Mimics of pancreatic neoplasms at cross-sectional imaging: Pearls for characterization and diagnostic work-up
Bibliographic record
Abstract
Interpreting imaging examinations of the pancreas can be a challenge. Several different entities can mimic or mask pancreatic neoplasms, including normal anatomic variants, non-pancreatic lesions, and both acute and chronic pancreatitis. It is important to distinguish these entities from pancreatic neoplasms, as the management and prognosis of a pancreatic neoplasm, particularly adenocarcinoma, have considerable impact on patients. Normal pancreatic variants that mimic a focal lesion include focal fatty atrophy, annular pancreas, and ectopic pancreas. Extra-pancreatic lesions that can mimic a primary pancreatic neoplasm include vascular lesions, such as arteriovenous malformations and pseudoaneurysms, duodenal diverticula, and intra-pancreatic accessory spleen. Both acute and chronic pancreatitis can mimic or mask a pancreatic neoplasm and are also associated with pancreatic ductal adenocarcinoma. Awareness of these entities and their imaging features will enable the radiologist to narrow the differential diagnosis, provide recommendations that expedite diagnosis and avoid unnecessary work-up or delays in patient care.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".