A82 SUCCESSFUL RESECTION OF GRADE 1 DUODENAL NEUROENDOCRINE TUMOURS USING ENDOSCOPIC TECHNIQUES IN TWO CANADIAN HOSPITALS
Bibliographic record
Abstract
Abstract Background Given the rarity of duodenal neuroendocrine tumours (dNETs), limited guidelines exist for resection of well-differentiated, ≤10 mm dNETS. As incidence rises, alternatives to surgery are valuable. We present 9 cases of endoscopic dNET resections and a literature review. Aims To demonstrate efficacy and safety of endoscopic resection for dNETs ≤10 mm at 2 Canadian hospitals. Methods We retrospectively analyzed data on 7 patients that had endoscopic dNET resection from 2013–2018. Endoscopic resection occurred if dNETs were ≤10 mm in diameter, did not extend to the muscularis propria and lymphovascular invasion was absent. WHO 2017 classification was used. Results All patients had biopsies and 5 (71%) had EUS prior to resection; 4 females and 3 males underwent resection of 9 dNETs; 2 via cap-assisted snare polypectomy; 4 with cap-assisted band mucosectomy; and 2 over-the-scope clip-assisted resection. The median size was 10 mm (4–11); 6 (67%) dNETS were found in the duodenal bulb, 2 at the D1/D2 junction and 1 in D2 alone. The median age was 68.5 (50–79) years. All dNETs were submucosal and well-differentiated. The dNETs were resected en bloc, but 3 did not have clear margins. Two procedures were complicated by duodenal perforation; 1 requiring surgery and 18 days in hospital. One case was complicated by bleeding with successful endoscopic hemostasis. The majority (75%) of resections were day procedures. Patients were followed for 6–12 months with an EGD or chromogrannin A. None of the patients had endoscopic residual disease, but 1 patient required a second procedure to remove a dNET left in situ following the initial resection of 2 dNETs 12 months earlier. In our literature review of 178 patients, the majority of dNETs were resected by EMR 81% (150/185) versus ESD, similar to our experience. Patients were slightly younger with a mean age of 63.28, and most dNETs (46%) were found in the duodenal bulb. Complications included intraoperative bleeding, perforation and death in 17 (9.55%), 9 (5.06%) and 1 (0.06%) patient(s) respectively. The rate of recurrence was 4/178 (2.25%) and patients had a mean follow up of 26.1 months. Conclusions Well-differentiated dNETs ≤10 mm in diameter can be successfully resected endoscopically. Complications can be managed intraoperatively and hospital stay remains minimal. Funding Agencies None
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".