ArticleLiver cancer2021
Clinical-Radiomic Analysis for Pretreatment Prediction of Objective Response to First Transarterial Chemoembolization in Hepatocellular Carcinoma.
Article in Liver cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05543304 (Predicting Response to Systemic Therapies for Hepatocellular Carcinoma), which is not on this map. Cited by 82 papers, 3 of them syntheses that pooled it.
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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.
Predicting Response to Systemic Therapies for Hepatocellular Carcinoma(HCC) Based on Clinical Variables and Radiomics Data With Machine Learning Methods
Who cites it
82 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Artificial intelligence for the prediction of posthepatectomy recurrence in hepatocellular carcinoma: a systematic review and meta-analysis.Annals of medicine · 2025Pooled it
- Artificial Intelligence and Machine Learning Predicting Transarterial Chemoembolization Outcomes: A Systematic Review.Digestive diseases and sciences · 2025Pooled it
- Radiomics as a tool for prognostic prediction in transarterial chemoembolization for hepatocellular carcinoma: a systematic review and meta-analysis.La Radiologia medica · 2024Pooled it
- Prediction of the efficacy of first transarterial chemoembolization for advanced hepatocellular carcinomaWorld journal of clinical cases · 2025Trial
- Magnetic resonance imaging-based radiomics for predicting P53-mutated hepatocellular carcinoma: intratumoral and peritumoral analysis.Translational cancer research · 2026Article
- A Review on Artificial Intelligence as a Solution to Burnout in Interventional Radiology.Cardiovascular and interventional radiology · 2026Review
- Clinical and LI-RADS features on gadoxetic acid‑enhanced MRI for predicting complete response after transarterial chemoembolization in hepatocellular carcinoma > 2 cm.Abdominal radiology (New York) · 2026Article
- Artificial intelligence-driven CT radiomics model predicts prognosis in TACE-refractory hepatocellular carcinoma.Abdominal radiology (New York) · 2026Article
- Indeterminate nodule-like arterial phase hyperenhancement in the liver on CT: differentiation of hepatocellular carcinomas from vascular pseudolesions using a CT radiomics approach.Journal of gastrointestinal oncology · 2026Article
- MRI-based clinical-radiologic model to predict the efficacy and prognosis of interventional with systemic therapy in advanced hepatocellular carcinoma: a multicenter study.Journal of translational medicine · 2026Article
- Development and validation of a clinical-adipometric nomogram for predicting tumor response to transarterial chemoembolization in hepatocellular carcinoma.Scientific reports · 2026Article
- Clinical MRI-radiomics model based on support vector machine to predict the efficacy of first transarterial chemoembolization for unresectable intrahepatic cholangiocarcinoma.La Radiologia medica · 2026Article
- Interpretable radiomics model based on magnetic resonance imaging to predict responses to transarterial chemoembolization for hepatocellular carcinoma.World journal of radiology · 2026Article
- Integrated primary tumor and all metastatic lymph nodes radiomics from 18 F-FDG PET/CT for precise M1 subclassification in nasopharyngeal carcinoma.BMC cancer · 2026Article
- AI models based on gadoxetic acid-enhanced MRI to predict treatment response and prognosis after TACE in hepatocellular carcinoma.Frontiers in oncology · 2026Article
- Radiomic Analysis Applied to Pretreatment Gd-EOB-DTPA-enhanced MR Imaging Predicts Response to Selective Transcatheter Arterial Chemoembolization for Hepatocellular Carcinoma.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
- Preoperative MVI prediction in intrahepatic cholangiocarcinoma via deep learning analysis of intratumoral and peritumoral features on multi-sequence MRI.BMC medical imaging · 2025Article
- Unresectable ectopic hepatocellular carcinoma in the left sub-diaphragmatic area and retroperitoneum treated with TACE: case report and literature review.Cancer biology & therapy · 2025Review
- China Liver Cancer Guidelines for the Diagnosis and Treatment of Hepatocellular Carcinoma (2024 Edition).Liver cancer · 2025Article
- Quantitative CT Perfusion and Radiomics Reveal Complementary Markers of Treatment Response in HCC Patients Undergoing TACE.Diagnostics (Basel, Switzerland) · 2025Article
22 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe preoperative selection of patients with intermediate-stage hepatocellular carcinoma (HCC) who are likely to have an objective response to first transarterial chemoembolization (TACE) remains challenging.
objectiveTo develop and validate a clinical-radiomic model (CR model) for preoperatively predicting treatment response to first TACE in patients with intermediate-stage HCC.
methodsA total of 595 patients with intermediate-stage HCC were included in this retrospective study. A tumoral and peritumoral (10 mm) radiomic signature (TPR-signature) was constructed based on 3,404 radiomic features from 4 regions of interest. A predictive CR model based on TPR-signature and clinical factors was developed using multivariate logistic regression. Calibration curves and area under the receiver operating characteristic curves (AUCs) were used to evaluate the model's performance.
resultsThe final CR model consisted of 5 independent predictors, including TPR-signature (
conclusionsThe CR model had an excellent performance in predicting the first TACE response in patients with intermediate-stage HCC and could provide a robust predictive tool to assist with the selection of patients for TACE.
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