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.

A Comparison of Demirjian and Cameriere Methods in Estimating Age and Development of a Modified Cameriere Method

Background: In recent years, age estimation in forensic medicine has become so important. Teeth are used to estimate age as valuable indicators. Objectives: This study aimed to compare Cameriere and Demirjian methods in estimating chronological age (Age) in an Iranian population and to develop a modified Cameriere method. Methods: In this cross-sectional study, we investigated a total of 486 panoramic radiographs of individuals aged 5 - 15 years adopted from two craniofacial radiology centers in Babol, northern Iran, in 2019. The dental age of subjects was assessed by Demirjian (DAge) and Cameriere (CAge) methods and compared with their chronological age. Also, a formula was designed based on the Cameriere method for our studied population, and the results of the original and modified Cameriere (MCAge) methods were compared. Results: The mean ± SD of Age (10.38 ± 2.30) had a significant difference with DAge (10.67 ± 2.33) and CAge (9.77 ± 2.01) (P < 0.001). The modified Cameriere formula was more accurate than Cameriere one, and MCAge was 10.38 ± 2.12, indicating no significant difference with Age (P = 0.993). Conclusions: According to our results, both Demirjian and Cameriere methods were not reliable for age estimation in the Iranian population. However, the modified Cameriere formula had a very high accuracy in estimating the age of the studied population.

Association between oral health status and type of motor function in children and adolescents with cerebral palsy

Objectives: The aim of the present study was to evaluate oral health and motor function in children and adolescents with cerebral palsy (CP) and determine the perception of caregivers regarding the oral health status of these individuals. Study Design: A cross-sectional study was conducted with 35 children/adolescents with CP and their caregivers. A questionnaire was administered to the caregivers addressing the oral health of the individuals with CP. The dmft/DMFT index, visible plaque index, malocclusion, dental age, pH, buffering capacity and flow salivary were determined. Motor function was evaluated using the GMFCS and GMFM-88 instruments. Results: A significant association was found between the GMFCS category and malocclusion. The GMFM-88 index was significantly lower in individuals with malocclusion and an altered dental age. Caregivers of quadriplegic individuals (57.1%), wheelchair users (42.9%) and those with more severe gross motor impairment (GMFM-88) reported more oral problems. Conclusion: Malocclusion and dental age were associated with motor function in children/adolescents with cerebral palsy. The caregivers of children and adolescents who are quadriplegic, use a wheelchair and have greater impairment regarding gross motor function reported more oral problems.

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.