Effect of volume and methylene blue on fluorescence intensity and transit of indocyanine green for sentinel lymph node mapping in a simulated feline tumor model
Bibliographic record
Abstract
OBJECTIVE: To compare the effect of volume and solution on transit time and fluorescence intensity (FI) using near-infrared fluorescence imaging (NIRF) in a simulated tumor model in cats. Secondarily, to describe SLN mapping with indocyanine green (ICG) NIRF and report any adverse effects of intradermally injected ICG in cats. ANIMALS: 7 healthy purpose-bred domestic shorthaired male cats. METHODS: Cats were randomly divided into 2 groups (ICG or ICG + methylene blue [MB]). Transit time and FI were determined for 1 or 2 mL solutions injected intradermally in 4 quadrants around a simulated tumor. Following massage, fluorescence intensity was quantified by calculating the corrected total ROI fluorescence using ImageJ software. Cats were monitored for adverse effects up to 4 weeks post-injection. RESULTS: A larger solution volume had decreased transit times to the SLN (P = .001). There was no significant difference in transit times between ICG and ICG-MB. ICG demonstrated a greater FI (P = .001) in the SLN compared to ICG-MB. Methylene blue did not percutaneously fluoresce under NIRF. The volume of the solution did not significantly affect FI. No adverse reactions were reported. CLINICAL RELEVANCE: Increased volume of ICG may aid in rapid percutaneous lymphatic tracking from tumor to SLN. Indocyanine green alone may be preferred over ICG-MB for greater visualization of the SLN. Intradermal injections of ICG and ICG-MB were well-tolerated in healthy cats with no significant complications. Clinical evaluation of this technique in an impaired lymphatic system, as seen in cancer patients, should be assessed in future research.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".