Identification of lymphatic pathway involved in the spread of bladder cancer: Evidence obtained from fluorescence navigation with intraoperatively injected indocyanine green
Bibliographic record
Abstract
Introduction: We identify lymphatic vessels draining from the bladderby using fluorescence navigation (FN) system.Methods: In total, 12 candidates for radical cystectomy and pelviclymph node dissection (PLND) were included in this study. Afteran indocyanine green (ICG) solution was injected into the bladderduring radical cystectomy, lymphatic vessels draining from thebladder were analyzed using a FN system. PLND was based onthe lymphatic mapping created from the FN measurements (in vivoprobing) in the external iliac, obturator and internal iliac regions;after PLND, the fluorescence of the removed lymph nodes (LNs)was analyzed on the bench (ex vivo probing).Results: There were no patients with complications associated withthe intravesical ICG injection. A lymphatic pathway along inferiorvesical vessels to internal iliac LNs was clearly illustrated in 7 cases.Under in-vivo probing, the fluorescence intensity of internal iliacnodes was greater than that of external iliac or obturator nodes.Under ex-vivo probing, the fluorescence intensity of internal iliacand obturator nodes was greater than that of external iliac nodes.Conclusions: Using an FN system after injecting ICG during a radicalcystectomy operation is a safe and rational approach to detectingthe lymphatic channel draining from the bladder.
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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".