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Multi-factorial age estimation: A Bayesian approach combining dental and skeletal magnetic resonance imaging
•Multi-factorial age estimation outperforms single site models in both sexes.•Anthropometric and sexual maturation data do not add relevant information to MRI.•Mean absolute error of age reached 1.41 years in females and 1.36 years in males.•Proportion of correctly classified minors reached 91% in females and 90% in males.
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.
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).
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.
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.
Journal Article
Bone age assessment with various machine learning techniques: A systematic literature review and meta-analysis
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.
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.
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.
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.
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.
Journal Article
Forensic age estimation for pelvic X-ray images using deep learning
PurposeTo 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 methodA 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.ResultsFor 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.ConclusionThe 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.
Journal Article
Age estimation in the living: A scoping review of population data for skeletal and dental methods
•Methods for age estimation in the living should be tested on different populations.•A scoping review on population data for age estimation methods was conducted.•Two hundred studies on the rate of skeletal maturation were found.•Four hundred thirty-nine studies on the rate of dental maturation were found.•For most of western and central African countries there are currently no population data.
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.
Journal Article
Estimation of dental age based on the developmental stages of permanent teeth in Japanese children and adolescents
Assessment of children’s growth and development based on general and oral developmental status and dental age is important in pediatric dentistry for appropriate diagnosis and treatment. Teeth are a useful maturation index because they are unlikely to be affected by exogenous factors such as disease. We examined the correlation between chronological and dental age of permanent teeth in Japanese children and adolescents using orthopantomography. The sample comprised 1024 orthopantomographs from individuals aged 3–18 years, which were stored in an electronic media database for 10 years (2009–2019). We classified the developmental stages of each permanent tooth were classified into 11 stages, clarified the dental age for each developmental stage, and prepared a conversion table. Using the results, we compared the sequence and rate of development of each permanent tooth. We clarified the dental age of each permanent tooth from childhood to mid-adolescence and established a method for calculating the dental age of the whole jaw that is appropriate for modern Japanese individuals. We found that girls tended to form teeth at a faster rate than boys until puberty, but boys caught up with girls after puberty, suggesting that secondary sexual characteristics are involved in the rate of tooth formation.
Journal Article
Machine learning assisted Cameriere method for dental age estimation
Background
Recently, the dental age estimation method developed by Cameriere has been widely recognized and accepted. Although machine learning (ML) methods can improve the accuracy of dental age estimation, no machine learning research exists on the use of the Cameriere dental age estimation method, making this research innovative and meaningful.
Aim
The purpose of this research is to use 7 lower left permanent teeth and three models [random forest (RF), support vector machine (SVM), and linear regression (LR)] based on the Cameriere method to predict children's dental age, and compare with the Cameriere age estimation.
Subjects and methods
This was a retrospective study that collected and analyzed orthopantomograms of 748 children (356 females and 392 males) aged 5–13 years. Data were randomly divided into training and test datasets in an 80–20% proportion for the ML algorithms. The procedure, starting with randomly creating new training and test datasets, was repeated 20 times. 7 permanent developing teeth on the left mandible (except wisdom teeth) were recorded using the Cameriere method. Then, the traditional Cameriere formula and three models (RF, SVM, and LR) were used to estimate the dental age. The age prediction accuracy was measured by five indicators: the coefficient of determination (R
2
), mean error (ME), root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE).
Results
The research showed that the ML models have better accuracy than the traditional Cameriere formula. The ME, MAE, MSE, and RMSE values of the SVM model (0.004, 0.489, 0.392, and 0.625, respectively) and the RF model (− 0.004, 0.495, 0.389, and 0.623, respectively) were lower with the highest accuracy. In contrast, the ME, MAE, MSE and RMSE of the European Cameriere formula were 0.592, 0.846, 0.755, and 0.869, respectively, and those of the Chinese Cameriere formula were 0.748, 0.812, 0.890 and 0.943, respectively.
Conclusions
Compared to the Cameriere formula, ML methods based on the Cameriere’s maturation stages were more accurate in estimating dental age. These results support the use of ML algorithms instead of the traditional Cameriere formula.
Journal Article
Developmental asymmetry of the clavicles and third molars and its implications for forensic age estimation
Age estimations are relevant for pre-trial detention and sentencing in criminal cases and as part of the evaluation in asylum processes to protect the rights and privileges of minors. No method can determine an exact chronological age due to individual variations in biological development. Current techniques assess skeletal or dental development and compare to reference populations. A key question is whether both sides of a body part need imaging, especially when asymmetric development occurs. This study evaluates whether bilateral imaging of the clavicles and third molars is necessary or if unilateral imaging suffices. We retrospectively analyzed clinical and radiological data from patients who underwent CT scans at Karolinska University Hospital, along with third molar data from studies using plain radiographs to assess development in relation to chronological age. The primary aim of this study is to examine the frequency of asymmetrical maturation in the medial clavicle and third molar in males and in females. The secondary aim was to examine how asymmetry influences age estimation in medico-legal contexts. To mitigate potential bias from relying on a single-reviewer assessment, we introduced a predefined level of misclassification into our model. Our findings show a strong correlation between right and left clavicle development (
ρ
= 0.871 (males) and
ρ
= 0.854 (females)) and near-perfect correlation (
ρ
= 0.980 (males) and
ρ
= 0.975 (females)) for third molars in both sexes. Asymmetrical development was found in approximately 23% (clavicle) and 13% (third molar) of males, and 20% and 17% of females, respectively. We recommend bilateral clavicle assessment to capture developmental variation and improve accuracy. For third molars, using the side with the most mature development in males and the least mature side in females enhances accuracy around the 18-year threshold.
Journal Article
Age determination in domestic dogs using cementum annuli: Validity and methodology
Age determination is an important part of forensic investigations and is used for assessment of population dynamics for animals and humans, understanding environmental conditions and so on. Age determinations using cementum annuli have been utilized for wild animals but have never been used for domestic dogs. The aim of this study was to test the accuracy of the method for domestic dogs and demonstrate the presence of cementum annuli. Ten domestic dogs were used for this experiment. The teeth were extracted from skulls via boiling and both mandibular and maxillary teeth were utilized. All teeth were decalcified using 10 % formic acid and 10 % formaldehyde solution. The decalcified teeth were embedded in paraffin and cut in 15 µm thickness. After staining with hematoxylin, the annuli were counted manually. The results obtained from this study suggest that domestic dogs indeed have cementum annuli and the annuli are countable, the number of annuli in teeth is compatible with the ages of animals, and canines of the same dogs show the same results meaning all canine teeth can be used for the age determination.
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•Cementum annuli method is effective, analyzing tooth growth rings like tree rings.•Counting cementum rings across multiple teeth improves accuracy in age estimates.•The method produces results for older animals that are difficult to achieve with other approaches.•Refining cementum annuli enhances precision in non-human forensic age determination.•The application of the cementum annuli count +1 formula in the estimation of age could lead to significant advancement in the field of veterinary medicine.
Journal Article
Age estimation using dental and hand-wrist radiography among a sample of Egyptian children
The current study aimed to evaluate the accuracy of Willems, Cameriere’s and Greulich and Pyle method in age estimation among a sample of Egyptian children aged 8–16 years based on analysis of 140 panoramic dental X-ray and hand-wrist radiographs (70 girls and 70 boys). Using Willems method, the mean dental age underestimated chronological age by (0.20 ± 0.91 years) for boys and by (0.24 ± 1.33 year) for girls; these differences were not statistically significant. Also, Cameriere’s method underestimated chronological age in both sexes by mean difference of (1.10 ± 1.22 year) in boys and (1.13 ± 1.31 year) in girls; these differences were statistically significant. Regarding Greulich and Pyle atlas, the mean of skeletal age was overestimated when compared to the real age in boys with a mean difference (0.04 ± 0.86 year). In girls; the age was underestimated by a mean difference of (0.15 ± 1.32 years) when compared to chronological age; these differences were not statistically significant. Comparing the two dental methods, the mean absolute error using Willems method was less than one year (0.94 and 0.96 years) in boys and girls respectively, while in Cameriere’s method, it was more than one year in both groups. Moreover; the mean absolute error using Greulich and Pyle atlas was less than two years (1.02 and 1.38 years) in boys and girls respectively. Since Willems and the atlas methods were more accurate, the combination of both of them could be used for age estimation in the Egyptian population.
Journal Article