Accuracy of scoring of the epiphyses at the knee joint (SKJ) for assessing legal adult age of 18 years

Bone Age Determination of Epiphyseal Fusion at Knee Joint and Its Correlation with Chronological Age

Background and Objectives: Bone age determination is a valuable method for forensic and disaster identifications of unknown human remains, as well as for medical and surgical procedural purposes. This retrospective research study aimed to determine the age based on epiphyseal fusion stages and investigate differences related to gender. Materials and Methods: X-rays of the knee were collected from medical imaging centers in hospitals in the south of Jordan and examined by two observers who determined the bone epiphyseal phase of closure for the femur, tibia, and fibula bone ends close to the knee based on a three-stage classification. Results: The main results revealed that females showed earlier epiphyseal union (Stage II) at the lower end of the femur and the upper ends of the tibia and fibula compared to males. In males, the start of complete union (Stage III) at knee bones was seen at the age of 17-18 years, while in females, it was seen at the age of 16-17 years. Additionally, knee bones showed complete union in 100% of males and females in the age groups 21-22 years and 20-21 years, respectively. Although females showed an earlier start and end of epiphyseal complete union than males, analysis of collected data showed no significant age differences between males and females at the three stages of epiphyseal union of the knee bones. Conclusions: Findings of the radiographic analysis of bone epiphyseal fusion at the knee joint are a helpful method for chronological age determination. This study supports the gender and ethnicity variation among different geographical locations. Studies with a high sample number would be needed to validate our findings.

Medico-legal indicators and cut-offs in different age classes through quantitative analysis of epiphyseal fusion segments on knee CT scans

Scientists are interested in determining age in subadults for several forensic purposes. High- resolution instrumental techniques are being increasingly used for age estimation, driven by the need to minimize errors; in this context, several studies have focused on the knee joint, recognized as a potential site for age examination in late adolescence. We analyzed 200 CT scans performed on Russian subjects (106 males and 94 females) between 13 and 20 years, without growth diseases, endocrine disorders, or osteodystrophy. Each subject underwent two scans, one for each leg. Two indicators were measured for each bone (femur, tibia and fibula): the entire length of the epiphyseal scar and the length of the part/s that is/are fused with metaphysis. Intra class Correlation Coefficient (ICC) was performed to evaluate the intra-operator reproducibility. The ratio between the two lengths was calculated for each bone (FemurR, TibiaR and FibulaR). The first aim was to evaluate a correlation between the ratios of the three bones and the three bones treated as a single parameter (given by the sum of the ratios) versus age. The results showed good correlations in both cases (τ a = 0.74, 0.64, 0.57 and 0.67). The second aim was to estimate the cut-offs derived from the sum of the three ratios respect to four age classes (14-15 years: cut-off ≤ 0.63, 15-16 years: cut-off ≤ 1.19, 16-17 years: cut-off ≥ 0.68 and 17-18 years: cut-off ≥ 1.49. The results from this research encourage further studies of the knee joint as an indicator of legal adult age.

Artificial Intelligence as a Decision-Making Tool in Forensic Dentistry: A Pilot Study with I3M

Expert determination of the third molar maturity index (I3M) constitutes one of the most common approaches for dental age estimation. This work aimed to investigate the technical feasibility of creating a decision-making tool based on I3M to support expert decision-making. Methods: The dataset consisted of 456 images from France and Uganda. Two deep learning approaches (Mask R-CNN, U-Net) were compared on mandibular radiographs, leading to a two-part instance segmentation (apical and coronal). Then, two topological data analysis approaches were compared on the inferred mask: one with a deep learning component (TDA-DL), one without (TDA). Regarding mask inference, U-Net had a better accuracy (mean intersection over union metric (mIoU)), 91.2% compared to 83.8% for Mask R-CNN. The combination of U-Net with TDA or TDA-DL to compute the I3M score revealed satisfying results in comparison with a dental forensic expert. The mean ± SD absolute error was 0.04 ± 0.03 for TDA, and 0.06 ± 0.04 for TDA-DL. The Pearson correlation coefficient of the I3M scores between the expert and a U-Net model was 0.93 when combined with TDA and 0.89 with TDA-DL. This pilot study illustrates the potential feasibility to automate an I3M solution combining a deep learning and a topological approach, with 95% accuracy in comparison with an expert.

[Age assessment using CT of knee joint and neural network technologies]

Age assessment of living persons plays an important role in clinical and sports medicine, as well as in law practice. Traditional methods have a number of problems: age restrictions, technical difficulties of visualization, low reproducibility and subjectivity of estimation. The proposed approach, which implies the use of multispiral computed tomography (MSCT) and database mining, will eliminate these drawbacks and improve the estimation of age. The aim of the study was to investigate the use of deep learning algorithms to classify the age groups (with a threshold level of 18 years) for CT images of knee joint. The study included 455 MSCT images of the knee joint of male and female subjects aged from 13 to 24. The method included score assessment of the distal femur's epiphyseal synostosis stages, tibia and fibula proximal epiphyses and a preliminary statistical analysis of correlations between age and stages of synostosis. The challenge of binary classification of target age groups with the use of convolutional neural networks was implemented at the second phase of the trial. Various architectures of convolutional neural networks and their ensembles were tested. The result of the study showed that the total score of epiphyseal synostosis has the highest correlation with the age (r=0.88). The proposed method of chronological age assessment on the basis of the knee area CT images research using deep learning algorithms demonstrated a good result. The classification accuracy (threshold level of 18 years) was 0.86.

The Cameriere, Haavikko, Demirjian, and Willems methods for the assessment of dental age in Croatian children

AIM

This study aimed to evaluate the accuracy and precision of the Cameriere European formula, Demirjian, Haavikko, and Willems methods for estimating dental age in a sample of children with permanent dentition in Croatia.

MATERIAL AND METHODS

The study consisted of a sample of 1576 panoramic radiographs; a sub-sample of 84 OPGs, in which all first seven mandibular teeth were maturated, was excluded from the study. A final sample of 1492 (704 males and 788 females) aged 6.0 to 13.9 years was evaluated. Seven mandibular teeth from the left side of the mandible were analyzed, and dental age (DA) was determined by the Cameriere European formula, Demirjian method from 1976, Haavikko, and Willems methods and compared to chronological age (CA). In addition, the mean age difference (DA-CA), the mean absolute error (MAE) between dental and chronological age, the percentage of the individuals of dental age within ± 0.25 to ± 2 years of chronological age, and intra-observer and inter-observer statistics were calculated.

RESULTS

The Cameriere European formula estimated the best dental age compared to the chronological age; the mean underestimation was - 0.4 years for both sexes, Haavikko underestimated by - 0.17 years, while Demirjian and Willems overestimated by 1.02 years and 0.48 years, respectively. The most significant difference showed the Demirjian method in 11-year-old and 12-year-old females. The MAE were 0.50 years, 1.01 years, 0.61 years, and 0.78 years in males and 0.51 years, 1.18 years, 0.61 years, and 0.70 years in females for the Cameriere European formula, Haavikko, Willems, and Demirjian methods, respectively. Furthermore, the Cameriere European formula showed the highest proportions of individuals with DA within ± 0.5 year difference of the CA, 61.5% in males and 59.6% in females. In addition, the Cameriere method showed the best intra-observer and inter-observer agreements.

CONCLUSIONS

Although the Demirjian method was used previously in Croatian children for legal, medical, and clinical purposes, the Cameriere European formula, Haavikko, and Willems were more accurate in the tested sample. According to our findings, the Cameriere European formula showed the best accuracy and precision in dental age assessment in Croatian children following Haavikko, and we recommend it as the method of the first choice in forensic and clinical analyses.

Investigation of the relationship between corpse age and microscopic morphometric indices of the fourth and sixth rib bones

This study was performed to estimate the corpse age using histological examinations of the fourth and sixth ribs by a morphometric method. One hundred samples of referred bodies of the Legal Medicine Organization of Lorestan province, Iran, were examined. The sampling was performed from the fourth and sixth ribs. The transverse sections of the samples were prepared, in which various variables such as the diameter of the haversian system (DHC), haversian system perimeter (PHS), haversian system area (AHS), and the thickness of the haversian lamellae (TH) were measured using a Motic microscope video system and the Motic Image Plus 2 software. To predict age from sex and the morphometric parameters a stepwise multiple linear regression was used. Accordingly, AHS in rib 4, DHC with lens 10 in rib 4, DHC with lens 10 in rib 6 and TH in rib 6 remained in the model at significance level 0.05 (R square = 0.1654). Although age was associated with some of the studied parameters, the obtained equation was not fit enough to predict the exact age. Further parameters should be studied for prediction of age in corpse.

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.

Application of knee MRI in forensic age estimation: A retrospective cohort

INTRODUCTION

Forensic age estimation is performed via clinical examination and utilizing various imaging modalities. Currently, radiography and CT are used. In this study we aim to evaluate if magnetic resonance imaging (MRI) can be used to determine stages of fusion in the epiphysis of the tibia and femur, and if these stages are significantly different regarding the mean age of subjects classified in each one.

METHODS

A total of 193 subjects were included in the study. Knee MR imaging was performed on all of the patients, and the patients were categorized based on imaging findings of the tibial and femoral epiphysis. Tukey multiple comparison test and analysis of variance were used to assess if the difference in the mean age of the groups were significantly different.

RESULTS

Analysis of variance revealed that the mean of the five groups, both in tibia and femur imaging were significantly different. Analysis of variance showed that in most of the cases, the groups mean age significantly differed from the other groups. Tukey multiple comparison tests showed that although the differences between stages I-III could not be regarded as significant, MR imaging was suitable in distinguishing stages IV-V from stages I-III.

CONCLUSION

MR imaging of the knee may be a suitable imaging modality to assess an individual's age, does not involve ionizing radiation, and that with imaging a single anatomical location, at least two epiphyses could be used to determine the age.

IMPLICATIONS FOR PRACTICE

Utilization of knee MRI by clinicians as a safe and practical age estimation method.

Adjusting posterior probabilities to meet predefined accuracy criteria: A proposal for a novel approach to osteometric sex estimation

The osteometric methods are the most reliable way to estimate the sex of skeletons when DNA analysis is not used. However, as osteometric studies usually ignore the overlap in male and female skeletal dimensions, they rarely achieve accuracy sufficient for forensic application. To resolve this issue, recent studies suggest sex estimation only when posterior probability (pp) is greater than 0.95, but that approach does not always provide sufficient accuracy and creates a large proportion of unsexed skeleton. Thus, our study aimed to explore whether it is possible to adjust pp on skeletal measurements with pronounced sexual dimorphism to meet 95% accuracy and to enable sex estimation on a reasonable proportion of individuals. From 207 skeletons, we included 65 postcranial measurements and selected 10% of variables with the highest sexual dimorphism. We computed univariate and bivariate discriminant functions using pp threshold of 0.5, 0.95, and the threshold required to achieve accuracy of ≥ 95%. Discriminant functions with pp=0.5 obtained accuracy of 85%-93%, while those with pp≥0.95 and adjusted posterior probabilities obtained 94%-99%. However, we showed that by selecting a particular threshold, sex could be estimated on a greater proportion of individuals than for pp≥0.95: 42%-86% vs. 24%-62% for univariate and 69%-95% vs. 49%-78% for bivariate functions. Therefore, when developing sex estimation models, we suggest not to use fixed pp level, but to adjust pp to achieve 95% accuracy and to minimize the percentage of unsexed skeletons.

Validation of the third molar maturity index cut-off value of <0.08 for indicating legal age of 18 years in Eastern Chinese region

Having a reliable, inexpensive and simple method to estimate 18 years of age would be of help in the forensic field. This study aimed to test the accuracy of the third molar maturity index (I_3M) in indicating the legal adult age of 18 years. This retrospective cross-sectional study analysed 450 digital panoramic images of Eastern Chinese children and young adults (226 females and 224 males) aged between 14 and 22 years. A cut-off value of I_3M < 0.08 was tested in discriminating adults from minors for both sex. For females, the sensitivity of the test (Se) was 75.0%, with a 95% confidence interval (95%CI) of 67.5% to 82.5%. The specificity of the test (Sp) was 100%. The proportion accurately classified (Ac) individuals was 85.8% (95%CI, 81.3% to 90.4%). The Bayes post-test probability was 100% (93.6% to 100%). For males, Se, Sp and Ac were 91.9% (95%CI, 87.1% to 96.7%), 92.0%(95%CI, 86.7% to 97.3%) and 92% (95%CI, 88.4% to 95.5%), respectively. The Bayes post-test probabilities was 92% (95%CI, 88.4% to 95.5%). Males were ahead in the development of third molars comparing to females according to I_3M. A stepwise logistic regression analysis showed that both I_3M and sex contribute to the regression model to discriminate adults (≥18 years) from minors (<18 years), while a receiver operating curve (ROC) analysis indicated some better accuracy of I_3M < 0.12 in females, without statistically significant difference when compared to I_3M < 0.08. The results of this study show that the cut-off value of I_3M < 0.08 may help to discriminate Eastern Chinese adults from minors. However, further study should evaluate the usefulness and possible variability of I_3M cut-off value in a specific population before used for legal and forensic procedures.

Third molar maturity index for indicating the legal adult age in southeastern France

The estimation of age in living subjects is today a significant issue because of the increase in the situations in which it arises and its legal consequences. In line with the Study Group on Forensic Age Diagnostics of the German Association of Legal Medicine's recommendations, it is based on the concomitant use of physical examination and methods for estimating bone age and dental age. Given the variations between the populations, the use of the latter requires their validation on all the ethnic groups on which they can be used. This aim of this study was to access the interest of the Cameriere's third molar maturity index (I_3M) to indicate if an individual had reached the age of 18 in a sample of individuals from southeastern France. The studied sample consisted of OPTs 339 (184 females and 155 males) subjects aged between 14 and 22 years old. A logistic regression analysis with the adult age and minor age as dichotomous dependent variable and gender and I_3M as predictor variables showed that gender was not statistically significant in discriminating adults and minors. The receiver operating curve (ROC) analysis showed the best discrimination performance of the specific cut-off value of I_3M<0.08 in discriminating adults from minors. The proportion of accurate classification was 0.897 and 0.916 for females and males, respectively. The specificity (Sp) and sensitivity (Se) results for females were 0.962 and 0.813, respectively. Sp and Se for males were 0.953 and 0.871, respectively. The Bayes post-test probability was 0.961 and 0.955 in females and males respectively. Obtained results showed that a cut-off value of I_3M<0.08 may be an additional tool for indicating adult age in the tested population.

The third molars for indicating legal adult age in Montenegro

AIM

From a medico-legal and penalty point of view, it is essential to conclude if an individual is a minor or an adult (18 years of age). Methods based on the third molar development have been used for this purpose. The present article aims to verify the Nolla's stages of mineralization of the third molars and a third molar maturity index (I3M) which is based on the measures of the projections of open apices normalized by their height in the sample of Montenegrins.

METHOD AND SAMPLE

The sample consisted of 683 panoramic radiographs (324 males and 359 females) between 13 and 24 years of age. The specific mineralization stages of Nolla and the cut-off value of I3M < 0.08 was used to discriminate adults and minors.

RESULTS

The best performance in discriminating adults and minors was for I3M < 0.08 followed by the Nolla stage 9. For I3M < 0.08 the results demonstrated high sensitivity of 0.92 and 0.82 and specificity of 0.94 and 0.96 in males and females, respectively. The proportions of correctly classified individuals were 0.93 in males and 0.89 in females. The Nolla stage 9 demonstrated the sensitivity of 0.95 and 0.85 and the specificity of 0.84 and 0.90 in males and females, respectively. The proportions of correctly classified individuals were 0.90 in males and 0.87 in females.

CONCLUSION

The suggested value of I3M < 0.08 followed by Nolla stage 9 can be used to discriminate adults from minors with high specificity.

Dental age estimation using four Demirjian's, Chaillet's and Willems' methods in Kosovar children

BACKGROUND

Tooth formation was recognized as useful body system to assess maturity and predict age. Tooth mineralization is much less affected by the endocrine and different nutritional status than bone mineralization, and teeth formation provides a more reliable indication of chronological age. Demirjian et al. in 1973 presented a scoring system and method for dental age estimation on a sample of French-Canadian children. Chaillet et al. and Willems et al. modified original Demirjian method. This study aimed to evaluate the accuracy of four Demirjian's, Chaillet and Willems methods for age estimation in the children of Kosovo.

MATERIALS AND METHODS

The cross-sectional study was based on the evaluation of the sample of 1022 orthopantomograms (OPTs) of healthy Kosovar children, aged between 5 and 14 years. OPTs were taken from the Radiology unit of University Dentistry Clinical Center of Kosova, as part of random clinical treatment. We tested the accuracy of four methods based on seven mandibular teeth, Demirjian from 1973 (Dem73) and 1976 (Dem76), Chaillet from 2005 (Chaillet) and Willems from 2001 (Willems) and two Demirjian's methods based on different sets of four teeth (Dem76PM1 and Dem76IN2).

RESULTS

For most tested methods, we found statistically significant differences between the chronological age (CA) and dental age (DA) (p < 0.05). In males, the most accurate method were those using four teeth, Dem76IN2 (0.03 years) following by Dem76PM1 (-0.05 years), following those using seven teeth, Willems (-0.14 years), Chaillet (-0.24 years) and Dem73 (0.43 years). In females, dental age was the most accurate for the Willems method (-0.24 years) following Chaillet (-0.35 years), Dem76 (0.43 years) and Dem73 (0.55 years), while Dem76PM1 and Dem76IN2 overestimated by 0.45 years and 0.46 years, respectively. The mean absolute difference between DA and CA were between 0.61 years for the Willems, to 0.78 years for the Dem73 in males, and 0.64 years for the Willems to 0.75 years for the Dem76IN2 in females.

CONCLUSION

The Willems method was the most accurate for estimating a dental age if all seven mandibular teeth are available for analysis, and we found the similar accuracy of Dem76PM1 and Dem76IN2 methods. Therefore, we may encourage their use for age estimation on the Kosovar children.

A 2-year follow-up MRI study for the evaluation of an age estimation method based on knee bone development

Age estimation is an actual topic in the area of forensic medicine with a special focus on the age limits of 16 and 18 years. Current research on this topic relies on retrospective data of inhomogeneous populations relating to sex, age range, and socioeconomic status. In this work, we present a 2-year follow-up study for the evaluation of an age estimation method on a prospective magnetic resonance imaging (MRI) knee data collective of a homogeneous population. The study includes 40 male subjects from northern Germany aged 14 to 21 years. Three MRI examinations were evenly acquired within 2 years for each subject. As a first evaluation, a three-stage system was used to assess the ossification status of the knee (I:"open", II:"partially ossified", III:"fully ossified"). Three raters assessed the growth plate of the distal femur, proximal tibia, and proximal fibula based on central 2D slices. A good inter-rater agreement was attained (κ = 0.84). All subjects younger than 18 years were rated as stage I and had a cumulative knee score (SKJ) ≤ 5. Based on the follow-up datasets, new parameters quantifying the intra-individual ossification process were calculated. The results of this follow-up analysis show a different start, end, and speed of each growth plate's maturation as well as an ossification peak for individuals at the age of 16. The generated MRI database provides new insights into the ossification process over time and serves as a basis for further evaluations of age estimation methods.

The third molar maturity index in indicating the legal adult age in Kosovar population

The third molar tooth, known as the "wisdom tooth," is the only tooth that can be used to determine legal adult age. This study aimed to test the accuracy of Cameriere's third molar maturity index (I_3M) in assessing the legal adult age of 18 years in the Kosovar population. Orthopantomographs (OPTs) of 1221 healthy living Kosovar individuals, aged between 12 and 23 years and with no congenital or developmental anomalies, were analyzed. Intra-class correlation coefficients were 0.858 (95% CI, 0.786 to 0.906) and 0.852 (95% CI, 0.779 to 0.903) for intra-rater and for inter-rater agreement, respectively. The sample was divided into training dataset (800 OPTs) and test dataset (421 OPTs). The training dataset was used to generate the logistic regression model, while the test dataset was used to study the performance of the model. I_3M and gender as independent variables and adult age (≥ 18 years) or minor age (< 18 years) as the dependent variable were used for logistic regression analysis. The receiver operating curve (ROC) analysis was used to determine the specific cut-off value of I_3M for predicting adult age. The results showed that only I_3M statistically significantly contributed to discriminating adults and minors. ROC analysis showed that the cut-off value of I_3M < 0.08 was the best in discriminating adults and minors. An analysis of the test dataset (421 OPTs) showed that as I_3M decreased the age gradually increased. The performance of the cut-off value of I_3M < 0.08, to discriminate between adults and minors, was analyzed by contingency tables for both sexes. In males, the accurate classification (Acc) was 0.968 (95% CI, 0.926 to 0.985), the sensitivity (Se) was 0.962 (95% CI, 0.925 to 0.978), and the specificity (Sp) was 0.976 (95% CI, 0.929 to 0.995). The Bayes post-test probability (Bayes PTP) was 0.975 (95% CI, 0.905 to 1.00). In females, Acc was 0.909 (95% CI, 0.870 to 0.917), Se and Sp were 0.826 (95% CI, 0.787 to 0.834) and 0.991 (95% CI, 0.953 to 1.00) respectively, while Bayes PTP was 0.989 (95% CI, 0.926 to 1.00). Our data support the usefulness of I_3M < 0.08 to indicate legal adult age in a Kosovar population.