CBCT in dental age estimation: A systematic review and meta analysis

Objectives: This study aimed to investigate the reproducibility of dental age estimation methods in cone beam computed tomography (CBCT) and the correlation between dental (DA) and chronological (CA) ages. Methods: The scientific literature was searched in six databases (PubMed, Scopus, LILACS, Web of Science, SciELO, and OATD). Only observational studies were selected. Within each study, the outcomes of interest were (I) the quantified reproducibility of the method (κ statistics and Intraclass correlation coefficient); and (II) the correlation (r) between the dental and chronological ages. A random-effect three-level meta-analysis was conducted alongside moderator analysis based on methods, arch (maxillary/mandibular), population, and number of roots. Results: From 671 studies, 39 fulfilled the inclusion criteria, with one study reporting two different methods. The methods used in the studies were divided into metric (n = 17), volumetric (n = 20), staging (n = 2), and atlas (n = 1). All studies reported high examiner reproducibility. Group 1 (metric and volumetric) provided a high inverse weighted r ([Formula: see text] = −0.71, CI [-0.79,–0.61]), and Group 2 (staging) provided a medium-weighted r ([Formula: see text] = 0.49, CI [0.44, 0.53]). Moderator analysis on Group one did not show statistically significant differences between methods, tooth position, arch, and number of roots. An exception was detected in the analysis based on population (Southeast Asia, [Formula: see text] = −0.89, CI [-0.94,–0.81]). Conclusion: There is high evidence that CBCT methods are reproducible and reliable in dental age estimation. Quantitative metric and volumetric analysis demonstrated better performance in predicting chronological age than staging. Future studies exploring population-specific variability for age estimation with metric and volumetric CBCT analysis may prove beneficial.

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 (R2), 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.

Evolution of dental age estimation methods in adults over the years from occlusal wear to more sophisticated recent techniques

Background Age estimation has been an integral part of forensic science, and age estimation by dental means is by far the most commonly employed method. Dental age estimation in children is more accurate and straightforward as most methods use the chronological stages of odontogenesis that are highly systematic, reducing the chances of dispersed results. In contrast, estimation of age in adults becomes tricky and less accurate with varied approaches since tooth formation is already complete. Main body The methods of adult dental age estimation have come a long way from a calculated guess based on crude visual observation of teeth to radiological methods and to more recent sophisticated methods. Technological advances have opened up molecular and genetic methods by utilizing DNA methylation and telomere length to improve the accuracy of age estimation by reducing error chances. Conclusions Although dental age estimation methods in children and adolescents have been extensively reviewed, various adult age estimation methods are not reviewed as a whole. The aim of this review is to appraise the evolution of dental age estimation methods in adults over the years from mere visualization of dental attrition to employing more sophisticated means such as radioactive carbon dating and genetics. This comprehensive review also attempts to add an account of the accuracy and suitability of various adult dental age estimation methods.

Age estimation by analysis of dental mineralization and its forensic contribution

Age is an important factor in the formation of the uniqueness of individuals. The procedure for assessing age in situations that cannot determine chronological age, especially in court cases, is mandatory. The literature presents different methods to estimate the age of individuals because civil and criminal majority at 18 years is a milestone in Brazil and other countries. Thus, age estimation through the analysis of dental mineralization stages is important, as it is rarely affected by exogenous or endogenous factors. This study evaluates different methods used to estimate age through dental mineralization and its forensic contribution. The following databases were used: PubMed, Medline, Scopus, Web of Science, and Google Scholar, using the descriptors "age estimation", "dental age estimation", and "forensic dentistry", both isolated and combined. It was verified the reliability of the analysis of dental mineralization stages for age estimation. Some of the methods used for this purpose have not been tested in Brazilian individuals. There are no up-to-date data on mineralization stages of permanent teeth for this population. Thus, current and specific data from the Brazilian population are required because the results to be obtained from new studies could benefit society, assisting the clarification of Justice in real-life situations.

Dental age estimation methods in children based on radiograph panoramic

Objectives: Age estimation is a key point in forensics, archeology, pediatrics and pediatric dentistry. Analysis using the development of teeth is one of the available methods that are used for physical identification, as well as age, in children. This article reviewed several journals about the methods of age identification, especially in children. The purpose of this review was to briefly inform about the recent researches regarding the application of age identification methods in children by using panoramic radiography as it is the most widely used method, in the years 2020-2021. Review: This article was a narrative review. Analyzed articles were searched from the PubMed database which were published between 2020 until 2021. There were 12 journals in accordance with the inclusion criteria of age estimation method in children using panoramic radiography. Conclusion: 7 of 12 journals that met the inclusion criteria used Willems method in the researches, 5 journals used Demirjian method, 3 journals used Cameriere method, 2 journals used Nolla method. Willems method was the most used analysis for identifying age and proved to be effective for identification in various populations, such as Belgium, Caucasian, Turkish, Saudi Arabian, Kenyan, Chinese and Taiwanese.

Age estimation accuracy based on Atlas London and Schour-Massler in Tionghoa ethnic children

Objectives: Age estimation is an important factor in forensic science and needs to be known accurately because it can narrow the search when examining unidentified victims, determine the victim's age at death and is also useful in cases of adulteration of athletes, child guardianship, or to determine whether someone is of legal age. or not according to the law. This study aims to determine individual age estimates based on the London Atlas and Schour-Massler Atlas and compare the accuracy of the two methods. Materials and Methods: 70 panoramic radiographs consisting of 31 boys and 39 girls from Chinese ethnicity in Surabaya, aged 6-13 years (72-156 months). Samples were determined for dental age based on the London Atlas and the Schour-Massler Atlas. The data that has been obtained is then processed by statistical analysis with SPSS for Windows, with an inclusion level of p <0.05. Results: This study showed that the London Atlas was better and more accurate than the Schour-Massler Atlas with a lower mean error and there was no significant difference between the London Atlas dental age estimation and chronological age with p value = 0.426 in the left region and p = 0.429 in the right region (p>0.05). Conclusion: The results obtained from this study indicate that dental development based on the London Atlas and Schour-Massler Atlas can be used as a method to determine the estimated age of children from the range of 6 - 13 years in ethnic Chinese.