Validation of a novel tool for automated tooth modelling by fusion of CBCT-derived roots with the respective IOS-derived crowns

Benedetta Baldini; Dhanaporn Papasratorn; Fernanda Bulhões Fagundes; Rocharles Cavalcante Fontenele; Reinhilde Jacobs

doi:10.1016/j.jdent.2024.105546

Validation of a novel tool for automated tooth modelling by fusion of CBCT-derived roots with the respective IOS-derived crowns

J Dent. 2024 Dec 30:153:105546. doi: 10.1016/j.jdent.2024.105546. Online ahead of print.

Authors

Benedetta Baldini¹, Dhanaporn Papasratorn², Fernanda Bulhões Fagundes³, Rocharles Cavalcante Fontenele⁴, Reinhilde Jacobs⁵

Affiliations

¹ OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, KU Leuven, Leuven, Belgium; Department of Oral and Maxillofacial Surgery, University Hospitals Leuven, Leuven, Belgium; Department of Electronics, Information and Bioengineering, Politecnico Di Milano, Italy; UOC Maxillo-Facial Surgery and Dentistry Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, Milan, Italy.
² OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, KU Leuven, Leuven, Belgium; Department of Oral and Maxillofacial Surgery, University Hospitals Leuven, Leuven, Belgium; Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Mahidol University, Bangkok, Thailand.
³ OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, KU Leuven, Leuven, Belgium; Department of Oral and Maxillofacial Surgery, University Hospitals Leuven, Leuven, Belgium; Division of Oral Radiology, Department of Oral Diagnosis, Piracicaba Dental School, University of Campinas, Piracicaba, Sao Paulo, Brazil.
⁴ OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, KU Leuven, Leuven, Belgium; Department of Oral and Maxillofacial Surgery, University Hospitals Leuven, Leuven, Belgium.
⁵ OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, KU Leuven, Leuven, Belgium; Department of Dental Medicine, Karolinska Institute, Stockholm, Sweden. Electronic address: [email protected].

PMID: 39743133
DOI: 10.1016/j.jdent.2024.105546

Abstract

Objectives: To validate a novel artificial intelligence (AI)-based tool for automated tooth modelling by fusing cone beam computed tomography (CBCT)-derived roots with corresponding intraoral scanner (IOS)-derived crowns.

Methods: A retrospective dataset of 30 patients, comprising 30 CBCT scans and 55 IOS dental arches, was used to evaluate the fusion model at full arch and single tooth levels. AI-fused models were compared with CBCT tooth segmentation using point-to-point surface distances-reported as median surface distance (MSD), root mean square distance (RMSD), and Hausdorff distance (HD)- alongside visual assessments. Qualitative assessment included visual inspection of CBCT multiplanar views. The automated fused model was also compared to expert-manual fusions for single tooth analysis in terms of accuracy, time efficiency, and consistency.

Results: AI-based fusion evaluation showed mean values of MSD, RMSD, and HD of 4 μm, 114 μm, and 940 μm for full arch; 5 μm, 104 μm, and 503 μm for single tooth analysis. Qualitative assessment showed discrepancies between fused tooth outline and CBCT tooth margin lower than 1 voxel for 59% of cases. AI-based fusion showed high similarity with expert-manual fusions with median MSD, RMSD, and HD values of 28 μm, 104 μm, and 576 μm, respectively. However, AI-based fusion was 32 times faster than manual fusion. Considering the time required for manual fusion, intra-observer agreement was high (ICC 0.93), while inter-observer agreement was moderate (ICC 0.48).

Conclusion: The AI-based CBCT/IOS fusion demonstrated clinically acceptable accuracy, efficiency, and consistency, offering substantial time savings and robust performance across different patients and imaging devices.

Clinical significance: Manual CBCT/IOS fusion performed by experts is effective but labor-intensive and time-consuming. AI algorithms show a remarkable ability to minimize human variability, resulting in more reliable and efficient fusion. This capability demonstrates the potential to provide a more personalized, precise and standardized approach for treatment planning and dental procedures.

Keywords: 3D imaging; Computer-Assisted Image Processing; artificial intelligence; cone-beam computed tomography; digital dentistry; intra-oral scanner; multimodal image fusion.