Panoramic radiograph-based dental age estimation in children and adolescents using multi-tooth methods: a scoping review of methods used and reported accuracy (2020-2025).

BACKGROUND

Accurate dental age estimation supports treatment planning in pediatric dentistry and orthodontics and forensic assessment when chronological age is uncertain. Because the accuracy of panoramic radiograph-based methods varies across populations, age groups, and method variants, a contemporary synthesis is needed to guide method selection.

OBJECTIVE

To map the methods used for panoramic radiograph-based dental age estimation in children and adolescents and to summarize the reported diagnostic accuracy of the most frequently used method families in studies published between 2020 and 2025.

METHODS

This scoping review was conducted using PubMed, Scopus, and Web of Science. Studies published between 1 January 2020 and 31 December 2025 were screened according to predefined eligibility criteria. Data were extracted using a standardized form, including study characteristics, dental age estimation methods, and reported accuracy outcomes (primarily mean absolute error [MAE] and mean difference/bias [DA-CA]). Thirty-four original studies were included.

RESULTS

The included studies comprised over 35,000 children and adolescents from multiple countries and were predominantly retrospective and clinic-based. Willems-family methods were the most frequently reported, followed by Demirjian-, Cameriere-, and London Atlas-based approaches. Across studies, accuracy reporting was heterogeneous with respect to MAE, bias metrics, sex stratification, and method variants. Cameriere family methods often showed lower MAE values in many cohorts; however, performance varied by population, age range, and method modification.

CONCLUSION

Panoramic radiograph-based dental age estimation methods show substantial heterogeneity in use and reported accuracy across populations. Willems-family methods are the most frequently applied, whereas Cameriere-family methods often demonstrate favorable accuracy in many cohorts, but no single method can be considered universally optimal. Population-specific validation and standardized reporting of accuracy metrics are needed.