Combining dental and skeletal evidence in age classification: Pilot study in a sample of Italian sub-adults

Efficacy of the methods of age determination using artificial intelligence in panoramic radiographs - a systematic review

The aim of this systematic review is to analyze the literature to determine whether the methods of artificial intelligence are effective in determining age in panoramic radiographs. Searches without language and year limits were conducted in PubMed/Medline, Embase, Web of Science, and Scopus databases. Hand searches were also performed, and unpublished manuscripts were searched in specialized journals. Thirty-six articles were included in the analysis. Significant differences in terms of root mean square error and mean absolute error were found between manual methods and artificial intelligence techniques, favoring the use of artificial intelligence (p < 0.00001). Few articles compared deep learning methods with machine learning models or manual models. Although there are advantages of machine learning in data processing and deep learning in data collection and analysis, non-comparable data was a limitation of this study. More information is needed on the comparison of these techniques, with particular emphasis on time as a variable.

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.

Adjusted binary classification (ABC) model in forensic science: An example on sex classification from handprint dimensions

Binary classification techniques are commonly used in forensic examination to test if a specimen belongs to a particular group and base the expert opinion on the questioned evidence. However, most of the currently used methods do not achieve sufficient accuracy due to the ignoring of the specimens classified in the overlapping area. To address the issue, we proposed a novel Adjusted binary classification (ABC) algorithm that automatically adjusts posterior probabilities to reach classification accuracy and positive/negative predicted values (PPV, NPV) of 95 %. In the presented example, we used three handprint measurements from 160 participants (80 males and 80 females) to develop models that would classify sex from their dimensions. The sample was split into the training/cross-validated (70 %) and testing sample (30 %). We developed four classification models using linear discriminant analysis (LDA) by employing traditional single cut-off values and ABC approach that for each group provides a specific posterior probability cut-off threshold. In the cross-validated sample, the accuracy of traditional models was 78.7-92.5 %, while PPVs/NPVs ranged between 78.2 and 93 %. ABC models provided 95 % accuracy, PPV, and NPV, and could classify 35.5-88.1 % of specimens. In the testing sample, ABC models achieved accuracy of 97.3-100 %, PPV/NPV 95.4-100 %, and could be applied to 29.1-87.5 % of specimens. The study demonstrated that the ABC approach could adjust classification models to reach predefined values of accuracy, PPV, and NPV. Therefore, it could be an efficient tool for conducting a binary classification in forensic settings and minimizing the possibilities of incorrect classifications.

Age estimation in the living: A scoping review of population data for skeletal and dental methods

Age estimation of living individuals has become a crucial part of the forensic practice, especially due to the global increase in cross-border migration. The low rate of birth registration in many countries, hence of identification documents of migrants, especially in Africa and Asia, highlights the importance of reliable methods for age estimation of living individuals. Despite the fact that a number of skeletal and dental methods for age estimation have been developed, their main limitation is that they are based on specific reference samples and there is still no consensus among researchers on whether these methods can be applied to all populations. Though this issue remains still unsolved, population information at a glance could be useful for forensic practitioners dealing with such issues. This study aims at presenting a scoping review and mapping of the current situation concerning population data for skeletal (hand-wrist and clavicle) and dental methods (teeth eruption and third molar formation) for age estimation in the living. Two hundred studies on the rate of skeletal maturation and four hundred thirty-nine on the rate of dental maturation were found, covering the period from 1952 and 2020 for a total of ninety-eight countries. For most of the western and central African countries there are currently no data on the rate of skeletal and dental maturation. The same applies to the countries of the Middle East, as well as the eastern European countries, especially as regard the skeletal development.

Minor or adult? Introducing decision analysis in forensic age estimation

Nowadays, forensic age estimation takes an important role in worldwide forensic and medico-legal institutes that are solicited by judicial or administrative authorities for providing an expert report on the age of individuals. The authorities' ultimate issue of interest is often the probability that the person is younger or older than a given age threshold, which is usually the age of majority. Such information is fundamental for deciding whether a person being judged falls under the legal category of an adult. This is a decision that may have important consequences for the individual, depending on the legal framework in which the decision is made. The aim of this paper is to introduce a normative approach for assisting the authority in the decision-making process given knowledge from available findings reported by means of probabilities. The normative approach proposed here has been acknowledged in the forensic framework, and represents a promising structure for reasoning that can support the decision-making process in forensic age estimation. The paper introduces the fundamental elements of decision theory applied to the specific case of age estimation, and provides some examples to illustrate its practical application.

Discriminatory ability of cervical vertebral maturation stages in predicting attainment of the legal age threshold of 14 years: A pilot study using lateral cephalograms

Purpose

In India, the age of 14 years is the legal age threshold for child labour. Therefore, in suspected instances of child labour, age assessment plays a crucial role in determining whether a violation of the law on the employment of children has occurred. The aim of this retrospective cross-sectional study was to assess the discriminatory ability of stages of cervical vertebral maturation (CVM) in predicting the legal age threshold of 14 years.

Materials and Methods

Routinely taken lateral cephalograms from 408 subjects aged 10 to 18 years were evaluated retrospectively using the CVM stages described by Baccetti et al. Descriptive statistics, accuracy, sensitivity, specificity, positive and negative predictive values, and likelihood ratios were calculated for stages 2, 3, and 4 of CVM.

Results

Real age increased as the CVM stage gradually increased. The results of 2×2 contingency tables showed that CVM stage 4 produced an accuracy of 71% and 73%, a false positive rate of 7% and 18%, and a post-test probability of 59% and 68% for boys and girls, respectively.

Conclusion

Based on these findings, it can be concluded that the stages of CVM are of limited use for predicting the attainment of the legal age threshold of 14 years. Future studies should investigate whether combinations of skeletal and dental methods could achieve better accuracy and post-test probability.

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

PURPOSE

To study age estimation performance of combined magnetic resonance imaging (MRI) data of all four third molars, the left wrist and both clavicles in a reference population of females and males. To study the value of adding anthropometric and sexual maturation data.

MATERIALS AND METHODS

Three Tesla MRI of the three anatomical sites was prospectively conducted from March 2012 to May 2017 in 14- to 26-year-old healthy Caucasian volunteers (160 females, 138 males). Development was assessed by allocating stages, anthropometric measurements were taken, and self-reported sexual maturation data were collected. All data was incorporated in a continuation-ratio model to estimate age, applying Bayes' rule to calculate point and interval predictions. Two performance aspects were studied: (1) accuracy and uncertainty of the point prediction, and (2) diagnostic ability to discern minors from adults (≥18 years).

RESULTS

Combining information from different anatomical sites decreased the mean absolute error (MAE) compared to incorporating only one site (P<0.0001). By contrast, adding anthropometric and sexual maturation data did not further improve MAE (P=0.11). In females, combining all three anatomical sites rendered a MAE equal to 1.41 years, a mean width of the 95% prediction intervals of 5.91 years, 93% correctly classified adults and 91% correctly classified minors. In males, the corresponding results were 1.36 years, 5.49 years, 94%, and 90%, respectively.

CONCLUSION

All aspects of age estimation improve when multi-factorial MRI data of the three anatomical sites are incorporated. Anthropometric and sexual maturation data do not seem to add relevant information.

A Review of Bomb Pulse Dating and its Use in the Investigation of Unidentified Human Remains

In cases where there is limited antemortem information, the examination of unidentified human remains as part of the investigation of long-term missing person's cases is a complex endeavor and consequently requires a multidisciplinary approach. Bomb pulse dating, which involves the analysis and interpretation of 14C concentration, is one technique that may assist in these investigations by providing an estimate of year of birth and year of death. This review examines the technique of bomb pulse dating and its use in the identification of differentially preserved unknown human remains. Research and case studies implementing bomb pulse dating have predominantly been undertaken in the Northern Hemisphere and have demonstrated reliable and accurate results. Limitations were, however, identified throughout the literature. These included the small sample sizes used in previous research/case studies which impacted on the statistical significance of the findings, as well as technique-specific issues. Such limitations highlight the need for future research.

Bone age assessment with various machine learning techniques: A systematic literature review and meta-analysis

BACKGROUND

The assessment of bone age and skeletal maturity and its comparison to chronological age is an important task in the medical environment for the diagnosis of pediatric endocrinology, orthodontics and orthopedic disorders, and legal environment in what concerns if an individual is a minor or not when there is a lack of documents. Being a time-consuming activity that can be prone to inter- and intra-rater variability, the use of methods which can automate it, like Machine Learning techniques, is of value.

OBJECTIVE

The goal of this paper is to present the state of the art evidence, trends and gaps in the research related to bone age assessment studies that make use of Machine Learning techniques.

METHOD

A systematic literature review was carried out, starting with the writing of the protocol, followed by searches on three databases: Pubmed, Scopus and Web of Science to identify the relevant evidence related to bone age assessment using Machine Learning techniques. One round of backward snowballing was performed to find additional studies. A quality assessment was performed on the selected studies to check for bias and low quality studies, which were removed. Data was extracted from the included studies to build summary tables. Lastly, a meta-analysis was performed on the performances of the selected studies.

RESULTS

26 studies constituted the final set of included studies. Most of them proposed automatic systems for bone age assessment and investigated methods for bone age assessment based on hand and wrist radiographs. The samples used in the studies were mostly comprehensive or bordered the age of 18, and the data origin was in most of cases from United States and West Europe. Few studies explored ethnic differences.

CONCLUSIONS

There is a clear focus of the research on bone age assessment methods based on radiographs whilst other types of medical imaging without radiation exposure (e.g. magnetic resonance imaging) are not much explored in the literature. Also, socioeconomic and other aspects that could influence in bone age were not addressed in the literature. Finally, studies that make use of more than one region of interest for bone age assessment are scarce.

Radiographic evaluation of dental and cervical vertebral development for age estimation in a young Brazilian population

Age estimation is guided by the evaluation of events that happen during the processes of bone and dental development. The purpose of this study was to validate the method of age estimation proposed by Lajolo et al. (2013) through oro-cervical radiographic indices in Brazilians. The study aimed to verify the effectiveness of age estimation equations through dental and cervical vertebrae examinations, in addition to including dental and cervical vertebrae data in new age estimation equations. The sample consisted of panoramic radiographs and teleradiographs from 510 subjects (8-24.9 years). Age estimation methods were applied by assessing the development of seven mandibular teeth, cervical vertebrae and third molars. Techniques used previously have been combinations of radiographic indices: Oro-Cervical Radiographic Simplified Score (OCRSS) and Oro-Cervical Radiographic Simplified Score without Wisdom Teeth (OCRSSWWT). In the second phase of the study, dental maturation, vertebral measurements, and real age were estimated by regression equations. OCRSS and OCRSSWWT had success rates of 67.4% (R2=0.64) and 70.8% (R2=0.62), respectively. When age estimation equations for tooth evaluations were applied, the average error was 1.3 years, and for cervical vertebrae measurements, the error was 1.9 years. When dental variables and the measurements of cervical vertebrae were included, the average error of equations was 1.0 year. Radiographic indices were easy to perform, and after adequate training, are reliable and can be used in forensic practice. The use of the new equations presented in this study is recommended because including cervical vertebrae and dental data provides greater accuracy for age estimation.

Forensic age estimation for pelvic X-ray images using deep learning

PURPOSE

To develop a deep learning bone age assessment model based on pelvic radiographs for forensic age estimation and compare its performance to that of the existing cubic regression model.

MATERIALS AND METHOD

A retrospective collection data of 1875 clinical pelvic radiographs between 10 and 25 years of age was obtained to develop the model. Model performance was assessed by comparing the testing results to estimated ages calculated directly using the existing cubic regression model based on ossification staging methods. The mean absolute error (MAE) and root-mean-squared error (RMSE) between the estimated ages and chronological age were calculated for both models.

RESULTS

For all test samples (between 10 and 25 years old), the mean MAE and RMSE between the automatic estimates using the proposed deep learning model and the reference standard were 0.94 and 1.30 years, respectively. For the test samples comparable to those of the existing cubic regression model (between 14 and 22 years old), the mean MAE and RMSE for the deep learning model were 0.89 and 1.21 years, respectively. For the existing cubic regression model, the mean MAE and RMSE were 1.05 and 1.61 years, respectively.

CONCLUSION

The deep learning convolutional neural network model achieves performance on par with the existing cubic regression model, demonstrating predictive ability capable of automated skeletal bone assessment based on pelvic radiographic images.

KEY POINTS

• The pelvis has considerable value in determining the bone age. • Deep learning can be used to create an automated bone age assessment model based on pelvic radiographs. • The deep learning convolutional neural network model achieves performance on par with the existing cubic regression model.

Dental age estimation in children with chromosomal syndromes

When the age of an individual is unknown, age assessment refers to the procedures through which authorities try to establish the chronological age of an individual. Dental evidence demonstrated to be very effective in estimating age and dental mineralization is largely deemed a process scarcely influenced by major diseases and nutritional or environmental factors which can affect child growth. This research aims to understand the possible influence of genetic syndromes on dental maturation of affected individuals. The sample is composed of a test sample of 159 chromosomal affected children, 69 males and 90 females, and a control sample of 157 healthy children, 77 males and 80 females aged between 4,49 and 19,8years. London Atlas was applied to estimate dental age on OPGs (orthopantompographies). No statistical significant difference has been found in dental estimates between syndromic and healthy individuals. Moreover no statistical significant difference emerged between sexes and age cohorts. Children affected by Down or Williams syndromes nor mean error neither the mean accuracy per cohort of age show differences compared to non-affected subjects. The London Atlas can be validly applied to age estimation of individuals with multiple agenesis as in Down and Williams syndromes, even if it a slight overestimation of age occurs systematically in syndromic as well as in healthy samples. The current findings suggest that dental maturation is a very stable biological process scarcely affected by even serious illnesses as genetic syndromes.

The age estimation practice related to illegal unaccompanied minors immigration in Italy

The migrants arrived to the Italian coasts in 2016 were 181.436, 18% more than the previous year and 6% more than the highest number ever since. An "unaccompanied minor" (UAM) is a third-country national or a stateless person under eighteen years of age, who arrives on the territory of the Member State unaccompanied by an adult responsible for him/her whether by law or by the practice of the Member State concerned, and for as long as he or she is not effectively taken into the care of such a person; it includes a minor who is left unaccompanied after he/she entered the territory of the Member States. As many as 95.985 UAMs applied for international protection in an EU member country just in 2015, almost four times the number registered in the previous year. The UAMs arrived in Italy were 28.283 in 2016; 94% of them were males, 92% unaccompanied, 8% of them under 15; the 53,6% is 17; the individuals between 16 and 17 are instead the 82%. Many of them (50%), 6561 in 2016, escaped from the sanctuaries, thus avoiding to be formally identified and registered in Italy in the attempt to reach more easily northern Europe countries, since The Dublin Regulations (2003) state that the asylum application should be held in the EU country of entrance or where parents reside. The age assessment procedures can therefore be considered as a relevant task that weighs in on the shoulders of the forensic experts with all the related issues and the coming of age is the important threshold. In the EU laws on asylum, the minors are considered as one of the groups of vulnerable persons towards whom Member States have specific obligations. A proper EU common formal regulation in the matter of age estimation procedures still lacks. According to the Italian legal framework in the matter, a medical examination should have been always performed but a new law completely changed the approach to the procedures of age estimation of the migrant (excluding the criminal cases) with a better adherence to the notions and concepts of vulnerability and psychological and social maturity.

Comparisons between skeletal and dental age assessment in unaccompanied asylum seeking children

BACKGROUND

For children with disputed date of birth, age assessments based on skeletal and dental development are recommended.

AIM

The aim of this retrospective study was to compare and contrast the results of age assessments from these two methods performed on unaccompanied asylum seeking children in Norway. In addition the aim of the analysis was to see if the skeletal age assessment from hand-wrist was operator sensitive.

MATERIALS AND METHODS

Age assessments performed from January 2010 to December 2014 were analysed. Skeletal development of hand-wrist was graded according to Greulich and Pyle (1959). Dental development of the wisdom teeth was scored on orthopantomograms according to Moorrees, Fanning and Hunt (1963) and age assessed from tables published by Liversidge (2008) and Haavikko (1970). In the statistical analysis agreement between the two age assessments was defined according to the asylum seeker's age being assessed to be older or younger than 18 years. The statistical analysis included 3333 boys and 486 girls.

RESULTS

The agreement was 83% for boys and 79% for girls. Approximately 70% of the boys and girls were 18 years or older by both methods. It was more common that the skeletal age was assessed older than 18 years and dental age younger than 18 years for both genders. It could be demonstrated that the age assessment based on skeletal maturation was not operator sensitive.

CONCLUSION

The analyses demonstrate that there is good agreement between the two age assessments, but a method to combine the results would increase the reliability of the age assessments.

Forensic age estimation based on development of third molars: a staging technique for magnetic resonance imaging

BACKGROUND

The development of third molars can be evaluated with medical imaging to estimate age in subadults. The appearance of third molars on magnetic resonance imaging (MRI) differs greatly from that on radiographs. Therefore a specific staging technique is necessary to classify third molar development on MRI and to apply it for age estimation.

AIM

To develop a specific staging technique to register third molar development on MRI and to evaluate its performance for age estimation in subadults.

MATERIALS AND METHODS

Using 3T MRI in three planes, all third molars were evaluated in 309 healthy Caucasian participants from 14 to 26 years old. According to the appearance of the developing third molars on MRI, descriptive criteria and schematic representations were established to define a specific staging technique. Two observers, with different levels of experience, staged all third molars independently with the developed technique. Intra- and inter-observer agreement were calculated. The data were imported in a Bayesian model for age estimation as described by Fieuws et al. (2016). This approach adequately handles correlation between age indicators and missing age indicators. It was used to calculate a point estimate and a prediction interval of the estimated age. Observed age minus predicted age was calculated, reflecting the error of the estimate.

RESULTS

One-hundred and sixty-six third molars were agenetic. Five percent (51/1096) of upper third molars and 7% (70/1044) of lower third molars were not assessable. Kappa for inter-observer agreement ranged from 0.76 to 0.80. For intra-observer agreement kappa ranged from 0.80 to 0.89. However, two stage differences between observers or between staging sessions occurred in up to 2.2% (20/899) of assessments, probably due to a learning effect. Using the Bayesian model for age estimation, a mean absolute error of 2.0 years in females and 1.7 years in males was obtained. Root mean squared error equalled 2.38 years and 2.06 years respectively. The performance to discern minors from adults was better for males than for females, with specificities of 96% and 73% respectively.

CONCLUSION

Age estimations based on the proposed staging method for third molars on MRI showed comparable reproducibility and performance as the established methods based on radiographs.

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.

The iliac crest in forensic age estimation: evaluation of three methods in pelvis X-rays

Age assessment in children and young adults is a relevant forensic issue. It is requested not only in evaluating criminal responsibility in youths without proper identification documents, often in relation to age thresholds, but also for release of a residency permit, and asylum seekers of minors. The analysis of the Risser sign and the iliac crest ossification process has been proposed as a useful tool for forensic age estimation. We evaluated the applicability of three different age estimation methods on a sample of 497 pelvic radiographs of Italian individuals between 10 and 25 years of age. Each method showed high reliability for both reproducibility and repeatability. The staging technique inspired by Kreitner and Kellinghaus methods (KK-MS) is easier than the Risser method in applicability, as it is not affected by the variations of ossification. We observed that all subjects who attained stage 3c of KK-MS and 5 of Risser Fr were >14 years, suggesting the benefits of these methods for that age threshold. The applicability of the area measurement method, inspired by Cameriere's approach, ranged between 12 and 20 years, but the statistical analysis showed only a moderate correlation with age. In order to evaluate the possible use of this approach it is therefore necessary to clarify and exclude external factors influencing the parameter. In conclusion, the iliac crest ossification is of interest in age estimation for forensic purposes. The evaluation of the pelvis X-ray, in addition to the other common dental and skeletal methods, could become a useful supplementary tool in age estimation for the 14 year threshold in order to fulfill forensic-level requirements.