Identification of lymphatic pathway involved in the spreading of prostate cancer by fluorescence navigation approach with intraoperatively injected indocyanine green
Bibliographic record
Abstract
OBJECTIVE: : The objective of this study was to identify lymphatic vessels draining from the prostate by using a fluorescence navigation (FN) system. METHODS: : Fourteen subjects were candidates for radical retropubic prostatectomy (RRP) and pelvic lymph node dissection (PLND). After an indocyanine green solution was injected into the prostate during RRP, lymphatic vessels draining from the prostate were analyzed using a FN system. After PLND based on lymphatic mapping by the FN system (in vivo probing) was performed in the external iliac, obturator and internal iliac regions; the fluorescence of the removed lymph nodes (LNs) was analyzed on the bench (ex vivo probing). RESULTS: : Under in vivo and ex vivo probing, the fluorescence intensity of internal iliac nodes was greater than that of external iliac or obturator nodes. CONCLUSION: : The current study suggests that using a FN system after injecting indocyanine green is a safe and rational approach for detecting the lymphatic channel draining from the prostate. The major lymphatic pathway involved in the spreading of prostate cancer appears to relate to internal iliac LNs, which would mean that the standard PLND covering external iliac and obturator regions would not keep the cancer from spreading.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.002 | 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".