Abstract
Objectives: The primary aim of this investigation was to validate a method for generating 3D replicas through virtual segmentation, utilizing artificial intelligence (AI) or manual-driven methods, assessing accuracy in terms of volumetric and linear discrepancies. The secondary aims were the assessment of time efficiency with both segmentation methods and the effect of post-processing 3D replicas.
Methods: Thirty teeth were scanned through Cone Beam Computed Tomography (CBCT), capturing the region of interest from human subjects. DICOM files underwent segmentation through both AI and manual-driven methods. Replicas were fabricated with a stereolithography 3D printer. After surface scanning of pre-processed replicas and extracted teeth, STL files were superimposed to evaluate linear and volumetric differences using the extracted teeth as the reference. Post-processed replicas were scanned to assess the effect of post-processing on linear and volumetric changes.
Results: AI-driven segmentation resulted in statistically significant mean linear and volumetric differences of -0.709mm and -4.70%, respectively. Manual segmentation showed no statistically significant differences in mean linear (-0.463mm) and volumetric (-1.20%) measures. Comparing manual and AI-driven segmentations, showed that AI-driven segmentation displayed mean linear and volumetric differences of -0.329mm and -2.23%, respectively. Additionally, AI segmentation reduced mean time by 21.8 minutes. When comparing post-processed to pre-processed replicas, there was a volumetric reduction of -4.53% and a mean linear difference of -0.151mm.
Conclusion: Both segmentation methods achieved acceptable accuracy, with manual segmentation slightly more accurate and AI-driven segmentation more time-efficient. Continuous improvement in AI offers the potential for increased accuracy, efficiency, and broader application in the future.
Clinical Significance: Tooth replica generation in the context of tooth autotransplantation therapy may contribute to enhanced success and survival rates. Accurate CBCT-based virtual segmentation and 3D printing technologies are particularly important in the fabrication of 3D replicas. Therefore, it is crucial to assess the accuracy of available techniques and alternatives to demonstrate their reliability and accuracy in the fabrication of tooth replicas.