Locoregional Therapies and Interventional Radiology in Managing Hepatocellular Carcinoma: A Comprehensive Approach to Bridging, Downstaging, and Liver Transplantation
Bibliographic record
Abstract
Abstract Hepatocellular carcinoma (HCC) remains a significant global health challenge, particularly for patients awaiting liver transplants (LTs) due to the scarcity of donor organs. During the waiting period, a multidisciplinary approach becomes crucial to optimize tumor treatment and preserve liver function. In recent years, interventional radiology has emerged as an integral part of treatment strategies. It has played a pivotal role in bridging and downstaging patients on the path to transplantation. Interventional radiologists administer minimally invasive locoregional therapies to HCC patients on LT waiting lists. Additionally, they address complications such as portal hypertension and portal vein thrombosis, which can lead to clinical deterioration and jeopardize transplant candidacy. This article examines the pivotal role of interventional radiology in the management of HCC, highlighting recent studies and advancements within the field. Additionally, it provides a concise review of the eligibility criteria for LT in patients with HCC, alongside a discussion of the surgical techniques employed in LT for these patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".