CT-based evaluation of the acetabulum for age estimation in an Indian population

Age estimation constitutes an important aspect of forensic research, investigation and human identification. For the purpose of age estimation, various markers within the skeletal framework are employed. Degenerative morphological changes in the skeleton can be used for age estimation in adults. Amongst the various bones, age-progressive changes in the innominate bone are of particular significance in age estimation. Within the pelvis, the acetabulum presents as a durable and well-preserved evidence, characteristic manifestations of which can be employed for age estimation. The present study aimed at a CT-based evaluation of acetabular changes for the purpose of age estimation in an Indian population. CT images of 250 individuals aged 10-88 years were scrutinized according to the features defined in the Calce method of acetabular age estimation. Scores were allotted to the various features and a cumulative score was calculated. No significant bilateral and sex differences were observed. Significant correlation was obtained between the scores for these defined characteristics and the chronological age of individuals. Population-specific regression models were generated for age estimation. The scoring method devised in the present research requires further validation as it represents a new tool for age estimation in medico-legal cases

Applicability of the six-phase method for auricular age estimation in an Indian population: A CT-based study

Age estimation plays a crucial role in human identification. Amongst numerous age markers located throughout the skeletal framework, the auricular surface of the ilium presents as a resilient structure, with different methods for auricular age estimation currently in practice. Amongst these methods, the Osborne method is believed to permit accurate age estimation through its use of robust age categories and discrete phase descriptors. The present study aimed to assess the applicability of the Osborne method in an Indian population through a computed tomographic (CT) examination of the auricular surface, an aspect presently unreported. In order to do so, CT scans of 380 individuals were collected and evaluated using the Osborne method. A CT-based examination indicated that surface texture described by Osborne is difficult to appreciate through 3D CT images. Indistinct definitions associated with certain features, and the mosaic display of features within each phase further prevents applying the method effectively. Overall accuracy percentages of 99.47% and 98.90% were obtained using the method in males and females, respectively, with corresponding inaccuracy values of 10.10 years and 9.04 years. Significantly reduced accuracy percentages were obtained with alternate, more robust age brackets presented within the original study, demonstrating the limited reliability associated with the method. Inaccuracy and bias values computed for each decade indicate the relative utility of the method in aging 40-59-year-old individuals. Low accuracy percentages, high error rates and different methodological hindrances encountered within the present study illustrate the limited applicability of the Osborne method in aging an Indian population

Applicability of the Suchey-Brooks method for age estimation in an Indian population: A computed tomography-based exploration using Bayesian analysis and machine learning

Age estimation occupies a prominent niche in the identification process. In cases where skeletal remains present for examination, age is often estimated from markers distributed throughout the skeletal framework. Within the pelvis, the pubic symphysis constitutes one of the more commonly utilized skeletal markers for age estimation, with the Suchey-Brooks method comprising one of the more commonly employed methods for pubic symphyseal age estimation. The present study was targeted towards assessing the applicability of the Suchey-Brooks method for pubic symphyseal age estimation, an aspect largely unreported for an Indian population. In order to do so, clinically undertaken pelvic computed tomography scans of individuals were evaluated using the Suchey-Brooks method, and the error associated with the method was established using Bayesian analysis and different machine learning regression models. Amongst different supervised machine learning models, support vector regression and random forest furnished lowest error computations in both sexes. Using both Bayesian analysis and machine learning, lower error computations were observed in females, suggesting that the method demonstrates greater applicability for this sex. Inaccuracy and root mean square error obtained with Bayesian analysis and machine learning illustrates that both statistical modalities furnish comparable error computations for pubic symphyseal age estimation using the Suchey-Brooks method. However, given the numerous advantages associated with machine learning, it is recommended to use the same within medicolegal settings. Error computations obtained with the Suchey-Brooks method, regardless of the statistical modality utilized, indicate that the method should be used in amalgamation with additional markers to garner accurate estimates of age