Performance of several diagnostic systems on detection of occlusal primary caries in permanent teeth
Bibliographic record
Abstract
Detection of caries at an early stage is unequivocally essential for early preventive intervention. Longitudinal assessment of caries lesions, especially under the opaque preventive sealant, would be of utmost importance to the dental community. OBJECTIVES: The aim of this two-part in-vitro study is to evaluate the performance of multiple detection methods: The International Caries Detection and Assessment System (ICDAS); two quantitative light-induced fluorescence systems QLF; Inspektor™ Pro and QLF-D Biluminator™2 (Inspektor Research Systems B.V.; Amsterdam, The Netherlands); and photothermal radiometry and modulated luminescence (PTR/LUM) of The Canary System® (Quantum Dental Technologies; Toronto, Canada). All these are to be evaluated on their detection of caries on posterior human permanent teeth for 1) of primary occlusal lesions, and 2) under the sealant of primary occlusal lesions. METHODS: One hundred and twenty (N = 120) human posterior permanent teeth, selected in compliance with IU-IRB “Institutional Review Board” standards, with non-cavitated occlusal lesions ICDAS (scores 0 to 4) were divided into two equal groups. The second group (N = 60) received an opaque resin dental sealant (Delton® Light-Curing Pit and Fissure Sealant Opaque, Dentsply, York, PA). All lesions were assessed with each detection method twice in a random order except for ICDAS, which was not used following the placement of the sealant. Histological validation was used to compare methods in regard to sensitivity, specificity, % correct, and the area under receiver- operating characteristic curve (AUC). Intra-examiner repeatability and inter-examiner agreement were measured using intraclass correlation coefficient (ICC). RESULTS: 1) Of primary occlusal lesions, sensitivity, specificity, and AUC values were respectively: 0.82, 0.86 and 0.87 (ICDAS); 0.89, 0.60 and 0.90 (Inspektor Pro); 0.96, 0.57 and 0.94 (QLF-D Biluminator 2); and 0.85, 0.43 and 0.79 (The Canary System). Intra-examiner repeatability and inter-examiner agreement were respectively: 0.81 to 0.87: 0.72 (ICDAS); 0.49 to 0.97: 0.73 (Inspektor Pro); 0.96 to 0.99: 0.96 (QLF-D Biluminator 2); and 0.33 to 0.63: 0.48 (The Canary System). 2) Of primary occlusal lesions under the opaque dental sealants, sensitivity, specificity, and AUC values were respectively: 0.99, 0.03 and 0.67 (Inspektor Pro); 1.00, 0.00 and 0.70 (QLF-D Biluminator 2); and 0.54, 0.50 and 0.58 (The Canary System). Intra-examiner repeatability and inter-examiner agreement were respectively: 0.24 to 0.37: 0.29 (Inspektor Pro); 0.80 to 0.84: 0.74 (QLF-D Biluminator 2); and 0.22 to 0.47: 0.01 (The Canary System). CONCLUSION: Limited to these in-vitro conditions, 1) ICDAS remains the method of choice for detection of early caries lesion due to its adequately high accuracy and repeatability. QLF systems demonstrate potential in longitudinal monitoring due to an almost perfect repeatability of QLF-D Biluminator 2. The Canary System performance and repeatability were not acceptable as a valid method of early caries detection. 2) None of the methods demonstrated acceptable ability in detecting of occlusal caries under the opaque sealant. However, QLF-D Biluminator 2, with limitation to these in-vitro conditions and Delton opaque sealant, demonstrated a fair accuracy AUC (0.70) in detecting of caries under sealants at an experimental threshold of 12.5% ΔF.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".