Development and in vivo test of a miniature Raman probe for early cancer detection in the peripheral lung
Bibliographic record
Abstract
The management of cancer in the periphery lung is in critical need of new strategies. Here, the development and test of a novel miniature Raman probe capable of navigating the peripheral lung architecture is reported. The probe was 1.35 mm in diameter, with a minimum bend radius of 13 mm and had a large light collection area for its size. Peripheral lung Raman spectra were successfully obtained from normal tissue and cancerous nodule using the probe coupled to a home-made rapid Raman spectroscopy system with a fast integration time of 1 second and a low excitation power of 15 mW. This is the first time in vivo Raman spectra from the periphery lung being reported. The collected spectra showed lipid, protein and deoxyhemoglobin signatures that might be useful for classifying pathology. Large scale clinical study is planned to confirm the utility of this new technology for improving periphery lung cancer detection. Left: Radial ultrasound image of a peripheral lung nodule: size given by crosshairs D1 and D2. Right: Truncated Raman spectra of a cancerous nodule, whole blood, and normal peripheral airway tissue. Spectra were shifted on intensity scale for clarity.
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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 | 0.001 | 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 | 0.000 |
| 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".