Automated reconstruction: Predictive models based on facial morphology matrices.

Forensic Facial Approximation (FFA) has evolved, with techniques advancing to refine the intercorrelation between the soft-tissue facial profile and the underlying skull. FFA has become essential for identifying unknown persons in South Africa, where the high number of migrant and illegal labourers and many unidentified remains make the identification process challenging. However, existing FFA methods are based on American or European standards, rendering them inapplicable in a South African context. We addressed this issue by conducting a study to create prediction models based on the relationships between facial morphology and known factors, such as population affinity, sex, and age, in white South African and French samples. We retrospectively collected 184 adult cone beam computed tomography (CBCT) scans representing 76 white South Africans (29 males and 47 females) and 108 French nationals (54 males and 54 females) to develop predictive statistical models using a projection onto latent structures regression algorithm (PLSR). On training and untrained datasets, the accuracy of the estimated soft-tissue shape of the ears, eyes, nose, and mouth was measured using metric deviations. The predictive models were optimized by integrating additional variables such as sex and age. Based on trained data, the prediction errors for the ears, eyes, nose, and mouth ranged between 1.6 mm and 4.1 mm for white South Africans; for the French group, they ranged between 1.9 mm and 4.2 mm. Prediction errors on non-trained data ranged between 1.6 mm and 4.3 mm for white South Africans, whereas prediction errors ranging between 1.8 mm and 4.3 mm were observed for the French. Ultimately, our study provided promising predictive models. Although the statistical models can be improved, the inherent variability among individuals restricts the accuracy of FFA. The predictive validity of the models was improved by including sex and age variables and considering population affinity. By integrating these factors, more customized and accurate predictive models can be developed, ultimately strengthening the effectiveness of forensic analysis in the South African region.

A New Methodology to Determine the Orifice for Root Canal Configurations in First Permanent Molar Root and Canal Morphologies Using Micro-Computed Tomography.

BACKGROUND: The distinction between where the pulp chamber ends and the root canal system begins is poorly defined within the existing literature. METHODS: This paper aimed to describe a range of accurate methods to define the transition from pulp chamber to root canal in different first molar root morphologies using micro-focus computed tomography (micro-CT). METHODS: The sample consisted of 86 mandibular and 101 maxillary first molars from the skeletal collections housed in the Department of Anatomy and Histology of the Sefako Makgatho Health Sciences University and the Pretoria Bone Collection. A stepwise approach using the cemento-enamel junction (CEJ) and dedicated landmarks was followed to create an automated cross-sectional slice. RESULTS: Transition from pulp chamber to root canal could be accurately determined on maxillary and mandibular teeth. The occurrence of two separate roots in mandibular molars was 97.7%, with the remaining 2.3% having an additional disto-lingual root, with no mandibular molars displaying fused roots. In the maxillary molars, 92.1% had three separate roots and 7.9% displayed root fusion. Within this group, one tooth displayed a C-shaped root canal configuration and one a mesotaurodont-type morphology. CONCLUSION: The suggested methodology to determine orifice location was found to be appropriate in all morphological types.

A histomorphological analysis of human and non-human femora.

Histology is used to describe post-mortem bone alterations, trauma, pathology and age estimation and to separate human and non-human bones. Many scholars are however not familiar with the intricate and variable microstructure of bone, and due to the complex nature of some classification systems, bone histomorphology is often incorrectly described or identified. Little information is available on the histomorphology of non-human bones found in southern Africa, and therefore, the aim of this study was to describe the histomorphology of non-human species commonly found in southern Africa, namely, impala and monkeys, along with cat, dog, cow, sheep, equid and pig. Human femora were included for comparative purposes. The periosteal surface of femora was described and focussed only on the arrangements of vascular canals, primary osteons and secondary osteons. The results compared favourably to other studies and also added a histomorphological description of impala femora which consisted of primary vascular longitudinal bone tissue. A large degree of overlap and combinations of bone tissue types was observed, as well as evidence which allows animals from similar taxonomic orders to be grouped together. Primary vascular bone was primarily observed in artiodactyls (cow, pig, sheep and impala), while Haversian bone was recognised in carnivores (cat and dog), Perissodactyla (horses and donkeys) and primates. These differences can be used to exclude human from unknown bone fragments and also serve to caution investigators when using animal models to infer human bone tissue responses to thermal damage, ballistic trauma, etc., as bone tissue types different to that of human bone may respond differently.