Image-Guided Percutaneous Biopsy for Pancreatic Lesions: 10-Year Experience in a Tertiary Cancer Center
Bibliographic record
Abstract
INTRODUCTION: Image-guided biopsy is an important tool in the diagnosis of solid pancreatic masses. This study aims to evaluate the accuracy and complications associated with this procedure. METHODS: We conducted a retrospective cohort study of all patients referred to interventional radiology for pancreatic biopsy at our institution from July 2004-July 2015. Two radiologists independently reviewed the images, technical aspects, and clinical characteristics. RESULTS: A total of 82 patients underwent pancreatic biopsy using a combination of computed tomography (CT) and/or ultrasound guidance. Mean age was 67.8 years with 56% males. Most lesions were located in the head (63.4%), followed by the tail (19.5%), and the body (17.1%). The procedures were performed using the anterior (79.3%), lateral (7.3%), or posterior (13.4%) approach, with direct access in 85.4% of the patients and indirect access (transgastric or transhepatic) in 14.6% of cases. Core biopsies were obtained in 81.7% of cases, and fine needle aspiration was performed in 18.3% of cases. Needle size varied from 18-22 gauge (median 20 gauge). The median number of samples collected was 3 (range 1-8). A conclusive result was obtained in 82.9% of cases. There were 9 (11%) patients with minor complications: minor bleeding, pain, and inadvertent bowel puncture with no clinical repercussion. There were no deaths or major complications. CONCLUSION: Percutaneous image-guided pancreatic mass biopsy can be performed safely with excellent accuracy. Our results are comparable with endoscopic biopsy/aspiration, and percutaneous biopsy may be used as an alternative, particularly at institutions where endoscopy facilities are limited.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".