ArticleEuropean radiology2023
CT-based radiomics nomogram for prediction of survival after transarterial chemoembolization with drug-eluting beads in patients with hepatocellular carcinoma and portal vein tumor thrombus.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
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12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 14 citations in OpenAlex.
- Performance of Artificial Intelligence Models in Predicting Responsiveness of Hepatocellular Carcinoma to Transarterial Chemoembolization (TACE): A Systematic Review and Meta-Analysis.Journal of the American College of Radiology : JACR · 2026Pooled it
- Artificial Intelligence and Machine Learning Predicting Transarterial Chemoembolization Outcomes: A Systematic Review.Digestive diseases and sciences · 2025Pooled it
- Development and validation of a prognostic nomogram for predicting the progression risk of HCC after lenvatinib therapy.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Predicting the outcome of transarterial chemoembolization combined with targeted immunotherapy for unresectable hepatocellular carcinoma based on MRI radiomics.Scientific reports · 2025Article
- MRI Radiomics to Predict Early Treatment Response to TACE Combined with Lenvatinib Plus a PD-1 Inhibitor for Hepatocellular Carcinoma with Portal Vein Tumor Thrombus.Journal of hepatocellular carcinoma · 2025Article
- The heterogeneity of cellular metabolism in the tumour microenvironment of hepatocellular carcinoma with portal vein tumour thrombus.Cell proliferation · 2025Article
- Establishing a Survival Time Prediction Model for Patients with Hepatocellular Carcinoma After TACE Based on CT Radiomics: A Multi-Center Study.Journal of hepatocellular carcinoma · 2025Article
- Prognostic analysis of different postoperative adjuvant therapies for patients with hepatocellular carcinoma after radical resection with high-risk recurrence factors: a multicenter real-world retrospective study.Frontiers in immunology · 2025Article
- Deep-learning radiomics and hand-crafted radiomics utilizing contrast-enhanced MRI to predict early peritumoral recurrence after DEB-TACE with hepatocellular carcinoma: a two-center study.Frontiers in oncology · 2025Article
- Development and verification of a nomogram for predicting portal vein tumor thrombosis in hepatocellular carcinoma.American journal of translational research · 2024Article
- Development and Validation of a Novel Prognostic Nomogram Based on Platelet and CD8Journal of hepatocellular carcinoma · 2024Article
- Research Progress in Predicting Hepatocellular Carcinoma with Portal Vein Tumour Thrombus in the Era of Artificial Intelligence.Journal of hepatocellular carcinoma · 2024Review
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5 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
objectivesTo develop and validate a CT-based radiomics model for the prediction of the overall survival (OS) of patients with hepatocellular carcinoma (HCC) and portal vein tumor thrombus (PVTT) treated with drug-eluting beads transarterial chemoembolization (DEB-TACE).
methodsPatients were retrospectively enrolled from two institutions for the constitution of training (n = 69) and validation (n = 31) cohorts with a median follow-up of 15 months. A total of 396 radiomics features were extracted from each baseline CT image. Features selected by variable importance and minimal depth were used for random survival forest model construction. The performance of the model was assessed using the concordance index (C-index), calibration curves, integrated discrimination index (IDI), net reclassification index (NRI), and decision curve analysis.
resultsType of PVTT and tumor number were proved to be significant clinical indicators for OS. Arterial phase images were used to extract radiomics features. Three radiomics features were selected for model construction. The C-index for the radiomics model was 0.759 in the training cohort and 0.730 in the validation cohort. To improve the predictive performance, clinical indicators were integrated into the radiomics model to form a combined model with a C-index of 0.814 in the training cohort and 0.792 in the validation cohort. The IDI was significant in both cohorts for the combined model versus the radiomics model in predicting 12-month OS.
conclusionsType of PVTT and tumor number affected the OS of HCC patients with PVTT treated with DEB-TACE. Moreover, the combined clinical-radiomics model had a satisfactory performance. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics nomogram, which consisted of 3 radiomics features and 2 clinical indicators, was recommended to predict 12-month overall survival of patients with hepatocellular carcinoma and portal vein tumor thrombus initially treated with drug-eluting beads transarterial chemoembolization. KEY POINTS: • Type of portal vein tumor thrombus and tumor number were significant predictors of the OS. • Integrated discrimination index and net reclassification index provided a quantitative evaluation of the incremental impact added by new indicators for the radiomics model. • A nomogram based on a radiomics signature and clinical indicators showed satisfactory performance in predicting OS after DEB-TACE.
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