Applicability and validation of Franco, Willems and Willems II dental age estimation models in a population of Ceará, Brazil

TL;DR

This study tested three dental age estimation models in children and adolescents from Ceará, Brazil, finding them valid for clinical and forensic use.

Contribution

First evaluation of Franco, Willems, and Willems II models in a Northeastern Brazilian population.

Findings

Franco’s model showed the smallest bias compared to chronological age.

All models demonstrated comparable accuracy and consistency in the Ceará population.

Differences between chronological and estimated ages were minimal and not clinically relevant.

Abstract

Dental age assessment plays a crucial role in clinical and forensic contexts. For safer practices, however, the existing methods need to be tested. This study aimed to evaluate for the first time the applicability of Franco’s, Willems’, and Willems’ II dental age assessment models in a Northeastern Brazilian sample. The sample consisted of 500 panoramic radiographs (250 males, 250 females) of Brazilian individuals between 6 and 15.9 years from the State of Ceará. Chronological (CA) and estimated (EA) ages compared using mean error (ME), mean absolute error (MAE), and root mean square error (RMSE). Statistical comparisons were performed through generalized estimating equations (GEE). The mean CA of the sample was 11.0 years. The mean EA was 11.3 years for Franco’s model, 11.6 for Willems’, and 11.5 for Willems II. Franco’s model showed the smallest bias, with ME values being 0.25 and 0.21 years lower than Willems’ and Willems II, respectively (p < 0.001). Differences between CA and EA were minimal across sexes and not clinically relevant. Age-group analysis revealed similar performance up to 11.9 years. Overall, Franco’s model demonstrated better error metrics, but all the models showed comparable accuracy and consistency for dental age estimation in children and adolescents from Ceará, confirming their validity and suitability for both clinical and forensic applications in this population.

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