Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: May 24, 2025
Date Accepted: Nov 3, 2025

The final, peer-reviewed published version of this preprint can be found here:

Dental Caries Detection in Children Using Intraoral Scanners Featuring Fluorescence: Diagnostic Agreement Study

Jones B, Chen T, Michou S, Kilpatrick N, Curtis N, Burgner DP, Vannahme C, Silva M

Dental Caries Detection in Children Using Intraoral Scanners Featuring Fluorescence: Diagnostic Agreement Study

JMIR Public Health Surveill 2025;11:e78023

DOI: 10.2196/78023

PMID: 41358644

PMCID: 12683709

Dental Caries Detection in Children Using Intraoral Scanners Featuring Fluorescence: A Diagnostic Agreement Study

  • Bree Jones; 
  • Tong Chen; 
  • Stavroula Michou; 
  • Nicky Kilpatrick; 
  • Nigel Curtis; 
  • David P Burgner; 
  • Christoph Vannahme; 
  • Mihiri Silva

ABSTRACT

Background:

Dental caries is a common chronic disease in children, yet large-scale surveillance is limited by the resource demands of clinical examinations. Digital tools like intraoral scanners may offer a scalable alternative for caries detection, enabling more efficient data collection for research and population-level oral health monitoring.

Objective:

To assess the diagnostic agreement between visual examination and on-screen assessment of 3D models generated by an intraoral scanner (IOS) in colour and supplemented with fluorescence for caries detection in primary teeth.

Methods:

Children participating in a clinical trial (n=216, mean age 5.6 years) underwent visual examination using the International Caries Detection and Assessment System (ICDAS) and intraoral scanning using the TRIOS 4 IOS (3Shape TRIOS A/S Denmark). Four trained registered dental practitioners independently assessed each participant’s 3D models in colour, then supplemented with fluorescence, using a previously validated ICDAS index modified for on-screen assessments of 3D models. All 3D models were assessed again four weeks later. The time taken for intraoral scanning and on-screen assessment was recorded. Multilevel logistic regression was used to estimate and compare the likelihood of detecting caries between methods, and Bland–Altman plots were used to visualise agreement. Analyses were performed at the initial (ICDAS>01), moderate (ICDAS>03), and extensive (ICDAS>05) dental caries thresholds. Intraclass Correlation Coefficient (ICC) estimated method agreement and examiner reliability.

Results:

8,209 visible primary tooth coronal surfaces were analysed. The likelihood of detecting caries using colour assessment of 3D models was similar to visual examination at all disease thresholds: initial (odds ratio 1.1, 95% confidence interval (CI) 1.0–1.3), moderate (0.9, 0.7-1.1) and extensive (1.0, 0.7–1.3). When colour assessments were supplemented with fluorescence, the likelihood of detecting caries was 30% higher at the initial threshold relative to visual examination (1.3, 1.1-1.5) and similar at the moderate (0.9, 0.7-1.1) and extensive thresholds (0.9, 0.7-1.3). Bland-Altman plots showed a high level of agreement at both moderate and extensive thresholds. Examiner reliability using intraoral scans ranged from good to excellent.

Conclusions:

On-screen assessment of 3D models in colour shows greatest agreement with visual examination for caries detection at all disease thresholds. Clinical Trial: Australian New Zealand Clinical Trials Registry ACTRN12622001237774


 Citation

Please cite as:

Jones B, Chen T, Michou S, Kilpatrick N, Curtis N, Burgner DP, Vannahme C, Silva M

Dental Caries Detection in Children Using Intraoral Scanners Featuring Fluorescence: Diagnostic Agreement Study

JMIR Public Health Surveill 2025;11:e78023

DOI: 10.2196/78023

PMID: 41358644

PMCID: 12683709

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.