Multi-factorial age estimation: A Bayesian approach combining dental and skeletal magnetic resonance imaging

A probability model for estimating age in young individuals relative to key legal thresholds: 15, 18 or 21-year

Age estimations are relevant for pre-trial detention, sentencing in criminal cases and as part of the evaluation in asylum processes to protect the rights and privileges of minors. No current method can determine an exact chronological age due to individual variations in biological development. This study seeks to develop a validated statistical model for estimating an age relative to key legal thresholds (15, 18, and 21 years) based on a skeletal (CT-clavicle, radiography-hand/wrist or MR-knee) and tooth (radiography-third molar) developmental stages. The whole model is based on 34 scientific studies, divided into examinations of the hand/wrist (15 studies), clavicle (5 studies), distal femur (4 studies), and third molars (10 studies). In total, data from approximately 27,000 individuals have been incorporated and the model has subsequently been validated with data from 5,000 individuals. The core framework of the model is built upon transition analysis and is further developed by a combination of a type of parametric bootstrapping and Bayesian theory. Validation of the model includes testing the models on independent datasets of individuals with known ages and shows a high precision with separate populations aligning closely with the model's predictions. The practical use of the complex statistical model requires a user-friendly tool to provide probabilities together with the margin of error. The assessment based on the model forms the medical component for the overall evaluation of an individual's age.

Age assessment of unaccompanied foreign minors: an analyses of knowledge and practices among Italian pediatricians

BACKGROUND

Increases in migration patterns in the recent years have led to a continuously growing number of unaccompanied foreign minors (UFMs) entering Italy. As part of processing and integration, age assessment is performed by pediatricians upon request of regulatory bodies. Updated guidelines for age estimation procedures were published in 2020 in order to prioritize the well-being of the minors and the accuracy of the assessment. Nonetheless, literature suggests that the recently established multidisciplinary approach has not yet been widely adopted by physicians.

METHODS

A cross-sectional exploratory survey was distributed to pediatricians in Italy in order to gauge their range of experience with UFMs and age assessment protocols.

RESULTS

In total 344 pediatricians participated in the survey, originating from varied regions in Italy. Out of pediatricians who reported conducting age assessment procedures (38.9%), only a small fraction (14.2%) confirmed being knowledgeable about the methodology. Instead, a significant portion (28.8% and 56.4%) either had partial awareness or lacked knowledge of these procedures. These responses significantly differed when comparing hospital and outpatient pediatricians or according to their geographical area of work (p <0.05).

CONCLUSION

Survey responses suggest that a gap in awareness and experience regarding a multidisciplinary approach to age estimations still exists, likely in part due to a lack of resources, especially at the regional level. In the future, efforts towards the education of professionals and mobilization of resources for investment in the field will be crucial for the improvement of work with UFMs and other migrant populations.

Age estimation from iliac auricular surface using Bayesian inference and principal component analysis: a CT-based study in an Indian population

Age estimation constitutes one of the pillars of human identification. The auricular surface of the ilium presents as a durable and robust structure within the human skeletal framework, capable of enabling accurate age estimation in older adults. Amongst different documented auricular age estimation methods, the Buckberry-Chamberlain method offers greater objectivity through its component-based approach. The present study aimed to test the applicability of the Buckberry-Chamberlain method in an Indian population through a CT-based examination of the auricular surface. CT scans of 435 participants undergoing CT examinations following the advice of their treating physicians were scrutinized for different age-related auricular changes. Three of the five morphological features described by Buckberry-Chamberlain could be appreciated on CT scans, and thus further statistical analysis was restricted to these features. Transition analysis coupled with Bayesian inference was undertaken individually for each feature to enable age estimation from individual features, while circumventing age mimicry. A Bayesian analysis of individual features yielded highest accuracy percentages (98.64%) and error rates (12.99 years) with macroporosity. Transverse organization and apical changes yielded accuracy percentages of 91.67% and 94.84%, respectively, with inaccuracy computations of 10.18 years and 11.74 years, respectively. Summary age models, i.e. multivariate age estimation models, derived by taking this differential accuracy and inaccuracy into consideration yielded a reduced inaccuracy value of 8.52 years. While Bayesian analysis undertaken within the present study enables age estimation from individual morphological features, summary age models appropriately weigh all appreciable features to yield more accurate and reliable estimates of age.

Skeletal age estimation of living adolescents and young adults: A pilot study on conventional radiography versus magnetic resonance imaging and staging technique versus atlas method

OBJECTIVE

To compare conventional radiography (CR) and magnetic resonance imaging (MRI) of the left hand/wrist and both clavicles for forensic age estimation of adolescents and young adults.

MATERIALS AND METHODS

CR and MRI were prospectively conducted in 108 healthy Caucasian volunteers (52 males, 56 females) aged 16 to 21 years. Skeletal development was assessed by allocating stages (wrist, clavicles) and atlas standards (hand/wrist). Inter- and intra-observer agreements were quantified using linear weighted Cohen's kappa, and descriptive statistics regarding within-stage/standard age distributions were reported.

RESULTS

Inter- and intra-observer agreements for hand/wrist CR (staging technique: 0.840-0.871 and 0.877-0.897, respectively; atlas method: 0.636-0.947 and 0.853-0.987, respectively) and MRI (staging technique: 0.890-0.932 and 0.897-0.952, respectively; atlas method: 0.854-0.941 and 0.775-0.978, respectively) were rather similar. The CR atlas method was less reproducible than the staging technique. Inter- and intra-observer agreements for clavicle CR (0.590-0.643 and 0.656-0.770, respectively) were lower than those for MRI (0.844-0.852 and 0.866-0.931, respectively). Furthermore, although shifted, wrist CR and MRI within-stage age distribution spread were similar, as were those between staging techniques and atlas methods. The possibility to apply (profound) substages to clavicle MRI rendered a more gradual increase of age distributions with increasing stages, compared to CR.

CONCLUSIONS

For age estimation based on the left hand/wrist and both clavicles, reference data should be considered anatomical structure- and imaging modality-specific. Moreover, CR is adequate for hand/wrist evaluation and a wrist staging technique seems to be more useful than an atlas method. By contrast, MRI is of added value for clavicle evaluation.

Forensic Age Estimation: A Multifactorial Approach in a Retrospective Population Study

Objectives: The objective of this study was to evaluate the accuracy of forensic age estimation in a German population by combining clavicle and wisdom teeth assessments based on cone beam computed tomography (CT) data. The study aimed to determine the reliability of this approach in predicting biological age. Material and Methods: A total of 161 CT data sets from 120 males and 41 females with known exact ages were evaluated by three raters. The clavicle was assessed according to stages 1-5 (including substages 2a-c and 3a-c), and the Demirjian stage's classification method was used for the wisdom teeth. Inter-class correlation (ICC) was calculated to assess the agreement among the three raters. Additionally, ordinary least square regressions were performed to predict chronological age using the clavicle or one of the four teeth. Finally, age prediction models using multiple indicators were developed. Results: The ICCs ranged from 0.82 for the clavicle to 0.86 and 0.88 for the wisdom teeth. Linear estimation tended to overestimate chronological age, especially in subjects over 18 years old. The clavicle showed the strongest overestimation. Combining age estimation from the clavicle with the upper and lower wisdom teeth improved the predictive power, resulting in a 14% and 15% increase in R² for the upper and lower wisdom teeth, respectively. Adding more than one tooth to the prediction did not improve the predictive power (all ΔR² < 1%). Conclusions: Age estimation using CT can be significantly improved by combining information from the analysis of wisdom teeth with age estimation based on the clavicle.

Mixed cumulative probit: a multivariate generalization of transition analysis that accommodates variation in the shape, spread and structure of data

Biological data are frequently nonlinear, heteroscedastic and conditionally dependent, and often researchers deal with missing data. To account for characteristics common in biological data in one algorithm, we developed the mixed cumulative probit (MCP), a novel latent trait model that is a formal generalization of the cumulative probit model usually used in transition analysis. Specifically, the MCP accommodates heteroscedasticity, mixtures of ordinal and continuous variables, missing values, conditional dependence and alternative specifications of the mean response and noise response. Cross-validation selects the best model parameters (mean response and the noise response for simple models, as well as conditional dependence for multivariate models), and the Kullback-Leibler divergence evaluates information gain during posterior inference to quantify mis-specified models (conditionally dependent versus conditionally independent). Two continuous and four ordinal skeletal and dental variables collected from 1296 individuals (aged birth to 22 years) from the Subadult Virtual Anthropology Database are used to introduce and demonstrate the algorithm. In addition to describing the features of the MCP, we provide material to help fit novel datasets using the MCP. The flexible, general formulation with model selection provides a process to robustly identify the modelling assumptions that are best suited for the data at hand.

Validity of age estimation methods and reproducibility of bone/dental maturity indices for chronological age estimation: a systematic review and meta-analysis of validation studies

Several approaches have been developed to estimate age, an important aspect of forensics and orthodontics, using different measures and radiological examinations. Here, through meta-analysis, we determined the validity of age estimation methods and reproducibility of bone/dental maturity indices used for age estimation. The PubMed and Google Scholar databases were searched to December 31, 2021 for human cross-sectional studies meeting pre-defined PICOS criteria that simultaneously assessed the reproducibility and validity. Meta-estimates of validity (mean error: estimated age-chronological age) and intra- and inter-observer reproducibility (Cohen's kappa, intraclass correlation coefficient) and their predictive intervals (PI) were calculated using mixed-effect models when heterogeneity was high (I2 > 50%). The literature search identified 433 studies, and 23 met the inclusion criteria. The mean error meta-estimate (mixed effects model) was 0.08 years (95% CI - 0.12; 0.29) in males and 0.09 (95% CI - 0.12; 0.30) in females. The PI of each method spanned zero; of nine reported estimation methods, Cameriere's had the smallest (- 0.82; 0.47) and Haavikko's the largest (- 7.24; 4.57) PI. The reproducibility meta-estimate (fixed effects model) was 0.98 (95% CI 0.97; 1.00) for intra- and 0.99 (95% CI 0.98; 1.00) for inter-observer agreement. All methods were valid but with different levels of precision. The intra- and inter-observer reproducibility was high and homogeneous across studies.

Mathematically optimal decisions in forensic age assessment

Forensic age estimation generally involves considerable amounts of uncertainty. Forensic age indicators such as teeth or skeleton images predict age only approximately, and this is likely to remain true even for future forensic age indicators. Thus, forensic age assessment should aim to make the best possible decisions under uncertainty. In this paper, we apply mathematical theory to make statistically optimal decisions to age assessment. Such an application is fairly straightforward assuming there is a standardized procedure for obtaining age indicator information from individuals, assuming we have data from the application of this procedure to a group of persons with known ages, and assuming the starting point for each individual is a probability distribution describing prior knowledge about the persons age. The main problem is then to obtain such a prior. Our analysis indicates that individual priors rather than a common prior for all persons may be necessary. We suggest that caseworkers, based on individual case information, may select a prior from a menu of priors. We show how information may then be collected over time to gradually increase the robustness of the decision procedure. We also show how replacing individual prior distributions for age with individual prior odds for being above an age limit cannot be recommended as a general method. Our theoretical framework is applied to data where the maturity of the distal femur and the third molar is observed using MRI. As part of this analysis we observe a weak positive conditional correlation between maturity of the two body parts.

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.

A probability model for assessing age relative to the 18-year old threshold based on magnetic resonance imaging of the knee combined with radiography of third molars in the lower jaw

OBJECTIVE

This study aims to generate a statistical model based on magnetic resonance imaging of the knee and radiography of third molars in the lower jaw, for assessing age relative to the 18-year old threshold.

METHODS

In total, 58 studies correlating knee or tooth development to age were assessed, 5 studies for knee and 7 studies for tooth were included in the statistical model. The relation between the development of the anatomical site, based on a binary system, and age were estimated using logistic regression. Separate meta-populations for knee and tooth were generated from the individual based data for men and women. A weighted estimate of probabilities was made by combining the probability densities for knee and tooth. Margin of errors for males and females in different age groups and knee and tooth maturity were calculated within the larger framework of transition analysis using a logit model as a base. Evidentiary values for combinations of knee and tooth maturity were evaluated with likelihood ratios.

RESULTS

For males, the sensitivity for the method was calculated to 0.78 (probability of correctly classifying adults), the specificity 0.90 (probability of correctly classifying minors), the negative predictive value 0.80 (proportion identified minors are minors) and the positive predictive value 0.89 (proportion identified adults are adults) indicating a model better at identifying minors than adults. The point at which half the female population has reached closed knee lies before the 18-year threshold, adding the knee as an indicator lowers specificity and increases sensitivity. The sensitivity when using tooth as an indicator for females is 0.24 and specificity 0.97, signifying few minors misclassified as adults but also a low probability of identifying adults. The negative predictive value for women when using tooth as the sole indicator is 0.56 and positive predictive value 0.88. Probabilities were calculated for males and females assuming a uniform age distribution between 15 and 21years. The calculated margin of error of minors classified as adults in a population between 15 and 21 years with the model was 11% for males and 12% for females. Further, the evidentiary value as well as margin of error vary for different combinations of knee and tooth maturity.

CONCLUSION

The statistical model based on the combination of MRI knee and radiography of mandibular third molars is a valid method to assess age relative to the 18-year old threshold when applied on males and of limited value in females.

Forensic age estimation based on magnetic resonance imaging of the proximal humeral epiphysis in Chinese living individuals

Forensic age estimation in living individuals is mainly based on radiological features, but direct radiography and computed tomography lead to a rise in ethical concerns due to radiation exposure. Thus, the contribution of magnetic resonance imaging (MRI) to age estimation of living individuals is a subject of ongoing research. In the current study, MRIs of shoulder were retrospectively collected from a modern Chinese Han population and data from 835 individuals (599 males and 236 females) in the age group 12 to 30 years were obtained. A staging technique based on (Schmidt et al. Int J Legal Med 121(4):321-324, 2007) and (Kellinghaus et al. Int J Legal Med 124(4):321-325, 2010) was used and all images were evaluated with T1-wieghted turbo spin echo (T1-TSE) sequence and T2-weighed fat suppression (T2-FS) sequence. One-sided images were assessed because data from both sides were considered coincidental, as no significant differences were found (P > 0.05). Two MRI sequences were evaluated separately and subsequently compared. Regression models and supportive vector classification (SVC) models were established accordingly. The intraobserver and interobserver agreement levels were good. Compared with T1-TSE sequence, the R² values of T2-FS sequence were generally higher, while the mean absolute deviation (MAD) values were slightly lower. For T2-FS sequence, the MAD value was 1.49 years in males and 2.19 years in females. With two MRI sequences incorporated, the SVC model obtained with 85.7% correctly classified minors and 96.2% correctly classified adults in males, while 83.3% and 98.0% respectively in females. In conclusion, T2-FS sequence may slightly outperform the T1-TSE sequence in shoulder MRI analysis for age estimation, while shoulder MRIs could be a reliable prediction indicator for the 18-year threshold and two MRI sequences incorporated are encouraged.

Age estimation based on 3D post-mortem computed tomography images of mandible and femur using convolutional neural networks

Age assessment has attracted increasing attention in the field of forensics. However, most existing works are laborious and requires domain-specific knowledge. Modern computing power makes it is possible to leverage massive amounts of data to produce more reliable results. Therefore, it is logical to use automated age estimation approaches to handle large datasets. In this study, a fully automated age prediction approach was proposed by assessing 3D mandible and femur scans using deep learning. A total of 814 post-mortem computed tomography scans from 619 men and 195 women, within the age range of 20-70, were collected from the National Forensic Service in South Korea. Multiple preprocessing steps were applied for each scan to normalize the image and perform intensity correction to create 3D voxels that represent these parts accurately. The accuracy of the proposed method was evaluated by 10-fold cross-validation. The initial cross-validation results illustrated the potential of the proposed method as it achieved a mean absolute error of 5.15 years with a concordance correlation coefficient of 0.80. The proposed approach is likely to be faster and potentially more reliable, which could be used for age assessment in the future.

Comparison of two established 2D staging techniques to their appliance in 3D cone beam computer-tomography for dental age estimation

For medicolegal purposes, orthodontic or orthognathic treatment various stomatological staging technique for age estimation with appliance of conventional radiographic images have been published. It remains uninvestigated if cone beam computer-tomography delivers comparable staging results to the conventional radiographic stages of third molar analysis. We conducted a retrospective cross-sectional study of 312 patients aged 13–21 years. Dental age estimation staging technique, introduced by Nolla and Demirjian, were applied on the left lower third molar imaged by conventional panoramic radiographs and cone beam computer-tomography. It was investigated if 2D and 3D imaging presented different staging results for dental age estimation. In 21% the Demirjian’s staging differed by a single stage between 2 and 3D images. The greatest congruence (87%) between 2 and 3D images was revealed for stage 7 (G). In contrary, stage 5 (E) presented the lowest level of congruence with 47.4%. The categorization of Nolla revealed divergences in staging for than two categorical variables in Nolla’s stages 3, 4, 5 and 6. In general, the analysis of the data displayed the divergence for Nolla’s stages 4–8. The staging results for 2D and 3D imaging in accordance to the rules of Nolla and Demirjian showed significant differences. Individuals of 18 years may present immature third molars, thus merely an immature third molar cannot reject legal majority. Nolla’s and Demirjian’s 2D and 3D imaging present significantly different staging results.

Automated age estimation of young individuals based on 3D knee MRI using deep learning

Age estimation is a crucial element of forensic medicine to assess the chronological age of living individuals without or lacking valid legal documentation. Methods used in practice are labor-intensive, subjective, and frequently comprise radiation exposure. Recently, also non-invasive methods using magnetic resonance imaging (MRI) have evaluated and confirmed a correlation between growth plate ossification in long bones and the chronological age of young subjects. However, automated and user-independent approaches are required to perform reliable assessments on large datasets. The aim of this study was to develop a fully automated and computer-based method for age estimation based on 3D knee MRIs using machine learning. The proposed solution is based on three parts: image-preprocessing, bone segmentation, and age estimation. A total of 185 coronal and 404 sagittal MR volumes from Caucasian male subjects in the age range of 13 and 21 years were available. The best result of the fivefold cross-validation was a mean absolute error of 0.67 ± 0.49 years in age regression and an accuracy of 90.9%, a sensitivity of 88.6%, and a specificity of 94.2% in classification (18-year age limit) using a combination of convolutional neural networks and tree-based machine learning algorithms. The potential of deep learning for age estimation is reflected in the results and can be further improved if it is trained on even larger and more diverse datasets.

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.

The influence of motion artefacts on magnetic resonance imaging of the clavicles for age estimation

PURPOSE

To determine how motion affects stage allocation to the clavicle's sternal end on MRI.

MATERIALS AND METHODS

Eighteen volunteers (9 females, 9 males) between 14 and 30 years old were prospectively scanned with 3-T MRI. One resting-state scan was followed by five intentional motion scans. Additionally, a control group of 72 resting-state scans were selected from previous research. Firstly, six observers allocated developmental stages to the clavicles independently. Secondly, they re-assessed the images, allocating developmental statuses (immature, mature). Finally, the resting-state scans of the 18 volunteers were assessed in consensus to decide on the "correct" stage/status. Results were compared between groups (control, prospective resting state, prospective motion), and between staging techniques (stages/statuses).

RESULTS

Inter-observer agreement was low (Krippendorff α 0.23-0.67). The proportion of correctly allocated stages (64%) was lower than correctly allocated statuses (83%). Overall, intentional motion resulted in fewer assessable images and less images of sufficient evidential value. The proportion of correctly allocated stages did not differ between resting-state (64%) and motion scans (65%), while correctly allocated statuses were more prevalent in resting-state scans (83% versus 77%). Remarkably, motion scans did not render a systematically higher or lower stage/status, compared to the consensus.

CONCLUSION

Intentional motion impedes clavicle MRI for age estimation. Still, in case of obvious disturbances, the forensic expert will consider the MRI unsuitable as evidence. Thus, the development of the clavicle as such and the staging technique seem to play a more important role in allocating a faulty stage for age estimation.

Dental and Skeletal Imaging in Forensic Age Estimation: Disparities in Current Approaches and the Continuing Search for Optimization

Medical imaging for forensic age estimation in living adolescents and young adults continues to be controversial and a subject of discussion. Because age estimation based on medical imaging is well studied, it is the current gold standard. However, large disparities exist between the centers conducting age estimation, both between and within countries. This review provides an overview of the most common approaches applied in Europe, with case examples illustrating the differences in imaging modalities, in staging of development, and in statistical processing of the age data. Additionally, the review looks toward the future because several European research groups have intensified studies on age estimation, exploring four strategies for optimization: (1) increasing sample sizes of the reference populations, (2) combining single-site information into multifactorial information, (3) avoiding ionizing radiation, and (4) conducting a fully automated analysis.

Applicability of 3.0 T MRI images in the estimation of full age based on shoulder joint ossification: Single-centre study

Skeletal maturity is evaluated by many radiological methods for forensic age estimation. Direct radiography and computed tomography lead to a rise in ethical concerns due to radiation exposure. Therefore, magnetic resonance imaging (MRI) has currently been used in recent studies. In this study, the ossification stage of the shoulder joint was determined retrospectively in 178 male and 109 female individuals in the age group 12 to 30 years using 3.0 T MRI. All the images were evaluated with T1-weighted turbo spin echo (T1 TSE) sequence and T1 fast low angle shot two-dimensional sequence (T1 FL2D). The combined staging method, which was defined by Kellinghaus et al. and Schmeling et al., was used. The intra- and inter-observer agreement levels were very good (κ and κ_w). There were no significant age differences between males and females in all stages. In most of the stages, the ossification of the proximal humeral epiphyses occurred earlier in females than in males. Stage 4 did not occur in either of the sexes before the 18th birthday as the youngest patients in this stage was at 19 and 18 years of age in males and females, respectively. We concluded that evaluating the ossification of the proximal humeral epiphysis with MRI imaging for forensic age estimation may be beneficial. Evaluating the same anatomical structure with different MRI sequences may be useful for accurate staging diagnosis.

Age estimation based on magnetic resonance imaging of the ankle joint in a modern Chinese Han population

OBJECTIVES

To expand the database on magnetic resonance imaging (MRI) analysis of distal tibial and calcaneal epiphyses as proposed by Saint-Martin et al. and investigate a more elaborate staging technique to establish regression models for age estimation in a modern Chinese Han population.

MATERIALS AND METHODS

T1-weighted ankle MRIs were retrospectively collected from April 2008 to July 2019, and data from 590 individuals (372 males and 218 females; aged from 8 to 25 years old) were obtained. One-sided sagittal images were assessed because data from both sides were considered coincidental, as no significant differences were found (P > 0.05). Three-stage and six-stage staging techniques were applied separately and subsequently compared. A subset was re-assessed a second time and by a different observer. Regression models were established accordingly.

RESULTS

Our results showed very good repeatability and consistency of two staging techniques (all Cohen's kappa values were more than 0.8). By comparison, the values of the coefficient of determination (R²) of the six-stage technique were generally higher than those of the three-stage technique. Compared with the distal tibia and two ankle bones combined, the calcaneus decreased the mean absolute deviation (MAD) with the six-stage technique. In males, incorporating only the calcaneus resulted in a MAD of 2.15 years, with correct classification rates of 87.5% adults and 50.0% among minors. In females, the corresponding results were 1.67 years, 100.0%, and 44.4%, respectively.

CONCLUSIONS

The six-stage technique may outperform the three-stage technique in MRI analysis of ankle bones for age estimation, while age estimation based on the calcaneus may perform better than that based on the distal tibia or both ankle bones in a modern Chinese Han population.