Related Experiment Video
Updated: Jun 9, 2025

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans
Published on: July 12, 2022
Correlation between dental age and chronological age of Taiwanese children on panoramic X-ray images by different
Kuo-Ting Sun1,2, Yun-Zhen Wu3,4, Jui-Ting Hsu5
1School of Dentistry, China Medical University, Taichung, Taiwan, ROC.
Background:
Accurate age estimation is vital in forensic medicine and clinical dentistry. The Demirjian method is commonly used for this purpose, but its applicability to Asian individuals is understudied. The present study evaluated the accuracy of dental age (DA) estimation for Taiwanese children by using the Demirjian, Willems, and modified Demirjian methods, comparing these estimates to those of chronological age (CA) based on panoramic X-ray images.
Methods:
A total of 232 Taiwanese children aged between 5 and 12 years underwent panoramic X-ray scans. Their permanent teeth were assessed using the Demirjian, Willems, and modified Demirjian methods to estimate DA. Regression analysis was used to determine the correlation between CA and DA, with linear regression equations established using SPSS statistics software to identify differences.
Results:
The Willems method had the lowest mean absolute error and the smallest mean difference between DA and CA among the 3 age estimation methods analyzed ( p < 0.001). The R2 value for the difference between DA and CA was 0.831 for the Willems method, 0.813 for the Demirjian method, and 0.782 for the modified Demirjian method ( p < 0.001). The Willems method had the highest correlation with CA, with the linear equation for Taiwanese children being CA = 0.822 × DA + 1.093. For comparison, for the Demirjian method, the equation was CA = 0.894 × DA + 0.165.
Conclusion:
The effectiveness of predictive methods varies across ethnicities, and therefore, region-specific formulas are required. For Taiwanese children, the Willems method predicts CA most accurately. This study contributes to the fields of legal medicine and clinical dentistry by demonstrating the accuracy of DA in predicting CA.

