Efficacy of bisphosphonates in detection of early enamel caries using NIR fluorescence imaging and inhibition of caries progression
Bibliographic record
Abstract
NIR fluorescence imaging using bisphosphonate-Indocyanine green has been indicated for early interproximal caries detection. This study assessed diagnostic accuracy of caries detection by NIR fluorescence imaging with OsteoSense 750 (OS750) in vitro and ex vivo, and to analyze the therapeutic efficacy of a bisphosphonate (Etidronate) in inhibiting enamel caries progression in vitro. Methods: Four experiments were conducted using extracted human teeth; 1) to calculate the infiltration rate of OS750 into interproximal white spot lesions using fluorescence microscope, 2) to assess diagnostic accuracy of interproximal natural white spot lesions using desktop NIR fluorescence imaging device in vitro setting, 3) to assess diagnostic accuracy of artificially created deeper enamel carious lesion (0.5 mm~1.0 mm) using NIR fluorescence image through the head-mount display in ex vivo setting, 4) to compare the progression on the enamel caries lesions treated by Etidronate, NaF and distilled-water. Diagnostic accuracy was analyzed using sensitivity, specificity and receiver operating curves (ROC). The caries progression was calculated with micro-CT and was statistically analyzed using a two-way ANOVA and the Tukey HDS post-hoc test. Results: 1) The infiltration rate of OS750 was 101.83% 8.66 (Min: 90.10%, Max: 133.94%). 2) The average of sensitivity and specificity in vitro setting experiments were 86.7% 4.4% and 70% 11%, respectively. The average of area under the ROC curves (AUC) was 0.883 0.059 indicating excellent performance. 3) The mean sensitivity and specificity in ex vivo setting was 82.97% 15% and 76.78% 13.27% respectively. 4) The carious lesion volume treated by Etidronate was significantly smaller at post treatment-1 (p<0.05) and treatment-2 (p<0.01) than the control. There was no significant difference in lesion volume in the Etidronate and NaF group at the time point of post treatment-1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".