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In an effort to standardize data collection and analysis in age estimation, a series of computational methods utilizing high-dimensional image data of the age indicator have recently been proposed as an alternative to subjective visual, trait-to-phase matching techniques. To systematically quantify the reproducibility of such methods, we investigate the intrascan variability and within- and between-observer reliability in initial scan data capturing and editing using 3D laser scans of the Suchey-Brooks pubic symphysis casts and five shape-based computational methods. Our results show that (i) five observers with various training background and experience levels edited the scans consistently for all three trials and the derived shape measures and age estimates were in excellent agreement among observers, and (ii) the computational methods are robust to a measured degree of scan trimming error. This study supports the application of computational methods to 3D laser scanned images for reliable age-at-death estimation, with reduced subjectivity., (© 2018 American Academy of Forensic Sciences.)

The pubic symphysis is among the most commonly used bilateral age indicators. Because of potential differences between right and left sides, it is necessary to investigate within-individual asymmetry, which can inflate age estimation error. This study uses 3D laser scans of paired pubic symphyses for 88 documented White males. Scan data are analyzed by numerical shape algorithms, proposed as an alternative to traditional visual assessment techniques. Results are used to quantify the within-individual asymmetry, evaluating if one side produces a better age-estimate. Relationships between the asymmetry and advanced age, weight, and stature are examined. This analysis indicates that the computational, shape-based techniques are robust to asymmetry (>80% of paired differences are within 10 years and >90% are within 15 years). For notably more asymmetric cases, differences in estimates are not associated with life history factors. Based on this study, either side can be used for age-at-death estimation by the computational methods., (© 2018 American Academy of Forensic Sciences.)

In forensic anthropology, age-at-death estimation typically requires the macroscopic assessment of the skeletal indicator and its association with a phase or score. High subjectivity and error are the recognized disadvantages of this approach, creating a need for alternative tools that enable the objective and mathematically robust assessment of true chronological age. We describe, here, three fully computational, quantitative shape analysis methods and a combinatory approach that make use of three-dimensional laser scans of the pubic symphysis. We report a novel age-related shape measure, focusing on the changes observed in the ventral margin curvature, and refine two former methods, whose measures capture the flatness of the symphyseal surface. We show how we can decrease age-estimation error and improve prior results by combining these outline and surface measures in two multivariate regression models. The presented models produce objective age-estimates that are comparable to current practices with root-mean-square-errors between 13.7 and 16.5 years., (© 2017 American Academy of Forensic Sciences.)

Objectives: The pubic symphysis is frequently used to estimate age-at-death from the adult skeleton. Assessment methods require the visual comparison of the bone morphology against age-informative characteristics that represent a series of phases. Age-at-death is then estimated from the age-range previously associated with the chosen phase. While easily executed, the "morphoscopic" process of feature-scoring and bone-to-phase-matching is known to be subjective. Studies of method and practitioner error demonstrate a need for alternative tools to quantify age-progressive change in the pubic symphysis. This article proposes a more objective, quantitative method that analyzes three-dimensional (3D) surface scans of the pubic symphysis using a thin plate spline algorithm (TPS)., Materials and Methods: This algorithm models the bending of a flat plane to approximately match the surface of the bone and minimizes the bending energy required for this transformation. Known age-at-death and bending energy were used to construct a linear model to predict age from observed bending energy. This approach is tested with scans from 44 documented white male skeletons and 12 casts., Results: The results of the surface analysis show a significant association (regression p-value = 0.0002 and coefficient of determination = 0.2270) between the minimum bending energy and age-at-death, with a root mean square error of ≈19 years., Discussion: This TPS method yields estimates comparable to established methods but offers a fully integrated, objective and quantitative framework of analysis and has potential for use in archaeological and forensic casework., (© 2015 Wiley Periodicals, Inc.)

The pubic symphysis is widely used in age estimation for the adult skeleton. Standard practice requires the visual comparison of surface morphology against criteria representing predefined phases and the estimation of case-specific age from an age range associated with the chosen phase. Known problems of method and observer error necessitate alternative tools to quantify age-related change in pubic morphology. This paper presents an objective, fully quantitative method for estimating age-at-death from the skeleton, which exploits a variance-based score of surface complexity computed from vertices obtained from a scanner sampling the pubic symphysis. For laser scans from 41 modern American male skeletons, this method produces results that are significantly associated with known age-at-death (RMSE = 17.15 years). Chronological age is predicted, therefore, equally well, if not, better, with this robust, objective, and fully quantitative method than with prevailing phase-aging systems. This method contributes to forensic casework by responding to medico-legal expectations for evidence standards., (© 2015 American Academy of Forensic Sciences.)