Imaging in staging, treatment planning, and monitoring of hepatocellular carcinoma for local and locoregional therapies: consensus recommendations from EORTC and ESGAR
Bibliographic record
Abstract
BACKGROUND: Periinterventional imaging of patients with hepatocellular carcinoma (HCC) during local and locoregional therapies plays a crucial role in clinical outcome by guiding treatment allocation, planning, and application. However, there is a considerable variety in clinical routine in terms of timing, modality, and imaging protocols. This study aimed to guide the standardization of the imaging procedures for patients with HCC by conducting a Delphi consensus-finding survey. METHODS: A multidisciplinary, multinational survey was conducted to standardize the imaging of patients with HCC using the Delphi method. RESULTS: Under the guidance of the European Organisation for Research and Treatment of Cancer (EORTC) Imaging and Gastrointestinal Tract Cancer Groups and the European Society of Gastrointestinal and Abdominal Radiology (ESGAR), the recommendations for imaging before, during, and after thermal ablation, transarterial chemoembolization, radioembolization, and stereotactic body radiation therapy were established. CONCLUSION: This consensus protocol provides a foundational guide for imaging in the daily clinical management of HCC patients, as well as for prospective studies assessing local and locoregional therapies. KEY POINTS: Question There are clear recommendations for the respective therapies/disease stages in HCC, but only to a limited extent for all-around imaging of local therapies. Findings This study conveyed a Delphi consensus-finding survey amongst European experts from multiple medical fields to standardize the periinterventional imaging of HCC patients. Clinical relevance These recommendations can guide both daily clinical practice and prospective trials focused on local and locoregional therapies.
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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 | 0.194 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".