ReviewHepatology international2019
Radiomics in hepatocellular carcinoma: a quantitative review.
Review in Hepatology international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers, 7 of them syntheses that pooled it.
What it found
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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.
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Who cites it
91 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative.European radiology · 2023Pooled it
- Cardiac CT and MRI radiomics: systematic review of the literature and radiomics quality score assessment.European radiology · 2022Pooled it
- Systematic review: radiomics for the diagnosis and prognosis of hepatocellular carcinoma.Alimentary pharmacology & therapeutics · 2021Pooled it
- Current progress and quality of radiomic studies for predicting EGFR mutation in patients with non-small cell lung cancer using PET/CT images: a systematic review.The British journal of radiology · 2021Pooled it
- Pancreas image mining: a systematic review of radiomics.European radiology · 2021Pooled it
- A systematic review of radiomics in osteosarcoma: utilizing radiomics quality score as a tool promoting clinical translation.European radiology · 2021Pooled it
- Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis.Frontiers in oncology · 2020Pooled it
- Comparative analysis of radiomics and deep-learning algorithms for survival prediction in hepatocellular carcinoma.Scientific reports · 2024Trial
- Using pre-operative radiomics to predict microvascular invasion of hepatocellular carcinoma based on Gd-EOB-DTPA enhanced MRI.BMC medical imaging · 2022Trial
- Comprehensive radiomics nomogram for predicting survival of patients with combined hepatocellular carcinoma and cholangiocarcinoma.World journal of gastroenterology · 2021Trial
- Preoperative prediction of early recurrence and microvascular invasion in hepatocellular carcinoma using conventional ultrasound, elastography, and clinical nutritional indicators: a radiomics-based study.American journal of translational research · 2026Article
- A deep learning and radiomics fusion model enhances endoscopic ultrasonography diagnosis of gastric tumors.Frontiers in oncology · 2026Article
- Preoperative Prediction of TACE Refractoriness in Hepatocellular Carcinoma Using CT-Based Radiomics Model.Journal of hepatocellular carcinoma · 2026Article
- Using Machine Learning to Predict Advanced-Stage Progression of Intermediate-Stage Hepatocellular Carcinoma after Transarterial Chemoembolization.Radiology. Imaging cancer · 2025Article
- New frontiers in hepatocellular carcinoma: Precision imaging for microvascular invasion prediction.World journal of gastroenterology · 2025Article
- Article
- Early Enhancement in Contrast-Enhanced Computed Tomography Is an Index ofVeterinary sciences · 2025Article
- CT Radiomics Combined with Metabolic-Biomarkers Enables Early Recurrence Prediction in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025Article
- Article
- A deep learning model for personalized intra-arterial therapy planning in unresectable hepatocellular carcinoma: a multicenter retrospective study.EClinicalMedicine · 2024Article
31 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Radiomics is an emerging field which extracts quantitative radiology data from medical images and explores their correlation with clinical outcomes in a non-invasive manner. This review aims to assess whether radiomics is a useful and reproducible method for clinical management of hepatocellular carcinoma (HCC) by reviewing the strengths and weaknesses of current radiomics literature pertaining specifically to HCC. From an initial set of 48 articles recovered through database searches, 23 articles were retained to be included in this review after full screening. Among these 23 studies, 7 used a radiomics approach in magnetic resonance imaging (MRI). Only two studies applied radiomics to positron emission tomography-computed tomography (PET-CT). In the remaining 14 articles, a radiomics analysis was performed on computed tomography (CT). Eight studies dealt with the relationship between biological signatures and imaging findings, and can be classified as radiogenomic studies. For each study included in our review, we computed a Radiomics Quality Score (RQS) as proposed by Lambin et al. We found that the RQS (mean ± standard deviation) was 8.35 ± 5.38 (out of a possible maximum value of 36). Although these scores are fairly low, and radiomics has not yet reached clinical utility in HCC, it is important to underscore the fact that these early studies pave the way for the radiomics field with a focus on HCC. Radiomics is still a very young field, and is far from being mature, but it remains a very promising technology for the future for developing adequate personalized treatment as a non-invasive approach, for complementing or replacing tumor biopsies, as well as for developing novel prognostic biomarkers in HCC patients.
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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.