Spectrum of liver lesions hyperintense on hepatobiliary phase: an approach by clinical setting
Bibliographic record
Abstract
Hepatobiliary MRI contrast agents are increasingly being used for liver imaging. In clinical practice, most focal liver lesions do not uptake hepatobiliary contrast agents. Less commonly, hepatic lesions may show variable signal characteristics on hepatobiliary phase. This pictorial essay reviews a broad spectrum of benign and malignant focal hepatic observations that may show hyperintensity on hepatobiliary phase in various clinical settings. In non-cirrhotic patients, focal hepatic observations that show hyperintensity in the hepatobiliary phase are usually benign and typically include focal nodular hyperplasia. In patients with primary or secondary vascular disorders, focal nodular hyperplasia-like lesions arise as a local hyperplastic response to vascular alterations and tend to be iso- or hyperintense in the hepatobiliary phase. In oncologic patients, metastases and cholangiocarcinoma are hypointense lesions in the hepatobiliary phase; however, occasionally they may show a diffuse, central and inhomogeneous hepatobiliary paradoxical uptake with peripheral rim hypointensity. Post-chemotherapy focal nodular hyperplasia-like lesions may be tricky, and their typical hyperintense rim in the hepatobiliary phase is very helpful for the differential diagnosis with metastases. In cirrhotic patients, hepatocellular carcinoma may occasionally appear hyperintense on hepatobiliary phase.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".