ReviewJHEP reports : innovation in hepatology2020
Evaluation of liver tumour response by imaging.
Review in JHEP reports : innovation in hepatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06490757 (A Phase 2 Open-label Single-arm Trial of JAK1 Inhibitor for the Treatment of Large Inflammatory Hepatocellular Adenomas), which is not on this map. Cited by 36 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Phase 2 Open-label Single-arm Trial of JAK1 Inhibitor for the Treatment of Large Inflammatory Hepatocellular Adenomas
Who cites it
36 citing papers in PubMed, 3 syntheses or guidelines pooled it, 62 citations in OpenAlex.
- Expert consensus regarding the clinical application of liver contrast-enhanced US with Sonazoid (Sonazoid CEUS).International journal of surgery (London, England) · 2026Guideline
- ESR Essentials: assessing the radiological response of liver metastases to systemic therapy-practice recommendations by the European Society of Gastrointestinal and Abdominal Radiology.European radiology · 2025Guideline
- Diagnostic accuracy of Liver Imaging Reporting and Data System locoregional treatment response criteria: a systematic review and meta-analysis.European radiology · 2021Pooled it
- Radiosensitization of intrahepatic cholangiocarcinoma and metastatic disease in the liver using microbubble cavitation: results from a phase 2 clinical trial.Cancer letters · 2025Trial
- Response evaluation to systemic therapy in HCC: Current challenges and future perspectives.Hepatology (Baltimore, Md.) · 2026Review
- Prognostic factors and treatment response in previously treated hepatocellular carcinoma patients receiving Y-90 radioembolization combined with targeted-immunotherapy: an exploratory analysis.Abdominal radiology (New York) · 2026Article
- MRI after Interventional Therapy of Hepatocellular Carcinoma: Typical Changes over Time.RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin · 2026Review
- Role of MRI in Imaging Assessment of Radiation-Based Treatment of Hepatocellular Carcinoma.Cancers · 2026Review
- Hepatocellular carcinoma treatment response: Imaging findings and criteria.World journal of radiology · 2025Review
- Real-world outcomes of selective internal radiation therapy withFuture oncology (London, England) · 2025Observational
- Sorafenib with or without co-interventions for hepatocellular carcinoma.The Cochrane database of systematic reviews · 2025Review
- Prognostic value of early response in predicting survival in hepatocellular carcinoma patients treated with selective internal radiation therapy.European radiology · 2025Article
- Proposal of discontinuation criteria of atezolizumab plus bevacizumab after curative conversion therapy for unresectable early-to-intermediate-stage hepatocellular carcinoma: a multicenter proof-of-concept study.Journal of gastroenterology · 2025Article
- Bioengineered Organoids Offer New Possibilities for Liver Cancer Studies: A Review of Key Milestones and Challenges.Bioengineering (Basel, Switzerland) · 2024Review
- Assessment of LI-RADS efficacy in classification of hepatocellular carcinoma and benign liver nodules using DCE-MRI features and machine learning.European journal of radiology open · 2023Article
- Four-dimensional flow MR imaging for evaluating treatment response after transcatheter arterial chemoembolization in cirrhotic patients with hepatocellular carcinoma.La Radiologia medica · 2023Article
- Drug-Off Criteria in Patients with Hepatocellular Carcinoma Who Achieved Clinical Complete Response after Combination Immunotherapy Combined with Locoregional Therapy.Liver cancer · 2023Article
- Detection of Liver Tumour Using Deep Learning Based Segmentation with Coot Extreme Learning Model.Biomedicines · 2023Article
- Immunotherapy Assessment: A New Paradigm for Radiologists.Diagnostics (Basel, Switzerland) · 2023Review
- Liver Imaging Reporting and Data System (LI-RADS) v2018: differential diagnostic value of ADC values for benign and malignant nodules with moderate probability (LR-3).Frontiers in oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The goal of assessing tumour response on imaging is to identify patients who are likely to benefit - or not - from anticancer treatment, especially in relation to survival. The World Health Organization was the first to develop assessment criteria. This early score, which assessed tumour burden by standardising lesion size measurements, laid the groundwork for many of the criteria that followed. This was then improved by the Response Evaluation Criteria in Solid Tumours (RECIST) which was quickly adopted by the oncology community. At the same time, many interventional oncology treatments were developed to target specific features of liver tumours that result in significant changes in tumours but have little effect on tumour size. New criteria focusing on the viable part of tumours were therefore designed to provide more appropriate feedback to guide patient management. Targeted therapy has resulted in a breakthrough that challenges conventional response criteria due to the non-linear relationship between response and tumour size, requiring the development of methods that emphasize the appearance of tumours. More recently, research into functional and quantitative imaging has created new opportunities in liver imaging. These results have suggested that certain parameters could serve as early predictors of response or could predict later tumour response at baseline. These approaches have now been extended by machine learning and deep learning. This clinical review focuses on the progress made in the evaluation of liver tumours on imaging, discussing the rationale for this approach, addressing challenges and controversies in the field, and suggesting possible future developments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.