Endoscopic Doppler optical coherence tomography and autofluorescence imaging of peripheral pulmonary nodules and vasculature
Bibliographic record
Abstract
We present the first endoscopic Doppler optical coherence tomography and co-registered autofluorescence imaging (DOCT-AFI) of peripheral pulmonary nodules and vascular networks in vivo using a small 0.9 mm diameter catheter. Using exemplary images from volumetric data sets collected from 31 patients during flexible bronchoscopy, we demonstrate how DOCT and AFI offer complementary information that may increase the ability to locate and characterize pulmonary nodules. AFI offers a sensitive visual presentation for the rapid identification of suspicious airway sites, while co-registered OCT provides detailed structural information to assess the airway morphology. We demonstrate the ability of AFI to visualize vascular networks in vivo and validate this finding using Doppler and structural OCT. Given the advantages of higher resolution, smaller probe size, and ability to visualize vasculature, DOCT-AFI has the potential to increase diagnostic accuracy and minimize bleeding to guide biopsy of pulmonary nodules compared to radial endobronchial ultrasound, the current standard of care.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".