This study aimed to investigate the age determination in forensic expert opinions at the Institute of Forensic Medicine (Mainz) over the last ten years and to determine the reliability rate of wisdom teeth in comparison to the clavicle. A total of 112 expert opinions were prepared between 2011 and 2021, following the guidelines established by the Working Group for Forensic Age Diagnostics (AGFAD). Five indicators were studied: clavicle development coded according to Wittschieber et al. using computed tomography and wisdom tooth development 18, 28, 38 and 48 coded according to Demirjian’s staging method in a dental panoramic radiograph. Following an ordinary least square regression analysis performed separately for each of the five indicators, it was possible to investigate whether the addition of more than one of the indicators would lead to a more predictive value for the age determination. The combination of the clavicle and tooth 48 showed the best value. Adding tooth 38, which showed the second-best prediction in the bivariate analyses, led to an increase of the explained variance of 11% to a total of 58% explained variance (p < 0.001). The addition of further wisdom teeth did not show any relevant effect. For the clinical performance of dental age diagnostics, the teeth of the mandible, in combination with the clavicle, should be primarily used.
Forensic odontology plays a crucial role in human identification, particularly in cases where traditional identification methods face challenges such as severe trauma, decomposition, skeletonization, or carbonization. The evolution of digital dentistry has significantly advanced dental autopsies, particularly through the use of intraoral scanners (IOSs). These devices provide a non-invasive and efficient method for capturing detailed impressions of dentition and photographic images of teeth. The benefits of intraoral scanning in analyzing human remains in forensic odontology are endless. Digital impressions can be easily stored, shared, and transmitted electronically, eliminating the need for physical storage or transportation of dental models. This technology also enables remote postmortem dental profiling. By combining digital models with antemortem dental records, forensic odontologists can more efficiently identify matches and discrepancies, with the added benefit of future advancements in artificial intelligence(AI). Intraoral scanning should be considered a routine process in all dental autopsies to improve postmortem dental data collection and archive. Forensic odontologists should be equipped with a portable X-ray device, a digital sensor, and an IOS.
Age estimation (AE) is a fundamental aspect used to establish the biological profile of both living and deceased individuals. This study evaluates AE methods to determine if bone development (BD) methods yield similar results to dental development (DD) and whether methods using samples with similar geographic origins, socioeconomic status (SES), chronology, data specificity, and/or anatomical regions yield consistent results. We hypothesized that BD and DD methods differ in age estimations, although these differences would be minor when methods have similar variables. The sample consisted of 11 immature skeletons from the Hospital Real de Todos os Santos’ collection (18th-century, Lisbon, Portugal) and applied 56 AE methods. The results were compiled into individual-based diagrams, facilitating both within- and between-individual comparisons, including stress-induced changes. This showed that BD methods tended to underestimate age compared to DD methods. BD methods closely aligning with DD methods were mainly based on individuals from lower to middle SES, focusing on areas like the iliac crest and medial clavicle. Findings also suggest that physiological stress might influence AE outcomes. This study emphasizes the importance of combining BD and DD methods alongside a detailed pathological and/or chronic stress assessment of human remains when estimating AE to minimize interpretative errors. This care applies to any discipline aiming to profile living or dead individuals, highlighting the importance of controlling for confounding variables, such as disease, in any AE estimation.
