Caries Detection in Primary Teeth Using Intraoral Scanners Featuring Fluorescence: Protocol for a Diagnostic Agreement Study

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Authors

Bree Jones, Stavroula Michou, Tong Chen, Margarita Moreno-Betancur, Nicky Kilpatrick, David P. Burgner, Christoph Vannahme, Mihiri Silva

Published

1 November 2023

Publication details

JMIR Research Protocols, 12:e51578

Links

DOI

 

Background: Digital methods that enable early caries identification can potentially streamline data collection in research and optimize dental examinations for young children. Intraoral Scanners are devices used for creating 3D models of teeth in dentistry and are being rapidly adopted into clinical workflows. Integrating fluorescence technology into scanner hardware can support early caries detection. However, the performance of caries detection methods using 3D models featuring color and fluorescence in primary teeth is unknown.

Objective: This study aims to assess the diagnostic agreement between visual examination, on-screen assessment of 3D models in approximate natural colors with and without fluorescence and application of an automated caries scoring system for caries detection in primary teeth.

Methods: The study sample will be drawn from eligible participants in a randomized controlled trial at the Royal Children’s Hospital, Melbourne, where a dental assessment was conducted, including visual examination using the International Caries Detection and Assessment System (ICDAS) and intraoral scan using the TRIOS 4 (3Shape TRIOS A/S, Copenhagen, Denmark). Participant clinical records will be collected, and all records meeting eligibility criteria will be subject to an on-screen assessment of 3D models by four dental practitioners. First, all primary tooth surfaces will be examined for caries based on 3D geometry and color, using a merged ICDAS index. Second, the on-screen assessment of 3D models will include fluorescence, where caries will be classified using a merged ICDAS index that has been modified to incorporate fluorescence criteria. After four weeks all examiners will repeat the on-screen assessment for all 3D models. Finally, an automated caries scoring system will be used to classify caries on primary occlusal surfaces. The agreement in the total number of caries detected per person between methods will be assessed using a Bland-Altman analysis and intraclass correlation coefficients . At a tooth surface level agreement between methods will be estimated using multilevel models to account for the clustering of dental data.

Results: Automated caries scoring of 3D models was completed as of October 2023, with publication of results expected by July 2024. On-screen assessment has commenced, with expected completion of scoring and data analysis by March 2024. Results will be disseminated by the end of 2024.

Conclusion: The study outcomes may inform new practices that utilize digital models to facilitate dental assessments. Novel approaches that enable remote dental examination without compromising the accuracy of visual examination have wide application in the research environment, clinical practice and for the provision of teledentistry.