Population-specific dental maturity scores for forensic age estimation in turkish children: a percentile-based modeling approach.

Accurate age estimation in children and adolescents is essential for forensic identification; however, the direct application of dental age estimation methods developed from Western European populations may introduce systematic bias when applied to other populations. This study aimed to develop and validate population-specific age estimation models based on the Dental Maturity Score (DMS) using data obtained from Turkish children. A total of 4,009 panoramic radiographs from individuals aged 2-18 years (2,035 males and 1,974 females) were included. Of these, 3,206 individuals constituted the model development (training) cohort and 803 the independent validation (test) cohort. The seven left permanent mandibular teeth were assessed according to the Demirjian staging system, and sex-specific DMSs were calculated. The relationship between chronological age and DMS was modeled using moving average, Locally Weighted Scatterplot Smoothing (LOWESS), the Lambda-Mu-Sigma (LMS) method, piecewise polynomial regression, and polynomial- and spline-based quantile regression. Model performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), and Bland-Altman agreement analysis. Among the evaluated approaches, the polynomial- and spline-based quantile regression models demonstrated the best overall performance. In the independent validation cohort, the polynomial-based quantile regression model achieved an R² of 0.94 and an MAE of 0.75 years in males, and an R² of 0.92 and an MAE of 1.09 years in females. Among the population-specific models developed for Turkish children, the polynomial-based quantile regression model demonstrated the highest predictive accuracy and consistent performance in the independent validation cohort, indicating that it is a suitable approach for forensic age estimation. In contrast, the spline-based quantile regression model provides a useful reference framework for the clinical assessment of dental development.