Optimal trait scoring for age estimation

Sex and ancestry patterning of residual correlations in human dental development: Cooperative genetic interaction and phenotypic plasticity

OBJECTIVES

Most research in human dental age estimation has focused on point estimates of age, and most research on dental development theories has focused on morphology or eruption. Correlations between developing teeth using ordinal staging have received less attention. The effect of demographic variables on these correlations is unknown. I tested the effect of reference sample demographic variables on the residual correlation matrix using the lens of cooperative genetic interaction (CGI).

MATERIALS AND METHODS

The sample consisted of Moorrees et al., Journal of Dental Research, 1963, 42, 1490-1502, scores of left mandibular permanent teeth from panoramic radiographs of 880 London children 3-22.99 years of age stratified by year of age, sex, and Bangladeshi or European ancestry. A multivariate cumulative probit model was fit to each sex/ancestry group (n = 220), each sex or ancestry (n = 440), and all individuals (n = 880). Residual correlation matrices from nine reference sample configurations were compared using Bartlett's tests of between-sample difference matrices against the identity matrix, hierarchical cluster analysis, and dendrogram cophenetic correlations.

RESULTS

Bartlett's test results were inconclusive. Cluster analysis showed clustering by tooth class, position within class, and developmental timing. Clustering patterns and dendrogram correlations showed similarity by sex but not ancestry.

DISCUSSION

Expectations of CGI were supported for developmental staging. This supports using CGI as a model for explaining patterns of variation within the dentition. Sex was found to produce consistent patterns of dental correlations, whereas ancestry did not. Clustering by timing of development supports phenotypic plasticity in the dentition and suggests shared environment over genetic ancestry to explain population differences.

The effect of reference sample composition and size on dental age interval estimates

OBJECTIVES

Validation studies in juvenile dental age estimation primarily focus on point estimates while interval performance for reference samples of different ancestry group compositions has received minimal attention. We tested the effect of reference sample size and composition by sex and ancestry group on age interval estimates.

MATERIALS AND METHODS

The dataset consisted of Moorrees et al. dental scores from panoramic radiographs of 3334 London children of Bangladeshi and European ancestry and 2-23 years of age. Model stability was assessed using standard error of mean age-at-transition for univariate cumulative probit and sample size, group mixing (sex or ancestry), and staging system as factors. Age estimation performance was tested using molar reference samples of four sizes, stratified by year of age, sex, and ancestry. Age estimates were performed using Bayesian multivariate cumulative probit with 5-fold cross-validation.

RESULTS

Standard error increased with decreasing sample size but showed no effect from mixing by sex or ancestry. Estimating ages using a reference and target sample of different sex reduced success rate significantly. The same test by ancestry groups had a lesser effect. Small sample size (n < 20/year of age) negatively affected most performance metrics.

DISCUSSION

We found that reference sample size, followed by sex, primarily drove age estimation performance. Combining reference samples by ancestry produced equivalent or better estimates of age by all metrics than using a single-demographic reference of smaller size. We further proposed that population specificity is an alternative hypothesis of intergroup difference that has been erroneously treated as a null.

Reference and target sample age distribution impacts between model types in dental developmental age estimation

The performance of age estimation methods may vary due to a combination of method- and sample-related factors. Method development and evaluation necessitates understanding what influences these factors have on age estimation outcomes. In the specific context of juvenile dental age estimation, we used a single dataset and complete factorial design to systematically test four potential sources of difference: age distributions of reference and target sample (uniform, unimodal, U-shaped), Bayesian (multivariate Bayesian cumulative probit) vs. classical regression modeling (multivariate adaptive regression splines i.e. MARS), and model selection bias. The dataset consisted of 850 sets of left mandibular molar scores from London children 5-18 years old. True age and estimated age intervals in target samples were compared for bias, root-mean-squared error, precision, and accuracy using locally weighted smoothing of performance measures across the age range and means of performance metrics between factor-level combinations. We found interactions of model type, reference distribution, and target distribution. MARS models showed consistent evidence of age mimicry. Central tendency of the reference sample corresponded with increased bias while central tendency of the target sample corresponded with reduced RMSE and reduced precision for both model types. We found evidence of model selection bias, mitigated through averaging model metrics. We conclude that reference and target sample distribution influences and model selection bias are sufficient to cause difference in model performance within a single population. We suggest using Bayesian modeling, drawing uniform reference and target samples, and calculating test error on a hold-out sample to mitigate these challenges in method development.

Forensic age estimation in males by MRI based on the medial epiphysis of the clavicle

Increasing cross-border migration has brought forensic age assessment into focus in recent decades. Forensic age estimation is based on the three pillars: physical and medical constitution, bone age, and tooth age. Part of the bone age examination includes the assessment of the medial end of the clavicles when the hand bones are already fully developed and a minority must be excluded. Recent research has brought MRI to the forefront as a radiation-free alternative for age assessment. However, there exits only a few studies with large sample size regarding the clavicles and with controversies about staging, motion artifacts, and exclusion based on anatomic norm variants. In the current prospective study, 338 central European male individuals between 13 and 24 years of age underwent MRI examination of the sternoclavicular region. Development was assessed by three blinded raters according to the staging system described by Schmeling et al. and Kellinghaus et al. and related to age by descriptive statistics and transition analyses with a cumulative probit model. In addition, reliability calculations were performed. No statistically significant developmental difference was found between the left and right clavicles. Inter-rater agreement was only moderate, but intra-rater agreement, on the other hand, was good. Stage 3c had a minimum age of 19.36 years and appears to be a good indicator of proof of majority. The minimum age of stage 4 was lower compared with other studies, 20.18 years, and therefore seems not to be an indicator of age of 21 years. In conclusion, we confirmed the value of clavicular MRI in the age estimation process. The transition analysis model is a good approach to circumvent the problems of age mimicry and samples that are not fully equilibrated. Given the moderate agreement between raters, a consensus reading is recommended.

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.

Conditional independence assumption and appropriate number of stages in dental developmental age estimation

When estimating the age of an individual it is critical that 1) age ranges are as narrow as possible while still capturing the true age of the individual with an acceptable frequency, and 2) this frequency is known. When multiple traits are used to produce a single age estimate, the simplest practice is to assume that the traits are conditionally independent from one another given age. Unfortunately, if the traits are correlated once the effect of age is accounted for, the resulting age intervals will be too narrow. The frequency at which the age interval captures the true age of the individual will be decreased below the expected value to some unknown degree. It is therefore critical that age estimation methods that include multiple traits incorporate the possible correlations between them. Moorrees et al. (1963) [1] scores of the permanent mandibular dentition from 2607 individuals between 2 and 23 years were used to produce and cross-validate a cumulative probit model for age estimation with an optimal number of stages for each tooth. Two correction methods for covariance of development between teeth were tested: the variance-covariance matrix for a multivariate normal, and the Boldsen et al. (2002) [2] ad-hoc method. Both correction methods successfully decreased age interval error rates from 21% to 23% in the uncorrected model to the expected value of 5%. These results demonstrate both the efficacy of these correction methods and the need to move away from assuming conditional independence in multi-trait age estimation.

Bone age estimation with the Greulich-Pyle atlas using 3T MR images of hand and wrist

The age estimation of the hand bones by means of X-ray examination is a pillar of the forensic age estimation. Since the associated radiation exposure is controversial, the search for ionizing radiation-free alternatives such as MRI is part of forensic research. The aim of the current study was to use the Greulich-Pyle (GP) atlas on MR images of the hand and wrist to provide reference values for assessing the age of the hand bones. 3T hand MR images of 238 male participants between the ages of 13 and 21 were acquired using 3D gradient echo sequences (VIBE, DESS). Two readers rated the images using the X-ray-based GP atlas method. A descriptive analysis and a transitional analysis were used for the statistical processing of the data. The agreement between and within the raters was assessed. In addition, a comparison was made with the chronological age and with X-ray studies. The descriptive analysis and the transition analysis showed similar results. Both evaluations showed good agreement with X-ray studies. The comparison with the chronological age showed a difference of 0.37 and 0.54 years for the two readers. The age estimate based on the cross-validated transition analysis showed a mean error of -0.28 years. Inter- and intra-rater agreement were good. In summary, it can be concluded that age estimation of hand bones with MR images is routinely applicable with the GP atlas as an alternative without ionizing radiation. However, in order to reduce the estimation error, a multi-factorial assessment based on examinations of several body regions is still recommended.

Sub-adult aging method selection (SAMS): A decisional tool for selecting and evaluating sub-adult age estimation methods based on standardized methodological parameters

OBJECTIVES

A decisional tool was developed to select sub-adult age estimation methods referenced in a centralized database. Through a freely accessible webpage interface, this tool allows users to evaluate how much the sampling and statistical protocols of these referenced methods comply with methodological recommendations published for building and applying methods in forensic anthropology.

MATERIALS AND METHODS

261 publications on sub-adult age estimation were collected. Three search parameters describing the anatomical element(s) and the indicators used to obtain age estimates are chosen by the user to filter the database and present the publications that best correspond to the user's selection. A simple algorithm was created to score age estimation methods according to their relevance and validity. "Relevance" and "Validity" parameters indicate how much a publication complies with user queries and published methodological recommendations, respectively; "Score" is a combination of "Relevance" and "Validity". The closer these parameters are to 1, the better the method complies with the user's choice and standardized protocols.

RESULTS

The publications resulting from the user's query appear as search results alphabetically. They are characterized by their "Relevance", "Validity" and "Score" values and descriptors relating to their methodology, sampling and statistical protocols. The reference of the publications and an URL to access them online are also provided.

CONCLUSIONS

SAMS is a decisional tool based on a centralized database for selecting, accessing and evaluating sub-adult age estimation methods based on published methodological recommendations. Protocol validity can be easily and fully accessed to provide the necessary information for method evaluation. The database will be gradually updated and implemented as new sub-adult age estimation methods are made available online.

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.

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

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.

A Bayesian Approach to Age-at-Death Estimation from Osteoarthritis of the Shoulder in Modern North Americans

Osteoarthritis (OA) is a marker of degeneration within the skeleton, frequently associated with age. This study quantifies the correlation between OA and age-at-death and investigates the utility of shoulder OA as a forensic age indicator using a modern North American sample of 206 individuals. Lipping, surface porosity, osteophyte formation, eburnation, and percentage of joint surface affected were recorded on an ordinal scale and summed to create composite scores that were assigned a specific phase. Spearman's correlation indicated a positive relationship between each composite score and age (right shoulder = 0.752; left shoulder = 0.734). Transition analysis revealed a tendency toward earlier degeneration of the right shoulder. Bayesian statistics generated phase-related age estimates based on highest posterior density regions. Best age estimates were into the seventh decade at the 90th and 50th percentile. The proposed method supplements traditional techniques by providing age estimates beyond a homogenous 50+ age cohort.