Evaluation of Root Length, Tip, and Torque Using AI-supported Planning Software Compared with CBCT: A Cross-sectional Observational Study

Background Accurate assessment of root length, tip, and torque is essential for orthodontic diagnosis and treatment planning. Cone-beam computed tomography (CBCT) provides reliable three-dimensional visualization of tooth roots but is associated with radiation exposure. Recently, artificial intelligence (AI)-supported planning software has enabled virtual root reconstruction using intraoral scan data; however, the accuracy of such reconstructions compared with CBCT remains uncertain. Objectives To compare root length, tip, and torque measurements obtained from CBCT with those generated by AI-supported planning software (Maestro 3D) using intraoral scan data. Methods This cross-sectional observational study included 21 patients with existing pre-treatment CBCT records. Intraoral scanning was performed prior to orthodontic treatment. The maxillary left central incisor was selected as the reference tooth. CBCT Digital Imaging and Communications in Medicine (DICOM) data were segmented using 3D Slicer to generate STL files. Intraoral STL files were imported into Maestro 3D, where AI-based root reconstruction was performed. Root length, tip, and torque measurements were recorded and compared using paired samples t -tests and Bland–Altman analysis. Results CBCT-derived root length measurements were significantly greater than AI-generated measurements (mean difference = 5.01 mm; P < .001). The AI-supported software consistently produced a fixed root length value of approximately 12 mm with no variation, indicating a limitation of the algorithm and suggesting reliance on standardized templates rather than individualized root morphology. Tip measurements also showed a statistically significant difference between the two methods (mean difference = −0.85°; P < .001). Torque measurements demonstrated a small but statistically significant difference between CBCT and AI-generated models (mean difference = 0.67°; P = .045). Conclusion AI-supported planning software underestimated root length and slightly overestimated tip compared with CBCT, while torque measurements were comparable. CBCT remains the reference standard for root length assessment, whereas AI-based intraoral scan analysis may be clinically acceptable for torque evaluation.