EUS-guided radiofrequency and ethanol ablation of pancreatic insulinomas: a single-center experience
Bibliographic record
Abstract
Aims Insulinomas are the most frequent functional pancreatic neuroendocrine tumors (pNETs). While surgical resection remains still the gold standard treatment, endoscopic ultrasound (EUS)-guided ablation using either ethanol (EUS-EA) or radiofrequency (EUS-RFA) is a minimally invasive alternative treatment modality which induces lesion necrosis [ 1 ]. This study presents a single-center experience in treating pancreatic insulinomas<2 cm with EUS-RFA or EUS-EA focusing on safety and efficacy. Methods 275 patients with pNETs based on EUS-guided fine needle biopsy between 2011 and 2023 were retrospectively identified. 30 of these lesions were treated with EUS-RFA and 4 with EUS-EA. Out of these 34, nine were pancreatic insulinomas, which were included in the analysis. Results 9 patients (7 female; mean age 49 years) with pancreatic insulinomas (mean lesion size 11mm; range 6-19mm) were treated with EUS-guided ablation. 7 of 9 patients underwent EUS-RFA and 2 patients EUS-EA due to a difficult location of the lesion. All EUS-RFA procedures (mean total ablation time for lesion 31s; range 17-69s) or EUS-EA (total ethanol volume, 1,4ml and 0,5ml) resulted in an immediate hypoglycemia relief after 1 treatment session. All patients remained asymptomatic (median follow-up 31 months; range, 11-47 months); 8 of 9 patients were followed-up radiologically in CT or/and EUS (median follow-up,15 months; range, 3-36 months ) and 3 patients due to only partial radiological regression were qualified for subsequent ablation sessions (mean session number 1.5; range 1-3); The complete regression of the lesion was observed among 6 patients by imaging modalities (CT or/and EUS). Two patients had minor adverse events (AEs) (local hematoma treated conservatively and upper gastrointestinal bleeding managed endoscopically). No severe AEs occurred. Conclusions Management of pancreatic insulinomas with EUS-RFA and EUS-EA seems to be effective and safe. However, further studies focusing on long-term response and recurrence are needed. Publication History Article published online: 15 April 2024 © 2024. European Society of Gastrointestinal Endoscopy. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".