Age estimation combining radiographic information of two dental and four skeletal predictors in children and subadults.

Improved age estimates may result from combining different age predictors. This study aimed to validate age estimation performances combining the radiographic development of teeth, cervical vertebrae, hand and wrist bones, skull, and mandible. The sampled consisted of 256 individuals aged between 4 and 20 years. Bayes' rule with a multivariate continuation ratio model was applied for the distribution of the dental scores. The additional age information of the skeletal variables was assessed extending the dental model separately and combining the variables. The performances of all models were quantified and compared using mean error (ME), mean absolute error (MAE), and root mean squared error (RMSE). The best performance resulted combining all variables (ME - 0.04 for F and M; MAE 0.91 for F and 0.95 for M; RMSE 1.14 for F and 1.19 for M). To improve performances and minimize radiation doses, the combination of teeth and hand and wrist bones information is recommended.