Applicability of Cameriere European formula for age estimation of 10-15 years legal threshold in South Indian population

Comparison of accuracy of different dental age estimation methods in Finnish and Turkish populations

OBJECTIVE

The aims of this study were to assess the accuracy of Cameriere's and Demirjian's methods in Finnish children, and compare the findings with those of the Turkish children according to dental age.

MATERIAL AND METHODS

Dental panoramic tomography (DPT) of children (482 Finnish, 423 Turkish) aged between 5 and 15 years were evaluated. Comparison of mean difference between estimated and chronological age was evaluated. The difference between two means was analysed using paired t-test at 95% confidence interval (CI). Pearson correlation coefficients were used to estimate the correlation between chronological and estimated ages.  Results: Demirjian's method resulted in overestimation in all age groups except for 8-year-old girls. Dental age, however, was found to be underestimated with Cameriere's method in all age groups but 6-year-old girls and boys. In Northern Finnish children, Demirjian's method was more suitable for boys while Cameriere's method led to better estimation in girls. When comparing Finnish and Turkish children, differences between dental ages and chronological ages differed significantly in 10-year-old boys and 8-year-old girls with both methods.  Conclusion: Dental age of Turkish children seems higher than that of Finnish children. There is a significant difference between chronological and dental ages in both populations assessed by both methods.

An investigation of the validity of the Bedek models and Cameriere-European formula used in dental age prediction in Turkish children

BACKGROUND

Dental age estimation is one of the most reliable methods for determining age, commonly used for forensic, criminal, and anthropological purposes. The purpose of this study was to assess and compare the precision of the Bedek models and the Cameriere-European Formula (CF) in determinating dental age in a sample of Turkish individuals.

METHODS

Retrospective panoramic radiographs of 1018 subjects (497 boys and 521 girls) aged 5-14 years were evaluated using the Bedek models and the CF. The differences between calculated dental age (DA) and chronological age (CA) for each sex and age group were analyzed using the paired sample t-test and the Wilcoxon signed-rank test. The accuracy of the methods used to estimate dental age was determined by calculating the mean absolute error (MAE) based on the proximity of the dental age to the chronological age.

RESULTS

The CF method overestimated CA by 0.1 year in the entire sample. Conversely, the Bedek models tended to overestimate CA, with the three-, four-, and seven-tooth models exhibiting the most significant difference. There was a statistically significant difference between boys and girls in the DA-CA calculation using the CF method in the entire sample. Among the Bedek models, the three- and four-tooth models had the lowest MAE in the entire sample, while the single-tooth model had the highest MAE.

CONCLUSION

The CF method showed higher accuracy in predicting the age of children living in eastern Turkey compared to the Bedek Models.

Age determination on panoramic radiographs using the Kvaal method with the aid of artificial intelligence

OBJECTIVES

This study aimed to assess and compare age estimation on panoramic radiography using the Kvaal method and machine learning (ML).

METHODS AND MATERIALS

554 panoramic radiographs were selected from a Brazilian practice. To estimate age using the Kvaal method, the following measurements were performed on the upper left central incisors and canines: tooth, pulp and root length; root and pulp width at three different levels: at the enamel-cementum junction (ECJ); midpoint between the enamel-cementum junction and; at the mid root level. For ML age estimation, radiomic, semantic and the radiomic-semantic attribute extractions were assessed. Nineteen semantic and 14 radiomic attributes and a single set of 33 semantic-radiomic attributes were extracted. Logistic Regression, Linear Regression, KNN, SVR, Decision Tree Reg, Random Forest Reg, Gradient Boost Reg e XG Boosting Reg were used for ML classification. For the Kvaal method, Mann-Whitney test, Spearman correlation coefficient, Student's t-test and linear regression with its respective coefficient of determination were used to estimate age and to assess data variability.

RESULTS

Mean absolute error (MAE) and standard error estimate (SEE) were assessed. For the Kvaal method, upper incisors presented higher precision than canines (R²: 0.335, SSE: 7.108). Males presented better MAE and SEE values (5.29,6.96) than females (5.69,7.37). The radiomic-semantic attributes presented superior precision (MAE: 4.77) than the radiomic and semantic (MAE: 5.23) attributes. The XG Boosting Reg classifier performed better than the other six assessed classifiers (MAE: 4.65). ML (MAE: 4.77 presented higher age estimation precision than the Kvaal method (MAE: 5.68).

CONCLUSION

The use of ML on panoramic radiographs can improve age estimation.

Age estimation of children based on open apex measurement in the developing permanent dentition: an Egyptian formula

Background

Cameriere’s original formula based on open apex measurements is a reliable, clinically applicable method for dental age estimation in different populations children. Dental development may differ between Egyptian children and other ethnic populations which may affect dental age accuracy using Cameriere’s formula.

Aim

Firstly, to verify Cameriere’s original formula on large Egyptian children sample, secondly, to develop an Egyptian-specific formula based on Cameriere’s method.

Material and methods

A prospective cross-sectional study of 762 good quality Orthopantomograms (OPGs) of 5–15 aged healthy Egyptian children selected from Nile Delta governorates between August 2020 and December 2021. Chronological age (CA) was calculated by subtracting birth date from radiograph date. OPGs were analyzed for N0, S, Xi morphologic variables using Sidexis program after that dental age was calculated using Cameriere’s formula then compared to CA. Multiple linear regression model was used to adapt Cameriere’s formula to construct an Egyptian formula. The same sample was used to verify the new formula accuracy.

Results

A total of 1093 OPGs were collected; 762 OPGs which met inclusion criteria were analyzed. Cameriere’s original formula revealed − 0.59- and − 0.53-year underestimation of females and males dental age (DA) respectively (p < 0.001). Regression analysis using the morphologic variables showed that X4, X7, N0 contributed significantly to CA yielding Egyptian-specific formula. New formula showed − 0.12-year male underestimation and 0.1-year female overestimation (p > 0.05).

Conclusion

Egyptian formula was more accurate than Cameriere’s formula in Egyptian children.

Clinical relevance

Egyptian-specific formula decreases the gap between CA and DA, so a relative approximate age is obtained that helps proper diagnosis and treatment planning for orthodontic and pediatric dentistry problems.

Conditional Uncorrelation and Efficient Subset Selection in Sparse Regression

Given m d -dimensional responsors and n d -dimensional predictors, sparse regression finds at most k predictors for each responsor for linear approximation, 1 ≤ k ≤ d-1 . The key problem in sparse regression is subset selection, which usually suffers from high computational cost. In recent years, many improved approximate methods of subset selection have been published. However, less attention has been paid to the nonapproximate method of subset selection, which is very necessary for many questions in data analysis. Here, we consider sparse regression from the view of correlation and propose the formula of conditional uncorrelation. Then, an efficient nonapproximate method of subset selection is proposed in which we do not need to calculate any coefficients in the regression equation for candidate predictors. By the proposed method, the computational complexity is reduced from O([1/6]k³+(m+1)k²+mkd) to O([1/6]k³+[1/2](m+1)k²) for each candidate subset in sparse regression. Because the dimension d is generally the number of observations or experiments and large enough, the proposed method can greatly improve the efficiency of nonapproximate subset selection. We also apply the proposed method in real scenarios of dental age assessment and sparse coding to validate the efficiency of the proposed method.

The Application of the Cameriere's Methodologies for Dental Age Estimation in a Select KwaZulu-Natal Population of South Africa

Background: The estimation of an individual’s age is a fundamental component of forensic odontology. Literary reports found that the efficiency of Cameriere methodology for age estimation varied among many population groups. Therefore, this study aimed to determine the applicability of the Cameriere methods to a select South African population of the KwaZulu-Natal (KZN) province. Materials and Methods: This cross-sectional retrospective study was conducted on 840 digital panoramic radiographs that met the inclusion criteria. Dental maturity was determined through the morphometric analysis of the seven left permanent mandibular and maxillary teeth in accordance with Cameriere et al. (2006). Moreover, the dental age was also calculated using the South African Black Bayesian formulae of the Cameriere method by Angelakopoulos et al. (2019). The paired sample t-test or Wilcoxon’s signed rank test assessed the significant difference between the chronological age and estimated dental age for the various formulae. A p-value < 0.05 was considered to be statistically significant. Results: The Cameriere et al. (2006) Italian formula and the South African Black Bayesian formulae of the Cameriere method by Angelakopoulos et al. (2019) underestimated and overestimated age in the South African Black and Indian population groups of the KZN province, respectively. Therefore, the authors generated a novel population-specific regression formulae (including and excluding third molars) using “step-wise regression analysis” and a “best-fit model” for the South African Black and Indian population groups of KZN. Conclusion: This study recommends that the population-specific formulae generated in this study be utilized in the KZN population to improve the accuracy of dental age estimation within this region.

[Accuracy of the Cameriere's method and its variant the European Formula for age estimation in subadult peruvian population]

Objective

To determine the accuracy of the Cameriere method and its variant, the European Formula, in a sub-adult Peruvian population; and determine a chronological age predictor equation.

Materials and methods

Descriptive, observational, cross-sectional and retrospective study. It was used 257 digital panoramic radiographs of patients in mixed dentition from 5 to 12 years of age belonging to the "Dental Cientifica" Dental Center of the Universidad Cientifica del Sur in the city of Lima, Peru. All morphological variables and gender of the subjects were used as predictor variables for age estimation. To evaluate the accuracy of each estimation method, the age of each individual was compared with the estimated age using the mean prediction error. Multiple linear regression was used to generate the predictive equation for chronological age.

Results

It was found that the mean prediction error between the chronological age with respect to the age estimated by the Cameriere method Formula and the European Formula was 0.73±0.55 years and 0.77±0.57 years, respectively. A model was generated whose predictor variables for age were s and N0, both variables were statistically significant and the Adjusted R2 for the number of variables was 75.96%.

Conclusion

It was determined that Cameriere's Formula was more accurate than the European Formula; however, there was no statistically significant difference between the two. Additionally, it was possible to establish a specific linear regression formula for a Peruvian population aged 5 to 12 years with an adequate predictive capacity.

Presence and Maturation Dynamics of Mandibular Third Molars and Their Influence on Late Mandibular Incisor Crowding: A Longitudinal Study

The objective of this study was to investigate the relationship between the absence, presence and dynamics of mandibular third molar development and the occurrence and amount of late mandibular incisor crowding. Dental plaster casts and panoramic radiographs of 72 orthodontically untreated subjects from the Nittedal growth study, Norway were analyzed. The subjects were recalled for a checkup at 12, 15, 18 and 21 years of age. Mandibular incisor crowding was assessed using Little's irregularity index and dental maturation of the third molars by the Cameriere's index. The majority of the subjects (64%) had ≥1 mm increase in irregularity; 22% experienced an increase of 0.1-0.9 mm and 14% had unchanged or decreased irregularity. Incisor irregularity increased with age, regardless of absence or presence of third molars. The amount of change in incisor irregularity from 12 to 21 years did not differ significantly between subjects with hypodontia of third molars, extraction and those with third molars present. No differences were observed between erupted, unerupted or impacted third molars. No correlation was found between the amount of change in irregularity and maturation of the third molars. In conclusion, occurrence and amount of mandibular late incisor crowding is not significantly influenced by the presence of mandibular third molars or their development dynamics.

Age Estimation Using the Cameriere Methods of Open Apices: A Meta-Analysis

PURPOSE

To evaluate the actual variability of the mean difference between chronological and dental age using the Cameriere method of open apices and to test its accuracy in variable age groups.

METHOD

We selected studies that contained data about the mean, standard deviation, and number of cases for chronological age, dental age and gender. We used a random-effects model. Statistical significance was estimated, at a p < 0.05, using prediction intervals. For the analysis of publication bias we used the funnel plot and Egger's regression test for plot asymmetry. I2 was used to test the presence of heterogeneity between studies. The Z test was used to test for statistical differences between subgroups, with p < 0.05 being considered statistically significant. We also used 95% for confidence intervals and prediction intervals.

RESULTS

In boys, the average difference between chronological and dental age was 0.44 (0.26-0.63) years, while in girls the average difference between chronological and dental age was 0.34 (0.19-0.49) years. In the 6-7 years age group and in the 14-15 years age group, there was a statistically significant difference between dental and chronological age. Our study shows that the Cameriere method is useful for estimating the chronological age, with errors of less than one year.

CONCLUSIONS

The Cameriere method of evaluating dental age using open apices is sufficiently accurate for forensic practice, at least in the 7-14 age-interval.