Computed tomography and angiographic interventional features of ruptured hepatocellular carcinoma: pictorial essay.
Bibliographic record
Abstract
Spontaneous rupture is an uncommon and potentially fatal complication of hepatocellular carcinoma (HCC), occurring in approximately 15% of patients with HCC in Asia and 3% in the United Kingdom.3 The prognosis for hemorrhage of HCC is poor, particularly in those patients with underlying cirrhosis and severe coagulopathy. Computed tomography (CT) rather than angiography is the first-line modality for the detection of rupture. CT can confirm the diagnosis of ruptured HCC and can also help in assessing other organs if the diagnosis is not clear prior to imaging. It allows for an assessment of the entire liver, including the portal vein, which aids in determining the feasibility of embolization and resection. Since the rate of bleeding must normally exceed 1 mL/min before it can be detected on angiography and the extravasation of contrast is present in less than 20% of cases, CT is a more helpful modality. The optimal CT protocol for this condition is triphasic: the precontrast phase allows for assessment of ethiodized oil (lipiodol) uptake, the arterial phase demonstrates enhancement of the mass, and the portal venous phase allows for assessment of the portal veins. Various treatment options have been proposed: transarterial catheter embolization (TACE), emergency liver resection, and delayed resection. Surgical treatment is difficult, if not impossible. In most cases, rupture is a result of diffuse intrahepatic spread of the tumour and underlying liver cirrhosis. Many authors have concluded that a multidisciplinary management that includes TACE as the primary procedure followed by a delayed resection is the preferred treatment. This pictorial essay reviews the radiologic features of spontaneously ruptured HCC on CT imaging and of treatment by angiography.
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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 | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".