New models for age estimation and assessment of their accuracy using developing mandibular third molar teeth in a Thai population

Radiologic assessment of third molar development and cervical vertebral maturation to validate age of majority in a Mexican population

An increase in irregular migration flows has further raised the importance of age estimation in forensic science. To improve the reliability of age of majority determination, one recommendation is to combine the evaluation of third molar development with age-related skeletal information. In the present study, we assessed mandibular third molar development and cervical vertebral maturation to evaluate the ability of these age indicators, alone and in combination, to accurately identify individuals 18 years of age or older. The study sample comprised 123 multi-slice computed tomography images of Mexican individuals (67 males and 56 females) aged between 14 and 22 years. Demirjian's stages of tooth development and Baccetti's stages of vertebral maturation were used. A fully developed mandibular third molar (stage H) indicated adult age with 100% certainty. However, around 70% of individuals older than 18 years had third molars that had not yet completed their development. Thus, immature third molars do not rule out the possibility that an individual has reached the age of majority. In the study sample, the combination of the maturity stages of teeth 38 and 48 or their combination with the cervical stages of maturation did not improve upon the prediction accuracy of either of the mandibular third molars alone (area under the ROC curve > 0.85). Therefore, these findings highlight the need to identify other complementary age estimation methods that minimize the number of false negatives (i.e., adults classified as minors) obtained with assessment of third molar development alone.

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.

Dental age estimation in Indonesian adults: An investigation of the maxillary canine pulp-to-tooth volume ratio using cone-beam computed tomography

Purpose

This study was performed to develop a linear regression model using the pulp-to-tooth volume ratio (PTVR) ratio of the maxillary canine, assessed through cone-beam computed tomography (CBCT) images, to predict chronological age (CA) in Indonesian adults.

Materials and Methods

A sample of 99 maxillary canines was collected from patients between 20 and 49.99 years old. These samples were obtained from CBCT scans taken at the Universitas Padjadjaran Dental Hospital in Indonesia between 2018 and 2022. Pulp volume (PV) and tooth volume (TV) were measured using ITK-SNAP, while PTVR was calculated from the PV/TV ratio. Using RStudio, a linear regression was performed to predict CA using PTVR. Additionally, correlation and observer agreement were assessed.

Results

The PTVR method demonstrated excellent reproducibility, and a significant correlation was found between the PTVR of the maxillary canine and CA (r=-0.74, P<0.01). The linear regression analysis showed an R2 of 0.58, a root mean square error of 5.85, and a mean absolute error of 4.31.

Conclusion

Linear regression using the PTVR can be effectively applied to predict CA in Indonesian adults between 20 and 49.99 years of age. As models of this type can be population-specific, recalibration for each population is encouraged. Additionally, future research should explore the use of other teeth, such as molars.

How old are you? A systematic review investigating the relationship between age and mandibular third molar maturity

INTRODUCTION AND OBJECTIVE

Radiographic evaluation of the maturity of mandibular third molars is a common method used for age estimation of adolescents and young adults. The aim of this systematic review was to examine the scientific base for the relationship between a fully matured mandibular third molar based on Demirjian's method and chronological age, in order to assess whether an individual is above or below the age of 18 years.

METHODS

The literature search was conducted in six databases until February 2022 for studies reporting data evaluating the tooth maturity using Demirjian´s method (specifically stage H) within populations ranging from 8 to 30 years (chronological age). Two reviewers screened the titles and abstracts identified through the search strategy independently. All studies of potential relevance according to the inclusion criteria were obtained in full text, after which they were assessed for inclusion by two independent reviewers. Any disagreement was resolved by a discussion. Two reviewers independently evaluated the risk of bias using the assessment tool QUADAS-2 and extracted the data from the studies with low or moderate risk of bias. Logistic regression was used to estimate the relationship between chronological age and proportion of subjects with a fully matured mandibular third molar (Demirjian´s tooth stage H).

RESULTS

A total of 15 studies with low or moderate risk of bias were included in the review. The studies were conducted in 13 countries and the chronological age of the investigated participants ranged from 3 to 27 years and the number of participants ranged between 208 and 5,769. Ten of the studies presented the results as mean age per Demirjian´s tooth stage H, but only five studies showed the distribution of developmental stages according to validated age. The proportion of subjects with a mandibular tooth in Demirjian´s tooth stage H at 18 years ranged from 0% to 22% among males and 0 to 16% in females. Since the studies were too heterogenous to perform a meta-analysis or a meaningful narrative review, we decided to refrain from a GRADE assessment.

CONCLUSION

The identified literature does not provide scientific evidence for the relationship between Demirjian´s stage H of a mandibular third molar and chronologic age in order to assess if an individual is under or above the age of 18 years.

Fully automated method for dental age estimation using the ACF detector and deep learning

Background

Dental age estimation plays an important role in identifying an unknown person. In forensic science, estimating age with high accuracy depends on the experience of the practitioner. Previous studies proposed classification of tooth development of the mandibular third molar by following Demirjian’s method, which is useful for dental age estimation. Although stage of tooth growth is very helpful in assessing age estimation, it must be performed manually. The drawback of this procedure is its need for skilled observers to carry out the tasks precisely and reproducibly because it is quite detailed. Therefore, this research aimed to apply computer-aid methods for reducing time and subjectivity in dental age estimation by using dental panoramic images based on Demirjian’s method. Dental panoramic images were collected from persons aged 15 to 23 years old. In accordance with Demirjian’s method, this study focused only on stages D to H of tooth development, which were discovered in the 15- to 23-year age range. The aggregate channel features detector was applied automatically to localize and crop only the lower left mandibular third molar in panoramic images. Then, the convolutional neural network model was applied to classify cropped images into D to H stages. Finally, the classified stages were used to estimate dental age.

Results

Experimental results showed that the proposed method in this study can localize the lower left mandibular third molar automatically with 99.5% accuracy, and training in the convolutional neural network model can achieve 83.25% classification accuracy using the transfer learning strategy with the Resnet50 network.

Conclusion

In this work, the aggregate channel features detector and convolutional neural network model were applied to localize a specific tooth in a panoramic image and identify the developmental stages automatically in order to estimate the age of the subjects. The proposed method can be applied in clinical practice as a tool that helps clinicians to reduce the time and subjectivity for dental age estimation.

Chronological Age Assessment Based on the Root Pulp Visibility in Lower Third Molars in a Group of Thai Population: Panoramic Radiographic Study

Background:

Radiographic visibility of the root pulp in lower third molars is one of the reliable methodologies for chronological age estimation.

Objective:

To evaluate the radiographic visibility of the lower third molar root pulp using digital panoramic radiographs of the Thai population, and determine the appropriation of this technique in age assessment, especially at the age of 18 years.

Methods:

A total of 746 digital panoramic radiographs of the Thai population aged from 16 to 26 years were recruited for the present study. The visibility of root pulp of lower third molars with completed root formation was recorded in the four stages. Descriptive statistics were performed for each stage in both males and females.

Results:

The first appearance of stage 0 is 16.71 years in males and 17.00 years in females. The minimum age of stage 1 was found at 17.08 years in males and 17.18 years in females. The beginning of stage 2 was 18.33 years in males and 18.17 years in females. For stage 3, the earliest presence was started at 18.58 years in males and 18.83 years in females.

Conclusion:

The occurrence of stages 2 or 3 in both males and females indicated that the subject is over 18 years of age. Further study on the Thai population should be conducted to confirm the results of the present study.

Age estimation using third molar maturation based on Demirjian's criteria

Dental age estimation is routinely used in human identification, in both the living and the dead. Teeth follow a predictable pattern of eruption and maturation that can be assessed radiographically in the living, allowing experts to estimate an individual's age. Third molars develop much later than the other permanent teeth, and can be used to estimate age of individuals nearing the age of maturity. Ability of third molar maturation when graded using Demirjian's method in ascertaining whether an individual has attained the medicolegal ages of 16 and 18 years has not yet been verified. The present study involved assessing the third molar maturation of 220 individuals of a training set using Demirjian's scoring system, generating regression models to estimate age using the third molar maturity scores, applying these models on a test set of 40 individuals, and calculating the mean difference (MD) and the mean absolute error (MAE) between the chronological and estimated ages of the test set participants. It was observed that the lowest mean difference and mean absolute error was observed for the maturation of the left mandibular third molar (MD = 1.05 years, MAE = 2.09 years). Boxplots generated in the study report that the third molar maturation stages given by Demirjian can identify whether an individual has attained the medicolegally significant ages of 16 and 18 years of age.

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.

Comparison of different machine learning approaches to predict dental age using Demirjian's staging approach

CONTEXT

Dental age, one of the indicators of biological age, is inferred by radiological methods. Two of the most commonly used methods are using Demirjian's radiographic stages of permanent teeth excluding the third molar (Demirjian's and Willems' method). The major drawbacks of these methods are that they are based on population-specific conversion tables and may tend to over- or underestimate dental age in other populations. Machine learning (ML) methods make it possible to create complex data schemas more simply while keeping the same annotation system. The objectives of this study are to compare (1) the capacity of ten machine learning algorithms to predict dental age in children using the seven left permanent mandibular teeth compared to reference methods and (2) the capacity of ten machine learning algorithms to predict dental age from childhood to young adulthood using the seven left permanent mandibular teeth and the four third molars.

METHODS

Using a large radiological database of 3605 orthopantomograms (1734 females and 1871 males) of healthy French patients aged between 2 and 24 years, seven left permanent mandibular teeth and the 4 third molars were assessed using Demirjian's stages. Dental age estimation was then performed using Demirjian's reference method and various ML regression methods. Two analyses were performed: with the 7 left mandibular teeth without third molars for the under 16 age group and with the third molars for the entire study population. The different methods were compared using mean error, mean absolute error, root mean square error as metrics, and the Bland-Altman graph.

RESULTS

All ML methods had a mean absolute error (MAE) under 0.811 years. With Demirjian's and Willems' methods, the MAE was 1.107 and 0.927 years, respectively. Except for the Bayesian ridge regression that gives poorer accuracy, there was no statistical difference between all ML tested.

CONCLUSION

Compared to the two reference methods, all the ML methods based on the maturation stages defined by Demirjian were more accurate in estimating dental age. These results support the use of ML algorithms instead of using standard population tables.

Age estimation in three distinct east Asian population groups using southern Han Chinese dental reference dataset

Background

Dental age estimation can assist in the identification of victims following natural disasters and it can also help to solve birth date disputes in individuals involved in criminal activities. A reference dataset (RDS) has been developed from the dental development of 2306 subjects of southern Han Chinese origin and subsequently validated. This study aimed to test the applicability of the southern Han Chinese dental maturation RDS on three distinct East Asian population groups.

Methods

A total of 953 dental panoramic radiographs of subjects aged 2 to 24 years were obtained from Philippines, Thailand and Japan. The staging of dental development was conducted according to Anglo-Canadian classification system. The dental age (DA) was calculated using six methods; one un-weighted average and five weighted average (n-tds, sd-tds, se-tds, 1/sd-tds, 1/se-tds) methods based on the scores of the southern Han Chinese RDS. Statistical significance was set at p < 0.05 and the variation between chronological age (CA) and DA was evaluated using paired t-test and Bland & Altman scatter plots.

Results

From six dental age calculations, all methods of DA accurately estimated the age of Japanese and few methods in Filipino subjects (n-tds, 1/sd-tds, 1/se-tds). There was consistent overestimation of age for all the methods for Thai females (p < 0.05).

Conclusions

The southern Han Chinese dental reference dataset was shown to be most accurate for Japanese, followed by Thai males and it was particularly ineffective for Filipinos and Thai females.

Age assessment in the living using modified Gustafson's criteria in a northern Chinese population

Regressive dental changes appear to be suitable for age assessment in living adults. In 2012, Olze et al. showed that several criteria presented by Gustafson for extracted teeth can also be applied to orthopantomograms. The objective of this study was to test the applicability and reliability of this method in a Chinese population. For this purpose, 1300 orthopantomograms of 650 female and 650 male Chinese aged between 15 and 40 years were evaluated. The characteristics of secondary dentin formation, periodontal recession, attrition, and cementum apposition were reviewed in all the mandibular premolars. The sample was split into a training and test dataset. Based on the training set, the correlation of the individual characteristics with chronological age was studied with a stepwise multiple regression analysis, in which individual characteristics formed the independent variable. According to the results, the R values amounted to 0.80 to 0.83; the standard error of estimate was 4.29 to 4.75 years. By analyzing the test dataset, the accuracy of the present study, Olze's and Timme's formulas were determined by the difference between the estimated dental age (DA) and chronological age (CA). Taking both mean differences and mean absolute differences into account, the Chinese age estimation formula did not always perform better compared with Olze's and Timme's formulas for both males and females. It was concluded that this method can be used in Chinese individuals for age assessment. However, the applicability of the method is limited by the quality of the X-ray images, and the method should only be applied by experienced forensic odontologists.

A systematic review and meta-analysis of the fully formed wisdom tooth as a radiological marker of adulthood

Assessment of third molar development on dental radiograms is one of the most commonly used methods of forensic age estimation. Despite widespread use and numerous studies, there is a paucity of aggregated data on how well a fully mature third molar identifies adulthood (> 18 years), the most important threshold in a medicolegal context. Therefore, a systematic review and meta-analysis was conducted. A total of 1229 studies were screened, and 82 studies were assessed for inclusion. Twenty-four studies, with a pooled cohort of 19,690 individuals, presented true positive (TP), true negative (TN), false positive (FP), and false negative (FN) outcomes, enabling meta-analysis. The outcomes were based on using the third molar in the fully mature stage as a diagnostic test to indicate age 18 years or above. The false positive rate (fall-out/1-specificity) was 3.1% (95% CI 2.1-4.6%), and the true positive rate (recall/sensitivity) was 51% (95% CI 44-58%). Diagnostic accuracy was 71%. These findings, while reassuring in terms of the low false positive rate, highlight the need for complementary age estimation methods to avoid a significant number of false negatives.

Third molar mineralization in relation to chronologic age estimation of the Han in central southern China

The purpose of this study is to provide a forensic reference data about estimating chronologic age by evaluating the third molar mineralization of Han in central southern China. The mineralization degree of third molars was assessed by Demirjian's classification with modification for 2519 digital orthopantomograms (1190 males, 1329 females; age 8-23 years). The mean ages of the initial mineralization and the crown completion of third molars were around 9.66 and 13.88 years old in males and 9.52 and 14.09 years old in females. The minimum ages of apical closure were around 16 years in both sexes. Twenty-eight at stage C and stage G and 38 and 48 at stage F occurred earlier in males than in females. There was no significant difference between maxillary and mandibular teeth in males and females except that stage C in males. Two formulas were devised to estimate age based on mineralization stages and sexes. In Hunan Province, the person will probably be over age 14, when a third molar reaches the stage G. The results of the study could provide reference for age estimation in forensic cases and clinical dentistry.