Comparison of Two Artificial Intelligence Programs for Bone Age Assessment Using Hand-Wrist Radiographs in Korean Children and Adolescents Undergoing Orthodontic Diagnosis.
Children, 2026
Abstract
Purpose
Accurate assessment of skeletal maturation is important for timing pediatric dental and orthodontic interventions. This study compared bone age estimates generated by two AI-based programs, CRESCOM MediAI-BA and VUNO Med-BoneAge®, in Korean children and adolescents undergoing orthodontic diagnostic evaluation.
Methods
This retrospective study compared bone-age estimates generated by CRESCOM MediAI-BA and VUNO Med-BoneAge® using left hand–wrist radiographs from 200 Korean children and adolescents (100 boys and 100 girls; 6–17 years) undergoing orthodontic diagnostic evaluation. Chronological age and program-derived bone age were compared by sex and age group using the Wilcoxon signed-rank test. Standardized differences were summarized using Cohen’s d, and Spearman correlations were calculated among chronological age, program-derived bone age, and the CRESCOM skeletal maturity indicator (SMI).
Results
The standardized differences between chronological age and CRESCOM-predicted bone age were very small in boys (d = 0.143) and small in girls (d = 0.258). Corresponding differences for VUNO Med-BoneAge® were small in boys (d = 0.254) and girls (d = 0.216). CRESCOM SMI correlated strongly with chronological age (ρ = 0.852), VUNO-predicted bone age (ρ = 0.910), and CRESCOM-predicted bone age (ρ = 0.932; all p < 0.001). However, statistically significant age- and sex-specific differences were observed between chronological age and AI-predicted bone age and between the two programs.
Conclusions
CRESCOM MediAI-BA may provide clinically useful adjunctive information for skeletal-maturity assessment; nevertheless, AI-derived bone-age estimates from different programs should not be considered interchangeable and should be interpreted in conjunction with clinical findings and established skeletal-maturity indicators.
