Lymph node mapping in gastric cancer: A pilot study in Western patients.
Bibliographic record
Abstract
192 Background: Adequate surgical lymphadenectomy is integral to the staging and treatment of gastric cancer. A number of Asian studies have explored the utility of lymph node (LN) mapping in gastric cancer but this in not commonly performed in Western countries. We sought to evaluate the utility and safety of LN mapping in Western patients. Methods: We conducted a pilot study of 13 patients with histologically proven non-metastatic gastric adenocarcinoma that received endoscopic peri-tumoral indocyanine green fluorescence (ICG) injections immediately prior to surgical resection to facilitate LN mapping. Illumination with ICG around the primary tumor, in lymphatic basins, tracts, and lymph nodes were confirmed by the PINPOINT system on recorded videos. Descriptive statistical analysis was performed. Results: Among the 13 patients enrolled, median age was 75 years and 7 were men. On pathologic review, 15% were T1, 54% were T2, and 69% had were node negative. Tumours were located in the proximal third in 1 patient, middle third in 2 patients and distal third in 10 patients. All patients had a laparoscopic subtotal gastrectomy and 10 patients had a D2 lymphadenectomy. 5 patients received preoperative and 7 received postoperative chemotherapy. The median number of LNs harvested was 26 [IQR 24-34]. Video confirmation of ICG mapping of the primary tumor, lymphatic basins, tracts, and LNs were obtained in all patients. All LNs identified with ICG uptake were removed with surgical lymphadenectomy. ICG mapped LNs fell outside the D1 distribution in 100% and outside the D1-plus distribution in 54% of cases. ICG mapped LNs were within the D2 distribution in all cases. No ICG related allergic reactions or procedural complications were observed. Postoperative complications included 2 grade A pancreatic fistulas, 1 gastrointestinal bleed, and 1 NSTEMI. Peri-operative morality was zero. Conclusions: We demonstrate ICG lymph node mapping as a safe and useful technique for identifying regional draining lymph nodes and for primary tumor localization in Western patients. The majority of cases found LNs draining outside the D1 and D1+ distributions, highlighting the importance of appropriate lymphadenectomies in gastric cancer.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.001 |
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".