Gallbladder Cancer: Imaging Appearance and Pitfalls in Diagnosis
Bibliographic record
Abstract
Gallbladder cancer is an uncommon malignancy with an overall poor prognosis. The clinical and imaging presentation of gallbladder cancer often overlaps with benign disease, making diagnosis difficult. Gallbladder cancer is most easily diagnosed on imaging when it presents as a mass replacing the gallbladder. At this stage, the prognosis is usually poor. Recognizing the features of gallbladder cancer early in the disease can enable complete resection and improve prognosis. Recognition of the patterns of wall enhancement on computed tomography can help differentiate gallbladder cancer from benign disease. Gallbladder wall thickening without pericholecystic fluid presenting in an older patient with raised alkaline phosphatase should raise concern regarding gallbladder cancer. Gallbladder polyps in high-risk individuals need close surveillance or surgery as per guidelines. Small gallbladder cancers in the neck can present as biliary dilatation or cholecystitis, and careful examination of this area is needed to assess for lesion. The imaging appearance of gallbladder cancer is reviewed and supported by local institutional data. Features that differentiate it from its common mimics enabling earlier diagnosis are described.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| 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".