Measurements of developing teeth, and carpals and epiphyses of the ulna and radius for assessing new cut-offs at the age thresholds of 10, 11, 12, 13 and 14 years

Combining Bayesian Calibration and Copula Models for Age Estimation

Accurately estimating and predicting chronological age from some anthropometric characteristics of an individual without an identity document can be crucial in the context of a growing number of forced migrants. In the related literature, the prediction of chronological age mostly relies upon the use of a single predictor, which is usually represented by a dental/skeletal maturity index, or multiple independent ordinal predictor (stage of maturation). This paper is the first attempt to combine a robust method to predict chronological age, such as Bayesian calibration, and the use of multiple continuous indices as predictors. The combination of these two aspects becomes possible due to the implementation of a complex statistical tool as the copula. Comparing the forecasts from our copula-based method with predictions from an independent model and two single predictor models, we showed that the accuracy increased.

Premolar maturity index (IPM) for indicating legal age 12 years in a sample of south Indian children - A digital pantomographic study

Legal age of 12 years has been set as the minimum age of criminal responsibility in many countries. This paper concerned a method for predicting the legal age 12 years based on the maturation of lower first and second premolars. The sample consisted of 900 digital pantomographs of south Indian children (450 males, 450 females) aged between 8 and 16 years. Among them, 580 DPTs were used as test sample and 320 DPTs as validation sample. New cut-offs at the age threshold 12 years were determined by using the measurement of open apices in first premolars (IPM1 < 0.10), second premolars (IPM2 < 0.14) and the combined method (IPM1 + IPM2 < 0.12). The sensitivity (Se), specificity (Sp) and posttest probability (PTP) were established. For IPM1 < 0.10, the Se, Sp and PTP were 92.4 %, 91.3 % and 91.1 % for males and 90.8 %, 87 % and 86.5 % for females. For IPM2 < 0.14, they were 92.6 %, 93.6 % and 93.4 % for males and 91.5 %, 83.1 % and 83.4 % for females. And, for the combined predictor (IPM1 + IPM2 < 0.12), these values were 92.6 %, 94.8 % and 94.6 % and 90.5 %, 84.9 % and 84.7 % in males and females respectively. The best score of positive predictive value and specificity was obtained for males with the combined predictor (IPM1 + IPM2 < 0.12) and with single predictor (IPM1 < 0.10) for females. To conclude, the combined predictor has resulted in better discrimination in males, while in females the single predictor (IMP1 < 0.10) did slightly better. Further studies are warranted to test the combination of dental and skeletal indicators for the prediction of 12 years in the studied population.

Quantitative and Qualitative Approaches for Dental Age Assessment in Sub Adult Portuguese Population: European Regression Formula and Demirjian Stages

INTRODUCTION

Over the last decade, the criminal justice system among the European countries deals with a new group of people, the undocumented people. In the criminal field, most of the suspected claimed to be under the minor legal age according to the type of crime. The government of each European country is committed to protecting the children and vulnerable people. There are serious safety concerns since adults falsely claim to be minors and legal systems oppose to such claims. In this study, we have used different age assessment methods and some of them without accuracy.

OBJECTIVE

To meet the general considerations we developed a study using the current dental age assessment methods. Hence, for the Portuguese population, this study aims to validate the European regression formula between the ages of 6 and 15 years of age; to estimate the cut-off point for the age of 12 years, and to compare the quantitative approach of European regression formula with Demirjian's qualitative approach for age estimation.

MATERIAL AND METHODS

483 orthopantomograms were analysed using the European formula and Demirjian scoring stages. A new method, Model 2, was designed to better suit the Portuguese population.

RESULTS

The European formula: average age underestimation of 4.88 for the third quadrant and 4.04 months for the fourth quadrant; and a mean absolute error (MAE) of 10.93 and 10.68 months respectively. Demirjian method: average overestimation of 8.70 months, MAE of 12.85 months. In Model 2: MAE of 9.37 months for the third quadrant, and 9.28 months for the fourth quadrant. Both European formula and Demirjian method had an area under ROC curves results above 0.93. Discrepancy of sensitivity between methods for the specific cut-off point: 11.48. The results obtained in this study can be extrapolated to 87.33% of the Portuguese population.

CONCLUSIONS

The European regression formula can be applied for the Portuguese population, and seems to be more accurate than Demirjian's methodology in this population. Nevertheless, both European regression formula and Demirjian method present similarly suitable results in the classification of 12 years of age, although there is a noticeable discrepancy favouring the European regression formula. The European Formula when applied for criminal age assessment, independently of population, is mandatory to indicate to the judicial institutions, the sensitivity of the results.

Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy

Three-dimensional convolutional neural networks (3D CNN) of artificial intelligence (AI) are potent in image processing and recognition using deep learning to perform generative and descriptive tasks. Compared to its predecessor, the advantage of CNN is that it automatically detects the important features without any human supervision. 3D CNN is used to extract features in three dimensions where input is a 3D volume or a sequence of 2D pictures, e.g., slices in a cone-beam computer tomography scan (CBCT). The main aim was to bridge interdisciplinary cooperation between forensic medical experts and deep learning engineers, emphasizing activating clinical forensic experts in the field with possibly basic knowledge of advanced artificial intelligence techniques with interest in its implementation in their efforts to advance forensic research further. This paper introduces a novel workflow of 3D CNN analysis of full-head CBCT scans. Authors explore the current and design customized 3D CNN application methods for particular forensic research in five perspectives: (1) sex determination, (2) biological age estimation, (3) 3D cephalometric landmark annotation, (4) growth vectors prediction, (5) facial soft-tissue estimation from the skull and vice versa. In conclusion, 3D CNN application can be a watershed moment in forensic medicine, leading to unprecedented improvement of forensic analysis workflows based on 3D neural networks.

Dental Age Assessment by I2M and I3M: Portuguese Legal Age Thresholds of 12 and 14 Year Olds

Objective

Better understanding of dental age assessment may help in cases of age estimation in Forensic Clinics. The first aim was to provide essential information on method reliability for upcoming studies using dental age assessment by second molar index (I_2M), and third molar index (I_3M) for age estimation on legal ages of 12 - 14 years. The second aim was to document forensic method outcomes of the Demirjian method which has already been used in forensic clinic.

Material and Methods

Two samples were used for this purpose: for I_2M, 633 orthopantomographs (270 females / 363 males), the age range from 7 to 17 years and for I_3M, 471 orthopantomographs (253 females / 218 males), the age range from 10 to 23 years, from the database population of Lisbon North University Hospital Center, approved by the Ethic Committee.

Results

The I_3M cut-off point (1.133) for 12- year- olds obtained better results than the cut-off point stated by the I_2M (0.135). Besides, I_2M cut-off point (0.001) for 14- year- olds showed better results when compared with the cut-off point (0.705) established by the I_3M. Both methods are reliable for the legal age thresholds of 12 and 14 years. However, using I_2M and I_3M allows us to vary the cut-off value to privilege sensitivities or specificity, depending on which is more appropriate to the intended application.

Conclusions

The accuracy (88.94%) of I_3M obtained better results for the 12- year- old cut-off point (1.133) and the accuracy (90.21%) of the I_2M performed better for the 14- year- old cut-off point (0.001).

Measurement of the open apices of mandibular first and second premolars to test the chronological age over 14 years: Study on a sample of south Indian children

Age estimation is an integral part of forensic medical and dental practice. In many countries, the age threshold of 14 years is set to determine the minimum age for criminal responsibility. In the present study, the authors studied the final maturation of the first (IPM₁) and second mandibular premolars (IPM₂) by Cameriere maturity index and determined cut-offs at the age threshold of 14 years, and validate on the test sample. Orthopantomograms of 960 healthy south Indian children and sub-adults (480 boys and 480 girls) aged between 10 and 18 were analysed, 640 as training sample and 320 as a test sample. The results of logistic regression analysis with age (</≥14 years) as a dependent variable and IPM₁, IPM_2, and sex as predictor variables on training sample showed that both IPM₁ and IPM₂ significantly related to the legal age of 14 years but not the sex (p = 0.052). A receiver operating characteristic (ROC) curve analysis was performed to evaluate the specific cut-off values of IPM₁ and IPM₂ for predicting 14 years. A cut- off value of IPM₁ < 0.01 and IPM₂ < 0.02 were obtained using the highest Youden index value. Our results on test sample showed that the combined predictor, IPM₁ + IPM₂ < 0.02, showed the highest specificity (97.5% in boys and 92.5% for girls), better post-test probability, 97.2% in boys and 91.9% for girls, and a smaller number of false positives (6.8%). In conclusion, the combination of IPM₁ and IPM₂ could be useful in determining the age of over 14 years in south Indian children.

Evaluation of proximal humeral epiphysis ossification in 3.0 T MR images according to the Dedouit staging method: Is it be used for age of majority?

Magnetic resonance imaging (MRI) for forensic age estimation is among the research issues since it does not lead to radiation exposure. In this study, the ossification stage of the proximal humeral epiphysis was determined retrospectively in 178 male and 109 female individuals in the 12 to 30-year age group using 3.0 T MRI. All images were evaluated with the proton density fat saturated turbo spin echo (PD TSE FS) sequence and the T2 TSE FS sequence. A five-stage scoring system was used following the method of Dedouit et al. The relevant statistics were defined as minimum, maximum, mean ± standard deviation, 95% confidence interval of mean and median and the intra- and interobserver agreement levels were very good (κ > 0.80). There were no significant age differences between males and females in any of the stages (all p-values>0.05). According to the present study, stage 5 was initially observed at age 22 years for both genders. According to our results, it is possible to determine the completion of the 18th year of life in either gender on the shoulder joint. Proximal humeral epiphysis ossification may be used as an additional method for forensic age estimation through MRI.

Accuracy of the cutoff value of the third molar maturity index: an Egyptian study

Background

This study aimed to test the sensitivity and specificity of the third molar maturity index (I3M) cutoff value to discriminate between individuals above and below 18 years of age in an Egyptian sample.

Material and methods

Digital images of 247 orthopantographs (97 boys and 150 girls) were evaluated. The cutoff value of I3Mobtained from the results of Cameriere et al. (Int J Legal Med 122:493–497, 2008) was evaluated in both girls and boys.

Results

Sensitivity (the proportion of individuals being 18 years of age or older) was 95% and 73% in boys and girls, respectively. Meanwhile, specificity (the proportion of individuals younger than 18) was 100% in boys and 97% in girls. The proportion of correctly classified boys was 97% while it was 59% in girls.

Conclusion

It can be concluded that the third molar maturity index can discriminate between individuals who are 18 years and over and those under 18 with higher accuracy in boys.

DNA methylation markers in combination with skeletal and dental ages to improve age estimation in children

Age estimation is critical in forensic science, in competitive sports and games and in other age-related fields, but the current methods are suboptimal. The combination of age-associated DNA methylation markers with skeletal age (SA) and dental age (DA) may improve the accuracy and precision of age estimation, but no study has examined this topic. In the current study, we measured SA (GP, TW3-RUS, and TW3-Carpal methods) and DA (Demirjian and Willems methods) by X-ray examination in 124 Chinese children (78 boys and 46 girls) aged 6-15 years. To identify age-associated CpG sites, we analyzed methylome-wide DNA methylation profiling by using the Illumina HumanMethylation450 BeadChip system in 48 randomly selected children. Five CpG sites were identified as associated with chronologic age (CA), with an absolute value of Pearson's correlation coefficient (r)>0.5 (p<0.01) and a false discovery rate<0.01. The validation of age-associated CpG sites was performed using droplet digital PCR techniques in all 124 children. After validation, four CpG sites for boys and five CpG sites for girls were further adopted to build the age estimation model with SA and DA using multivariate linear stepwise regressions. These CpG sites were located at 4 known genes: DDO, PRPH2, DHX8, and ITGA2B and at one unknown gene with the Illumina ID number of 22398226. The accuracy of age estimation methods was compared according to the mean absolute error (MAE) and root mean square error (RMSE). The best single measure for SA was the TW3-RUS method (MAE=0.69years, RMSE=0.95years) in boys, and the GP method (MAE=0.74years, RMSE=0.94years) in girls. For DA, the Willems method was the best single measure for both boys (MAE=0.63years, RMSE=0.78years) and girls (MAE=0.54years, RMSE=0.68years). The models that incorporated SA and DA with the methylation levels of age-associated CpG sites provided the highest accuracy of age estimation in both boys (MAE=0.47years, R²=0.886) and girls (MAE=0.33years, R²=0.941). Cross validation of the results confirmed the reliability and validity of the models. In conclusion, age-associated DNA methylation markers in combination with SA and DA greatly improve the accuracy of age estimation in Chinese children. This method may be applied in forensic science, in competitive sports and games and in other age-related fields.

A new formula for assessing skeletal age in growing infants and children by measuring carpals and epiphyses of radio and ulna

The aim of this study is to develop a specific formula for the purpose of assessing skeletal age in a sample of Italian growing infants and children by measuring carpals and epiphyses of radio and ulna. A sample of 332 X-rays of left hand-wrist bones (130 boys and 202 girls), aged between 1 and 16 years, was analyzed retrospectively. Analysis of covariance (ANCOVA) was applied to study how sex affects the growth of the ratio Bo/Ca in the boys and girls groups. The regression model, describing age as a linear function of sex and the Bo/Ca ratio for the new Italian sample, yielded the following formula: Age = -1.7702 + 1.0088 g + 14.8166 (Bo/Ca). This model explained 83.5% of total variance (R(2) = 0.835). The median of the absolute values of residuals (observed age minus predicted age) was -0.38, with a quartile deviation of 2.01 and a standard error of estimate of 1.54. A second sample test of 204 Italian children (108 girls and 96 boys), aged between 1 and 16 years, was used to evaluate the accuracy of the specific regression model. A sample paired t-test was used to analyze the mean differences between the skeletal and chronological age. The mean error for girls is 0.00 and the estimated age is slightly underestimated in boys with a mean error of -0.30 years. The standard deviations are 0.70 years for girls and 0.78 years for boys. The obtained results indicate that there is a high relationship between estimated and chronological ages.