Computed tomography-guided percutaneous core needle biopsy in pancreatic tumor diagnosis
Bibliographic record
Abstract
AIM: To evaluate the techniques, results, and complications related to computed tomography (CT)-guided percutaneous core needle biopsies of solid pancreatic lesions. METHODS: CT-guided percutaneous biopsies of solid pancreatic lesions performed at a cancer reference center between January 2012 and September 2013 were retrospectively analyzed. Biopsy material was collected with a 16-20 G Tru-Core needle (10-15 cm; Angiotech, Vancouver, CA) using a coaxial system and automatic biopsy gun. When direct access to the lesion was not possible, indirect (transgastric or transhepatic) access or hydrodissection and/or pneumodissection maneuvers were used. Characteristics of the patients, lesions, procedures, and histologic results were recorded using a standardized form. RESULTS: A total of 103 procedures included in the study were performed on patients with a mean age of 64.8 year (range: 39-94 year). The mean size of the pancreatic lesions was 45.5 mm (range: 15-195 mm). Most (75/103, 72.8%) procedures were performed via direct access, though hydrodissection and/or pneumodissection were used in 22.2% (23/103) of cases and indirect transhepatic or transgastric access was used in 4.8% (5/103) of cases. Histologic analysis was performed on all biopsies, and diagnoses were conclusive in 98.1% (101/103) of cases, confirming 3.9% (4/103) of tumors were benign and 94.2% (97/103) were malignant; results were atypical in 1.9% (2/103) of cases, requiring a repeat biopsy to diagnose a neuroendocrine tumor, and surgical resection to confirm a primary adenocarcinoma. Only mild/moderate complications were observed in 9/103 patients (8.7%), and they were more commonly associated with biopsies of lesions located in the head/uncinate process (n = 8), than of those located in the body/tail (n = 1) of the pancreas, but this difference was not significant. CONCLUSION: CT-guided biopsy of a pancreatic lesion is a safe procedure with a high success rate, and is an excellent option for minimally invasive diagnosis.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".