ArticleEuropean radiology2019
Predicting the grade of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04299919 (The Artificial Intelligent Prognostic Assessment and Pathological Basis Research of Early Primary Hepatocellular Carcinoma After Minimally Invasive Treatment Based on Multimodal MRI and Clinical Big Data), which is not on this map. Cited by 105 papers, 2 of them syntheses that pooled it.
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The Artificial Intelligent Prognostic Assessment and Pathological Basis Research of Early Primary Hepatocellular Carcinoma After Minimally Invasive Treatment Based on Multimodal MRI and Clinical Big Data
Who cites it
105 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Research progress of MRI-based radiomics in hepatocellular carcinoma.Frontiers in oncology · 2025Pooled it
- Systematic review: radiomics for the diagnosis and prognosis of hepatocellular carcinoma.Alimentary pharmacology & therapeutics · 2021Pooled it
- Qualitative and quantitative assessment of intratumoral fat using chemical-shift MRI for predicting histological grade of hepatocellular carcinoma.BMC medical imaging · 2026Article
- Radiomics predicts poorly differentiated hepatocellular carcinoma and uncovers ribosomal-immune dysregulation mechanism.iScience · 2026Article
- Development and Validation of a Clinical Radiomics Nomogram for Predicting Early Recurrence After Microwave Ablation in Hepatocellular Carcinoma Patients With Type 2 Diabetes.Cancer management and research · 2026Article
- Establishment and validation of a CT-based clinical deep learning radiomics nomogram for predicting the response to transcatheter arterial chemoembolization in patients with hepatocellular carcinoma.Frontiers in oncology · 2026Article
- Interpretable model based on multisequence magnetic resonance imaging radiomics for predicting the pathological grades of hepatocellular carcinomas.World journal of radiology · 2025Article
- MRI-based habitat radiomics and deep learning for predicting vessels encapsulating tumor clusters and survival in hepatocellular carcinoma.Insights into imaging · 2025Article
- Magnetic resonance imaging radiomics-based machine learning model for preoperative prediction of pathological grade in pancreatic cancer: A preliminary study.European journal of radiology open · 2025Article
- Prediction of Histopathological Grade of Hepatocellular Carcinoma by Gadoxetic Acid-Enhanced Magnetic Resonance Imaging Radiomics Features.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2025Article
- Radiomics-based prediction of HCC response to atezolizumab/bevacizumab.Oncology letters · 2025Article
- Targeting Glypican-3 for Liver Cancer Therapy: Clinical Applications and Detection Methods.Journal of clinical and translational hepatology · 2025Review
- Progress in the application of fludeoxyglucose positron emission tomography computed tomography in biliary tract cancer.World journal of hepatology · 2025Review
- MRI Imaging Biomarkers for Prognostication of Hepatocellular Carcinoma.Journal of the Korean Society of Radiology · 2025Review
- Prognostic impact of extracellular volume fraction derived from equilibrium contrast-enhanced CT in HCC patients receiving immune checkpoint inhibitors.Scientific reports · 2025Article
- Article
- Deep Learning Radiopathomics Models Based on Contrast-enhanced MRI and Pathologic Imaging for Predicting Vessels Encapsulating Tumor Clusters and Prognosis in Hepatocellular Carcinoma.Radiology. Imaging cancer · 2025Article
- Evaluation of combined hepatocellular-cholangiocarcinoma using CEUS LI-RADS: correlation with pathological characteristics.Abdominal radiology (New York) · 2025Article
- Artificial Intelligence and Radiomics in Cholangiocarcinoma: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2025Review
- Triphasic CT Radiomics Model for Preoperative Prediction of Hepatocellular Carcinoma Pathological Grading.Journal of hepatocellular carcinoma · 2025Article
45 more citing papers are in PubMed but not listed here.
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10 authors.
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Abstract
purposeThis study was conducted in order to investigate the value of magnetic resonance imaging (MRI)-based radiomics signatures for the preoperative prediction of hepatocellular carcinoma (HCC) grade.
methodsData from 170 patients confirmed to have HCC by surgical pathology were divided into a training group (n = 125) and a test group (n = 45). The radiomics features of tumours based on both T1-weighted imaging (WI) and T2WI were extracted by using Matrix Laboratory (MATLAB), and radiomics signatures were generated using the least absolute shrinkage and selection operator (LASSO) logistic regression model. The predicted values of pathological HCC grades using radiomics signatures, clinical factors (including age, sex, tumour size, alpha fetoprotein (AFP) level, history of hepatitis B, hepatocirrhosis, portal vein tumour thrombosis, portal hypertension and pseudocapsule) and the combined models were assessed.
resultsRadiomics signatures could successfully categorise high-grade and low-grade HCC cases (p < 0.05) in both the training and test datasets. Regarding the performances of clinical factors, radiomics signatures and the combined clinical and radiomics signature (from the combined T1WI and T2WI images) models for HCC grading prediction, the areas under the curve (AUCs) were 0.600, 0.742 and 0.800 in the test datasets, respectively. Both the AFP level and radiomics signature were independent predictors of HCC grade (p < 0.05).
conclusionsRadiomics signatures may be important for discriminating high-grade and low-grade HCC cases. The combination of the radiomics signatures with clinical factors may be helpful for the preoperative prediction of HCC grade. KEY POINTS: • The radiomics signature based on non-contrast-enhanced MR images was significantly associated with the pathological grade of HCC. • The radiomics signatures based on T1WI or T2WI images performed similarly at predicting the pathological grade of HCC. • Combining the radiomics signature and clinical factors (including age, sex, tumour size, AFP level, history of hepatitis B, hepatocirrhosis, portal vein tumour thrombosis, portal hypertension and pseudocapsule) may be helpful for the preoperative prediction of HCC grade.
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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.