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Abstract

Medicine

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images

Published: February 23rd, 2024

DOI:

10.3791/66014

1Department of Orthodontics, Seoul National University Bundang Hospital, 2Division of Orthodontics, Faculty of Dentistry, University of British Columbia, 3Postgraduate Orthodontic Program, Arizona School of Dentistry & Oral Health, A. T. Still University, 4Graduate School of Dentistry, Kyung Hee University

* These authors contributed equally

Abstract

This study aimed to introduce cone-beam computed tomography (CBCT) digitization and integration of digital dental images (DDI) based on artificial intelligence (AI)-based registration (ABR) and to evaluate the reliability and reproducibility using this method compared with those of surface-based registration (SBR). This retrospective study consisted of CBCT images and DDI of 17 patients who had undergone computer-aided bimaxillary orthognathic surgery. The digitization of CBCT images and their integration with DDI were repeated using an AI-based program. CBCT images and DDI were integrated using a point-to-point registration. In contrast, with the SBR method, the three landmarks were identified manually on the CBCT and DDI, which were integrated with the iterative closest points method.

After two repeated integrations of each method, the three-dimensional coordinate values of the first maxillary molars and central incisors and their differences were obtained. Intraclass coefficient (ICC) testing was performed to evaluate intra-observer reliability with each method's coordinates and compare their reliability between the ABR and SBR. The intra-observer reliability showed significant and almost perfect ICC in each method. There was no significance in the mean difference between the first and second registrations in each ABR and SBR and between both methods; however, their ranges were narrower with ABR than with the SBR method. This study shows that AI-based digitization and integration are reliable and reproducible.

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Keywords Artificial Intelligence

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