A novel four-teeth model for dental age estimation: Reliability, validity, and comparative accuracy with a seven-teeth approach.

Abstract

Dental age estimation plays a critical role in forensic identification and legal age determination, particularly in children and adolescents. Although multi-tooth regression models demonstrate high predictive accuracy, their application may be restricted in situations involving incomplete dentition or suboptimal radiographic visualization. The present study aimed to develop and validate a simplified four-teeth model for dental age estimation and to compare its performance with established seven-teeth models. A cross-sectional study was conducted using 2000 panoramic radiographs of Indian children aged 5-16 yrs. Dental maturity was assessed using the normalized open apices method. A regression equation based on four mandibular posterior teeth (34, 35, 36, 37) was derived using stepwise multiple linear regression and validated on an test dataset (n = 500). Model performance was evaluated using coefficient of determination (R²), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE), and compared with Prabhu's population-specific and Cameriere's seven-teeth models. The four-teeth model demonstrated good predictive ability (R² = 69.6%, p < 0.0001), with an overall RMSE of 1.15 yrs and MAE of 0.95 yrs. The highest accuracy was observed in the 9-13 yrs age group (RMSE = 0.98 yrs), where performance was comparable to the seven-teeth models. Prediction error increased in the 13-16-yrs group (RMSE = 1.50 yrs), reflecting reduced discriminatory information following completion of root development. The model may therefore be useful as a simplified adjunct for dental age estimation primarily during the 5-13-yrs developmental period, in cases of incomplete dentition or compromised radiographic quality while external validation is required before broader forensic application.