRI is an important tool for the prenatal diagnosis of brain malformations and is often requested after second-trimester ultrasonography reveals a possible abnormality. Despite the immature state of the fetal brain at this early stage, early suggestive signs of the presence of brain malformations can be recognized. To differentiate between the normal dynamics of the growing brain and the developing pathological conditions can be challenging and requires extensive knowledge of normal central nervous system developmental stages and their neuroradiological counterparts at those different stages. This article reviews the second-trimester appearances of some commonly encountered brain malformations, focusing on helpful tricks and subtle signs to aid in the diagnosis of such conditions as rhombencephalosynapsis, various causes of vermian rotation, molar tooth spectrum anomalies, diencephalic-mesencephalic junction dysplasia, ganglionic eminence anomalies, and the most common malformations of cortical development.