A Computational Framework for Age-at-Death Estimation from the Skeleton: Surface and Outline Analysis of 3D Laser Scans of the Adult Pubic Symphysis

Evaluation of the forAge Age-at-Death Estimation Program Using Pubic Symphyseal Surface in a Korean Population

The forAge program estimates the age-at-death of human pubic symphysis using 3-dimensional scans. It was developed by Dennis E. Slice and Bridget F. B. Algee-Hewitt, and utilizes three distinct scores: the Slice and Algee-Hewitt (SAH) score, bending energy (BE), and ventral curvature (VC). However, these scores and age estimation regression equation were obtained through European American pubic symphysis. Changes in the pubic symphysis surface are evaluated as one of the most reliable indicators for estimating age, but in connection with this, using Korean materials, changes in the pubic symphysis surface and the actual changes are evaluated. There is no bar where the relationship between ages is grasped, and there are cases where a methodology developed for a specific group is applied to a Korean group. Changing the pubic symphysis surface by aging was evaluated as one of the most reliable indicators for estimating age. However, there is no study conducted on the relationship between changes in the pubic symphysis and actual age and applied the age estimation method for a specific population among Korean population. The purpose of this study is to compare the difference between the actual age and the estimated age in Korean to see if the forAge program is applicable to other population of different ancestral origin. One hundred and four modern Korean pubic symphyseal surfaces (47 to 96 years old) were used in this study. Through the pubic symphyseal surface 3-dimensional images, age-at-death was estimated via prediction equation and new regression lines using SAH, VC, and BE scores. Firstly, the estimated age via prediction equation using the first version of SAH score was lower than the actual age according to all pubic symphyseal surfaces for those older than 56. With aging, the difference between the actual age and estimated age became markedly larger. Secondly, the estimated ages via the new regression lines using VC, the second version of SAH score, and BE were shown a similar pattern to the previous prediction equation. The current study explored the applicability of a quantitative method using pubic symphyseal surface for age estimation in a modern Korean population. This study showed the forAge program cannot be applied to a modern Korean population, as they present relatively low correlations with the actual age-at-death.

Automated age-at-death estimation from 3D surface scans of the facies auricularis of the pelvic bone

This work presents an automated data-mining model for age-at-death estimation based on 3D scans of the auricular surface of the pelvic bone. The study is based on a multi-population sample of 688 individuals (males and females) originating from one Asian and five European identified osteological collections. Our method requires no expert knowledge and achieves similar accuracy compared to traditional subjective methods. Apart from data acquisition, the whole procedure of pre-processing, feature extraction and age estimation is fully automated and implemented as a computer program. This program is a part of a freely available web-based software tool called CoxAGE3D. This software tool is available at https://coxage3d.fit.cvut.cz/ Our age-at-death estimation method is suitable for use on individuals with known/unknown population affinity and provides moderate correlation between the estimated age and actual age (Pearson's correlation coefficient is 0.56), and a mean absolute error of 12.4 years.

The first rib as a method of adult age-at-death estimation in a modern South African sample

An age-at-death estimation method using the first rib may be particularly advantageous as this rib is relatively easy to identify, not easily damaged postmortem, and associated with less mechanical stresses compared to other age indicators. Previously, mixed results have been achieved using the first rib to estimate age-at-death. This study aimed to develop and test an age-at-death estimation method using the first rib. An identified modern black South African sample of 260 skeletons were used to collect age-related data from the first rib. Multiple linear regression analysis equations were created from this data for male, female, and combined samples. When tested on a hold-out sample, equations generated mean inaccuracies of 7-13 years for point estimates. The 95% confidence intervals contained the true age in 11-33% of individuals depending on the equation used, but wider intervals generated using 95% prediction intervals contained true ages for 100% of individuals. Point estimate inaccuracies are comparable to other age-at-death estimation methods and may be useful if single indicator estimation is unavoidable in the case of missing or damaged bones. However, combined methods that use indicators from many areas of the skeleton are preferable and may reduce interval widths.

Paleodemography: From archaeology and skeletal age estimation to life in the past

Much of paleodemography, an interdisciplinary field with strong ties to archaeology, among other disciplines, is oriented toward clarifying the life experiences of past people and why they changed over time. We focus on how human skeletons contribute to our understanding of preindustrial demographic regimes, including when changes took place that led to the world as we know it today. Problems with existing paleodemographic practices are highlighted, as are promising directions for future work. The latter requires both better age estimates and innovative methods to handle data appropriately. Age-at-death estimates for adult skeletons are a particular problem, especially for adults over 50 years that undoubtedly are mistakenly underrepresented in published studies of archaeological skeletons. Better age estimates for the entirety of the lifespan are essential to generate realistic distributions of age at death. There are currently encouraging signs that after about a half-century of intensive, and sometimes contentious, research, paleodemography is poised to contribute much to understandings of evolutionary processes, the structure of past populations, and human-disease interaction, among other topics.

The computational age-at-death estimation from 3D surface models of the adult pubic symphysis using data mining methods

Age-at-death estimation of adult skeletal remains is a key part of biological profile estimation, yet it remains problematic for several reasons. One of them may be the subjective nature of the evaluation of age-related changes, or the fact that the human eye is unable to detect all the relevant surface changes. We have several aims: (1) to validate already existing computer models for age estimation; (2) to propose our own expert system based on computational approaches to eliminate the factor of subjectivity and to use the full potential of surface changes on an articulation area; and (3) to determine what age range the pubic symphysis is useful for age estimation. A sample of 483 3D representations of the pubic symphyseal surfaces from the ossa coxae of adult individuals coming from four European (two from Portugal, one from Switzerland and Greece) and one Asian (Thailand) identified skeletal collections was used. A validation of published algorithms showed very high error in our dataset-the Mean Absolute Error (MAE) ranged from 16.2 and 25.1 years. Two completely new approaches were proposed in this paper: SASS (Simple Automated Symphyseal Surface-based) and AANNESS (Advanced Automated Neural Network-grounded Extended Symphyseal Surface-based), whose MAE values are 11.7 and 10.6 years, respectively. Lastly, it was demonstrated that our models could estimate the age-at-death using the pubic symphysis over the entire adult age range. The proposed models offer objective age estimates with low estimation error (compared to traditional visual methods) and are able to estimate age using the pubic symphysis across the entire adult age range.

Forensic anthropology casework performance: Assessing accuracy and trends for biological profile estimates on a comprehensive sample of identified decedent cases

The purpose of this study was to investigate the accuracy rates and trends in forensic anthropology casework concerning the estimation of the biological profile (sex, age, ancestry, and stature). Identified cases from the Forensic Anthropology Database for Assessing Methods Accuracy (FADAMA; n = 359) were analyzed to explore the following: accuracy rates per biological profile component, case-level performance in assessing the biological profile, and factors related to inaccuracy rates. Accuracy rates for the four biological profile components ranged from 83% to 98%, with sex estimation performing the best and stature performing the poorest. While the overall sex estimation inaccuracies were the lowest of any biological profile component, we found that females are missexed approximately ten times more often than males. Inaccurate age estimates were more frequently the result of overestimation than underestimation, while the trends are reversed for stature estimation. Regarding ancestry estimation performance, African American/Black and White decedents had the lowest inaccuracy rates, while Hispanic and Asian/Pacific Islander decedents demonstrated greater inaccuracy rates. When examining accuracy rates for each case, 81% of cases had no inaccurate biological profile estimates, while 17% and 2% inaccurately estimated one and two biological profile components, respectively. The demographic trends of identified forensic anthropology cases reflect the national unidentified decedent demographics. Biological profile accuracy rates were generally comparable to previous studies. The findings highlight the current status of forensic anthropologists' casework performance, with a greater amount of case-level inaccuracy rates than previously thought, and demonstrate the potential methodological and sampling strategies that could improve accuracy rates.

Correlation of the human pubic symphysis surface with age-at-death: a novel quantitative method based on a bandpass filter

Age-at-death estimation from skeletal remains typically utilizes the roughness of pubic symphysis articular surfaces. This study presents a new quantitative method adapting a tool from geometric morphometrics, bandpass filtering of partial warp bending energy to extract only age-related changes of the surfaces. The study sample consisted of 440 surface-scanned symphyseal pubic bones from men between 14 and 82 years of age, which were landmarked with 102 fixed and surface semilandmarks. From the original sample, 371 specimens within Procrustes distance of 0.05 of the side-specific average were selected. For this subsample, age was correlated with total bending energy (calculated as summed squared partial warps amplitudes) for a wide range of plausible bandpass filters. For our subsample's 188 right-side surfaces, the correlation between age and bandpass filtered versions of bending energy peaks relatively sharply at r = -0.648 for ages up through 49 years against the first seven partial warp amplitudes only. The finding for left symphyses is similar. The results demonstrate that below the age 50, the symphyseal surface form changes most systematically related to age may be best detected by a lowpass-filtered version of bending energy: signals at the largest geometric scales of roughness rather than its full spectrum. Combining this method with information from other skeletal features could further improve age-at-death estimation based on the symphyseal pubic surface.

Technical note: preliminary insight into a new method for age-at-death estimation from the pubic symphysis

Age-at-death estimation methods are important in forensic anthropology. However, age assessment is problematic due to inter-individual variation. The subjectivity of visual scoring systems can affect the accuracy and reliability of methods as well. One of the most studied skeletal regions for age assessment is the pubic symphysis. Few studies on Spanish pubic symphysis collections have been conducted, making further research necessary as well as the sampling of more forensic skeletal collections. This study is a preliminary development of an age-at-death estimation method from the pubic symphysis based on a new simple scoring system. A documented late twentieth century skeletal collection (N = 29) and a twenty-first century forensic collection (N = 76) are used. Sixteen traits are evaluated, and a new trait (microgrooves) is described and evaluated for the first time in this study. All traits are scored in a binary manner (present or absent), thus reducing ambiguity and subjectivity. Several data sets are constructed based on different age intervals. Machine learning methods are employed to evaluate the scoring system's performance. The results show that microgrooves, macroporosity, beveling, lower extremity, ventral and dorsal margin decomposition, and lipping are the best preforming traits. The new microgroove trait proves to be a good age predictor. Reliable classification results are obtained for three age intervals (≤ 29, 30-69, ≥ 70). Older individuals are reliably classified with two age intervals (< 80, ≥ 80). The combination of binary attributes and machine learning algorithms is a promising tool for gaining objectivity in age-at-death assessment.

Estimation of adult age-at-death from entheseal robusticity: A test using an identified Italian skeletal collection

OBJECTIVES

The present study tests the effectiveness of entheseal robusticity (ER) as a potential predictor of adult age-at-death by applying multiple regression models to a large contemporary identified skeletal sample.

MATERIALS AND METHODS

ER was recorded for 23 bilateral postcranial entheses on 481 adult individuals (271 females and 210 males) from the Frassetto identified skeletal collection of Sassari (Italy), following the method of Mariotti et al. 2007. ER scores were used as predictors in multiple regression analyses with age as the dependent variable; the performance of the resulting models was tested through standard error of estimate, the correlation coefficient between predicted and documented age, and the percentage of correctly classified individuals.

RESULTS

ER show a higher correlation with age in females, resulting in more accurate estimates when compared with those obtained for males. Age-at-death is overestimated for male individuals under 45 years old and underestimated for older individuals. Regression models including a reduced set of ER sites result in better estimates compared with those using the complete set of variables.

DISCUSSION

Results suggest the potential usefulness of ER for the estimation of age, especially for female skeletal remains. If used with caution, ER may be a valid complement to existing methods for the reconstruction of the biological profile of skeletal remains of archaeological and forensic interest.

Evaluation of the Enhanced Computational Methods of Estimating Age-at-Death Using the Pubic Symphyses of a White South African Population

To address problems of reproducibility related to current age estimation methods, the enhanced computational Methods (ECM) were previously developed using a sample of white North American male pubic symphyses and showed promise in improving current techniques. However, given the evidence of sex and population differences in the onset of age markers, this study set out to test the ECM on a white South African sample. The sample consisted of 184 well-preserved os coxae from individuals of known age and sex. Pubic symphyseal surfaces were scanned using the Artec Spider 3D scanner, processed using Artec Studio 10 and analyzed using forAge. Point estimates of age were then compared to the true age of each individual. Results indicate that the ECM performed poorly in a white South African population, with consistent underestimation of age-at-death and weak positive correlations with true age. Despite the low correlations, the ECM did, however, reduce observer error.

Impact of 3D surface scanning protocols on the Os coxae digital data: Implications for sex and age-at-death assessment

The 3D imaging technologies have become of paramount importance for example in disciplines such as forensic anthropology and bioarchaeology, where they are being used more and more frequently. There are several new possibilities that they offer; for instance, the easier and faster sharing of data among institutions, the possibility of permanent documentation, or new opportunities of data analysis. An important requirement, however, is whether the data obtained from different scanning devices are comparable and whether the possible varying outputs could affect further analyses, such as the estimation of the biological profile. Therefore, we aimed to investigate two important questions: (1) whether 3D models acquired by two different scanning technologies (structured light and laser) are comparable and (2) whether the scanning equipment has an effect on the anthropological analyses, such as age-at-death estimation and sex assessment. 3D models of ossa coxa (n = 29) were acquired by laser (NextEngine) and structured light (HP 3D Structured Light Scanner PRO 2) scanners. The resulting 3D models from both scanners were subjected to age-at-death analyses (via the quantitative method of Stoyanova et al., 2017) and sex analyses (via Diagnose Sexuelle Probabiliste 2 of Brůžek et al., 2017). Furthermore, high quality scans of a small sample (n = 5) of pubic symphyseal surfaces with the RedLux Profiler device were acquired as reference surfaces to which the outputs from both scanners were compared. Small deviations between surfaces were more evident in more rugged surfaces (in areas of depression and protrusion). Even though small differences from the reference surfaces were found, they did not have a significant effect on the age and sex estimates. It never resulted in the opposite sex assignment, and no significant differences were observed between age estimates (with the exception of those with the TPS/BE model).

Estimation of age in forensic anthropology: historical perspective and recent methodological advances

Estimation of age represents a central focus of forensic anthropological analysis of human skeletal remains and of the living. Advances registered in recent research include the topics of taphonomic impact, new anatomical areas of interest, histology, population variation, the dental pulp chamber, technology, mathematical approaches, biochemical analysis and techniques specifically targeting the living. This article reviews the historical development of age estimation methods and considers likely future directions.

Bone Mineral Density Adult Age Estimation in Forensic Anthropology: A Test of the DXAGE Application

Estimating age-at-death of individuals represented only by skeletonized human remains is a fundamental aspect of forensic anthropological casework. Recently, several researchers have proposed that bone mineral density (BMD) is a useful predictor of age-at-death in forensic contexts. Navega et al. (JFS 63(2):497-503) developed an online application called DXAGE for calculating age-at-death from BMD parameters. This study tests the utility of DXAGE by utilizing data from the National Health and Nutrition Examination Survey (NHANES). BMD data from a female subsample (n = 470) of the NHANES 2007-2008 dataset were analyzed, and the relationship between predicted age and real age was examined. Inaccuracy was 14.25 years, and bias was -7.20 years. Results show that there is a weak correlation between predicted and actual age (r = 0.47) using the DXAGE application. While BMD data are potentially useful for predicting age age-at-death, the DXAGE application should be used cautiously in forensic anthropological contexts.

Can you make morphometrics work when you know the right answer? Pick and mix approaches for apple identification

Morphological classification of living things has challenged science for several centuries and has led to a wide range of objective morphometric approaches in data gathering and analysis. In this paper we explore those methods using apple cultivars, a model biological system in which discrete groups are pre-defined but in which there is a high level of overall morphological similarity. The effectiveness of morphometric techniques in discovering the groups is evaluated using statistical learning tools. No one technique proved optimal in classification on every occasion, linear morphometric techniques slightly out-performing geometric (72.6% accuracy on test set versus 66.7%). The combined use of these techniques with post-hoc knowledge of their individual successes with particular cultivars achieves a notably higher classification accuracy (77.8%). From this we conclude that even with pre-determined discrete categories, a range of approaches is needed where those categories are intrinsically similar to each other, and we raise the question of whether in studies where potentially continuous natural variation is being categorised the level of match between categories is routinely set too high.

A validation study of the Stoyanova et al. method (2017) for age-at-death estimation quantifying the 3D pubic symphyseal surface of adult males of European populations

The age-at-death estimation thresholds have recently been shifted towards a more objective assessment of the aging process. Such a non-subjective approach offers quantitative methods of age estimation; for instance, the method relating to the surfaces of pubic symphyses of males published by Stoyanova et al. (J Forensic Sci 62:1434-1444, 2017). A validation study was conducted to test the method performance in European samples. The sample consisted of 96 meshes of pubic symphyses of male individuals (known sex and age) that came from four different samples (two Portuguese collections, one Swiss, and one Crete). Stoyanova's method based on five regression models (three univariate and two multivariate models) performed worse in our sample, but only when the whole sample (without age limitation) was included. A sample limited to individuals under 40 years of age achieved better results in our study. The best results were reached through the thin plate spline algorithm (TPS/BE) with a root mean square error of 5.93 years and inaccuracy of 4.47 years. Generally, the multivariate regression models did not contribute to better age estimation. In our sample in all age categories, age was systematically underestimated. The quantitative method tested in this study works best for individuals under 40 years of age and provides a suitable basis for further research.

A Study on the Asymmetry of the Human Left and Right Pubic Symphyseal Surfaces Using High-Definition Data Capture and Computational Shape Methods

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.

DXAGE: A New Method for Age at Death Estimation Based on Femoral Bone Mineral Density and Artificial Neural Networks

Age at death estimation in adult skeletons is hampered, among others, by the unremarkable correlation of bone estimators with chronological age, implementation of inappropriate statistical techniques, observer error, and skeletal incompleteness or destruction. Therefore, it is beneficial to consider alternative methods to assess age at death in adult skeletons. The decrease in bone mineral density with age was explored to generate a method to assess age at death in human remains. A connectionist computational approach, artificial neural networks, was employed to model femur densitometry data gathered in 100 female individuals from the Coimbra Identified Skeletal Collection. Bone mineral density declines consistently with age and the method performs appropriately, with mean absolute differences between known and predicted age ranging from 9.19 to 13.49 years. The proposed method-DXAGE-was implemented online to streamline age estimation. This preliminary study highlights the value of densitometry to assess age at death in human remains.