BACKGROUND: This study aims to evaluate the performance of a deep learning system for the evaluation of tooth development stages on images obtained from panoramic radiographs from child patients.
METHODS: The study collected a total of 1500 images obtained from panoramic radiographs from child patients between the ages of 5 and 14 years. YOLOv5, a convolutional neural network (CNN)-based object detection model, was used to automatically detect the calcification states of teeth. Images obtained from panoramic radiographs from child patients were trained and tested in the YOLOv5 algorithm. True-positive (TP), false-positive (FP), and false-negative (FN) ratios were calculated. A confusion matrix was used to evaluate the performance of the model.
RESULTS: Among the 146 test group images with 1022 labels, there were 828 TPs, 308 FPs, and 1 FN. The sensitivity, precision, and F1-score values of the detection model of the tooth stage development model were 0.99, 0.72, and 0.84, respectively.
CONCLUSIONS: In conclusion, utilizing a deep learning-based approach for the detection of dental development on pediatric panoramic radiographs may facilitate a precise evaluation of the chronological correlation between tooth development stages and age. This can help clinicians make treatment decisions and aid dentists in finding more accurate treatment options.

Background: The stage of tooth formation is one of the most reliable indicators for predicting a patient\'s developmental age by radiographs. This study compared the accuracy of three distinct dental age estimation methods (Demirjian, Nolla, and Willems) in children aged 3-17 in the northern Iranian population. Methods: This cross-sectional study examined panoramic radiographs of 434 children aged 3-17 from Mazandaran Province, Iran, who had teeth 31-37 present on the left mandible. This study employed the Demirjian, Nolla, and Willems methods to estimate the dental age of the sample and compare it with the chronological age. The data were analyzed using SPSS v16. A paired t-test was used to compare chronological and dental ages. The Pearson correlation was used to correlate the chronological and dental ages. The errors of different methods were compared using the Wilcoxon test. P values < 0.05 were considered significant for all tests except Wilcoxon. For Wilcoxon, a P value < 0.017 was considered significant. Results: The three methods presented differing mean estimated ages. The Demirjian method delivered the highest mean, and all three methods differed significantly when compared in pairs. The results showed that the Demirjian method overestimated chronological age by 0.25 years (P < 0.001) in girls and 0.09 years (P = 0.28) in boys. The Willems method underestimated chronological age by 0.05 years (P = 0.47) in girls and 0.12 years (P = 0.13) in boys. The Nolla method underestimated chronological age by 0.41 years (P < 0.001) in girls and 0.40 years (P < 0.001) in boys. The accuracy of each method varied with the patient\'s age. Conclusion: According to the findings, the Willems method outperformed the Demirjian method, and the Demirjian method exceeded the Nolla method for estimating dental age in Iranian children aged 3-17. Overall, the Demirjian method overestimated the age of the study population, whereas the other two underestimated it.

BACKGROUND: Dental development assessment is an important factor in dental age estimation and dental maturity evaluation. This study aimed to develop and evaluate the performance of an automated dental development staging system based on Demirjian\'s method using deep learning.
METHODS: The study included 5133 anonymous panoramic radiographs obtained from the Department of Pediatric Dentistry database at Seoul National University Dental Hospital between 2020 and 2021. The proposed methodology involves a three-step procedure for dental staging: detection, segmentation, and classification. The panoramic data were randomly divided into training and validating sets (8:2), and YOLOv5, U-Net, and EfficientNet were trained and employed for each stage. The models\' performance, along with the Grad-CAM analysis of EfficientNet, was evaluated.
RESULTS: The mean average precision (mAP) was 0.995 for detection, and the segmentation achieved an accuracy of 0.978. The classification performance showed F1 scores of 69.23, 80.67, 84.97, and 90.81 for the Incisor, Canine, Premolar, and Molar models, respectively. In the Grad-CAM analysis, the classification model focused on the apical portion of the developing tooth, a crucial feature for staging according to Demirjian\'s method.
CONCLUSIONS: These results indicate that the proposed deep learning approach for automated dental staging can serve as a supportive tool for dentists, facilitating rapid and objective dental age estimation and dental maturity evaluation.

The aim of this study was to determine whether the relationship between dental age (DA), cervical stage (CS) and chronological age (CA) in Chinese male children with unilateral cleft lip and palate (UCLP) is similar to that of children without clefts. Panoramic and cephalometric radiographs of 105 male UCLP patients, aged from 8 to 16 years, were collected and compared to 210 age-matched healthy control males. The Demirjian and cervical vertebral maturation (CVM) methods were used to visually examine the radiographs and Spearman\'s correlation analysis was used to identify differences between the two groups with regards to CS, DA and CA. There was a significant positive correlation between DA and CA in both groups and the mean CA-DA difference was significantly higher in children with UCLP when compared to controls (0.319 vs. 0.003, p < 0.05). A significant delay in tooth development was detected in UCLP children from 10 to 12 years-of-age. Both the UCLP and control groups showed high correlations between CS and DA. Calcification stage D appeared only before CS3; however, from CS5 to 6, all teeth have almost completed their maturation phase. Chinese male UCLP patients are likely to experience delayed tooth development compared to healthy controls, especially during the fast-growing period. Evaluating the stages of tooth mineralization could represent a rapid method to assess growth potential.

BACKGROUND: The correlation between dental maturity and skeletal maturity has been proposed, but its clinical application remains challenging. Moreover, the varying correlations observed in different studies indicate the necessity for research tailored to specific populations.
OBJECTIVE: To compare skeletal maturity in Korean children with advanced and delayed dental maturity using dental maturity percentile.
METHODS: Dental panoramic radiographs and cephalometric radiographs were obtained from 5133 and 395 healthy Korean children aged between 4 and 16 years old. Dental maturity was assessed with Demirjian\'s method, while skeletal maturity was assessed with the cervical vertebral maturation method. Standard percentile curves were developed through quantile regression. Advanced (93 boys and 110 girls) and delayed (92 boys and 100 girls) dental maturity groups were defined by the 50th percentile.
RESULTS: The advanced group showed earlier skeletal maturity in multiple cervical stages (CS) in both boys (CS 1, 2, 3, 4, and 6) and girls (CS 1, 3, 4, 5, and 6). Significant differences, as determined by Mann-Whitney U tests, were observed in CS 1 for boys (p = 0.004) and in CS 4 for girls (p = 0.037). High Spearman correlation coefficients between dental maturity and cervical vertebral maturity exceeded 0.826 (p = 0.000) in all groups.
CONCLUSIONS: A correlation between dental and skeletal maturity, as well as advanced skeletal maturity in the advanced dental maturity group, was observed. Using percentile curves to determine dental maturity may aid in assessing skeletal maturity, with potential applications in orthodontic diagnosis and treatment planning.

BACKGROUND: The notion that \"age is just a number\" is sometimes expressed colloquially; however, within the domains of medicine and dentistry, age is not only a numerical value. Rather, it has significant importance in several facets of diagnosis and treatment planning. Demonstrating one\'s identity is necessary not only in the aftermath of natural calamities or mishaps but also in the context of forensic examination of living persons. Age assessment is a very important tool in forensic odontology and plays a vital role in various fields, including medico-legal matters. The primary focus of the current investigation is to assess the precision and correctness of the data and reliability of Demirjian\'s method (DM) and Willems\' method (WM) for age estimation (AE) among the population of Saudi Arabia.
METHODS: This research was conducted on 300 children from Saudi Arabia, aged seven to 13 years, including both males and females. The assessment of orthopantomography images involved the utilization of both Demirjian\'s and Willems\' methodologies for ascertaining dental age. This determined dental age was then meticulously juxtaposed with the chronological age (CA) of every participant. The data collected underwent a comprehensive statistical analysis, which encompassed the application of the paired t-test.
RESULTS: By using both methodologies, it was discovered that the estimated age (EA) exhibited higher values in both men and females compared to the CA. Both Willems\' and Demirjian\'s approaches yielded significantly different results in terms of statistical significance (p = 0.000 and p = 0.000, respectively), as shown by the comparison.
CONCLUSIONS: When comparing Willems\' technique to Demirjian\'s method, it was found that the population under research showed somewhat greater accuracy levels for AE. However, it is important to note that the disparity between these two approaches was relatively small. Consequently, it is imperative to emphasize the necessity for additional research involving a larger sample size to establish the validation of a more region-specific AE method tailored specifically for the Saudi Arabian population.

BACKGROUND: The dentition is one of the most accurate features for age estimation in children. However, there is some evidence that timing of dental development varies across populations. Recent research suggests that dental development may also be susceptible to influence by environmental factors, such as obesity. Given that there are also population differences in average body mass, it is possible that this may be a confounding variable that was not accounted for in prior work. We aim to compare the relative association between body mass index (BMI) and ancestry with timing of dental development.
METHODS: A retrospective cross-sectional chart review was undertaken using panoramic radiographs of 6- to 12-year-olds (n = 281). Age, ancestry, sex, height, and weight were obtained. Dental development was assessed using the Demirjian method, and chronological age was subtracted from estimated dental age to determine relative timing of dental development (ΔAge). BMI was calculated based upon recorded height/weight within 6 months of time of radiograph.
RESULTS: We found no difference in timing of dental development (accelerated/delayed) across ancestry groups (African-American, Euro-American, Hispanic, Asian; P = .15). Overweight/obese subjects had statistically significantly advanced (precocious) dental development (P < .001). Compared to normal-weight subjects, children who were overweight\'s age were overestimated by 5.76 months (0.48 years) and children with obesity by 5.97 months (0.49 years) on average.
CONCLUSIONS: BMI appears to have a greater impact on relative timing of dental development than ancestry in this population. Our results support other findings that obesity results in accelerated growth and development.

UNASSIGNED: The chronological age (CA) of a patient does not always correspond to the events of growth surge; therefore treatment strategies need good knowledge of biological markers.
UNASSIGNED: The aim of the present study was to investigate the relationships between the skeletal age (SA), dental age (DA), and CA along with the stages of calcification of teeth and the cervical vertebral maturity (CVM) stages in Indian subjects.
UNASSIGNED: A sample of 100 pairs preexisting radiographs, both orthopantomogram and lateral cephalogram, of the individuals in the age-group of 8-15 years were procured and were analyzed for the level of dental and skeletal maturity using Demirjian scale and cervical vertebral maturity index, respectively.
UNASSIGNED: A high correlation coefficient (r) was found to be 0.839 (p = 0) between chronological and dental age (DA), 0.833 (p = 0) between chronological and skeletal age (SA), and 0.730 (p = 0) between skeletal and DA.
UNASSIGNED: The current research showed that the overall correlation between all three ages was found to be high. It was found that the SA assessed by the CVM stages had a high correlation with the CA.
UNASSIGNED: Within the limits of the present study, there exists a high degree of correlation between biological ages and chronological age, but still it is imperative for a correct assessment of biological age of individual patients for quality treatment outcomes.
UNASSIGNED: Gandhi K, Malhotra R, Datta G, et al. Treatment Predicament for Pediatric Dentist: Gender-wise Comparative Correlation of Biological and Chronological Age in 8-15-year-old Children. Int J Clin Pediatr Dent 2022;15(5):569-574.

Dental age estimation plays an important role in the field of clinic medicine and forensic medicine. The Demirjian and Nolla methods are common scoring methods for dental age estimation but there was no research about the comparison of accuracy of these two methods in northeastern Chinese children. Hence, in this study, we compared the accuracy of these two methods to explore more suitable method for our studied population. We collected 535 orthopantomograms from northern Chinese children aged from 6 to 15 years and divided them into training dataset and testing dataset according to the ratio of 7:3. The dental age of training dataset were estimated using Demirjian and Nolla methods, respectively. The results suggested that the mean differences of these two methods were 0.24 and -0.40 years, and mean absolute difference were 0.65 and 0.59 years. Then to further improve the accuracy of dental age assessment, the new improved formulas and dental age conversion tables were established after analyzing the relationship between the sum scores based on Nolla method and chronology age in training dataset. According to the new method used in testing dataset, the minimum value of mean difference (0.00) and mean absolute difference (0.49) were obtained, which are largely smaller than that of Demirjian and Nolla methods. The new developed method and dental age conversion scales may be more suitable dental age estimation method for northeastern Chinese children.

Estimation of children\'s chronological age is highly important in human and forensic sciences. The Demirjian method has been reported as accurate for this purpose. The literature review shows some evidence that the accuracy of estimating chronological age via the Demirjian standards is not a straightforward process. The objective of this research is to analyze the reliability of the Demirjian standards in Portuguese and Spanish children and adolescents and adapt it to include sex and group age as contingent factors.
Orthopantomographs of 574 Portuguese and Spanish male and female children and adolescents were employed to test the reliability of the Demirjian method. After testing for inter-rater consistency and age estimation using the Demirjian standards, multiple regression analysis was performed controlling for sex and age group.
The Demirjian standards overestimated chronological age for both sexes, mainly for females. Through the development of regression functions, more detailed dental age estimation was performed. The predictive capacities of the Demirjian method and the significant teeth varied as a function of children\'s age. The Demirjian global standard predicted over 65% of the variance of the chronological age. Taking a tooth-by-tooth approach, the predictive ability increased by over 70%.
The accuracy of estimating chronological age via the Demirjian method is not as reliable as it might appear, judging from the results found according to age group and according to sex crossed with age group.