Detection and monitoring of early dental caries and erosion using three-dimensional enhanced truncated-correlation photothermal coherence tomography imaging
Bibliographic record
Abstract
SIGNIFICANCE: Dental caries is the most common oral disease, with significant effects on healthcare systems and quality of life. Developing diagnostic methods for early caries detection is key to reducing this burden and enabling non-invasive treatment as opposed to the drill-and-fill approach. AIM: The application of a thermophotonic-based 3D imaging modality [enhanced truncated-correlation photothermal coherence tomography (eTC-PCT)] to early dental caries is investigated. To this end, the detection threshold, sensitivity, and 3D lesion reconstruction capability of eTC-PCT in imaging artificially generated caries and surface erosion are evaluated. APPROACH: eTC-PCT employs a diode laser with pulsed excitation, a mid-IR camera, and an in-house developed image reconstruction algorithm to produce depth-resolved 2D images and 3D reconstructions. Starting with healthy teeth, dental caries and surface erosion are simulated in vitro through application of specific demineralizing/eroding acidic solutions. RESULTS: eTC-PCT can detect artificial caries as early as 2 days after onset of artificial demineralization and after 45 s of surface erosion, with a laser power equivalent to 64% of maximum permissible exposure. In both cases, the lesion is not visible to the eye and undetected by x-rays. eTC-PCT is capable of monitoring lesion progression in 2-day increments and generating 3D tomographic reconstructions of the advancing lesion. CONCLUSIONS: eTC-PCT shows great potential for further development as a dental imaging modality combining low detection threshold, high sensitivity to lesion progression, 3D reconstruction capability, and lack of ionizing radiation. These features enable early diagnosis and frequent monitoring, making eTC-PCT a promising technology for facilitating preventive dentistry.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".