ArticleEuropean radiology2023
Radiomics nomogram for the prediction of microvascular invasion of HCC and patients' benefit from postoperative adjuvant TACE: a multi-center study.
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 29 papers, 1 of them a synthesis that pooled it.
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29 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Advancing Diagnostic Accuracy in Liver Cancer: A Systematic Review of Artificial Intelligence Applications in Hepatocellular Carcinoma and Cholangiocarcinoma Detection Using Abdominal CT Imaging.Asian Pacific journal of cancer prevention : APJCP · 2026Pooled it
- Machine learning models based on MRI predict the expression levels of Galectin - 9 expression in rectal cancer.Abdominal radiology (New York) · 2026Article
- CRAF-Net: A Fine-Grained Cross-Channel Attention Network for Preoperative Microvascular Invasion Grading in Hepatocellular Carcinoma via DCE-MRI.Journal of imaging informatics in medicine · 2026Article
- Article
- Intra-ablational and peri-ablational radiomics based on post-RFA gadoxetic acid disodium-enhanced MRI for predicting short-term prognosis in hepatocellular carcinoma.Abdominal radiology (New York) · 2026Article
- Visualized Clinical-Radiomics Model Based on Non-Contrast Computed Tomography for Predicting Efficacy of Surufatinib in Hepatic Metastases of Neuroendocrine Neoplasms.Cancer medicine · 2026Article
- A deep learning radiopathomic signature predicts recurrence risk of hepatocellular carcinoma after hepatectomy.Communications biology · 2026Article
- Preoperative Prediction of TACE Refractoriness in Hepatocellular Carcinoma Using CT-Based Radiomics Model.Journal of hepatocellular carcinoma · 2026Article
- Contrast-Enhanced CT Shell Features and Deep Learning for Predicting Early Transarterial Chemoembolization Refractoriness in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2026Article
- A Multimodal Diagnostic Model for Hepatocellular Carcinoma Integrating Biomarkers Related to Programmed Cell Death and Radiomics Features.Current medicinal chemistry · 2026Article
- Emerging Role of MRI-Based Artificial Intelligence in Individualized Treatment Strategies for Hepatocellular Carcinoma: A Narrative Review.Journal of magnetic resonance imaging : JMRI · 2026Review
- Missing Postoperative Adjuvant Therapy Seriously Interferes with the Attribution Analysis of Non-transplant Recurrence in Hepatocellular Carcinoma.Annals of surgical oncology · 2026Article
- Artificial Intelligence and Radiomics in Primary Liver Cancer Imaging: A Bibliometric and Visualized Analysis.Journal of hepatocellular carcinoma · 2026Article
- Revisiting the role of postoperative adjuvant transarterial chemoembolization in hepatocellular carcinoma: a propensity score matching analysis.Journal of gastrointestinal oncology · 2025Article
- Development of a nomogram for predicting microvascular invasion in patients with hepatocellular carcinoma.BMC cancer · 2025Article
- Review
- Predicting the outcome of transarterial chemoembolization combined with targeted immunotherapy for unresectable hepatocellular carcinoma based on MRI radiomics.Scientific reports · 2025Article
- From texture analysis to artificial intelligence: global research landscape and evolutionary trajectory of radiomics in hepatocellular carcinoma.Discover oncology · 2025Article
- Current Advances in Classification, Prediction and Management of Microvascular Invasion in Hepatocellular Carcinoma.Journal of cellular and molecular medicine · 2025Review
- Chinese expert consensus on the diagnosis and treatment of hepatocellular carcinoma with microvascular invasion (2024 edition).Hepatobiliary surgery and nutrition · 2025Review
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12 authors at 5 institutions in 1 country.
Funding
Abstract
objectivesTo evaluate the performance of a radiomics nomogram developed based on gadolinium-ethoxybenzyl-diethylenetriamine penta-acetic acid (Gd-EOB-DTPA) MRI for preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC), and to identify patients who may benefit from the postoperative adjuvant transarterial chemoembolization (PA-TACE).
methodsA total of 260 eligible patients were retrospectively enrolled from three hospitals (140, 65, and 55 in training, standardized external, and non-standardized external validation cohort). Radiomics features and image characteristics were extracted from Gd-EOB-DTPA MRI image before hepatectomy for each lesion. In the training cohort, a radiomics nomogram which incorporated the radiomics signature and radiological predictors was developed. The performance of the radiomics nomogram was assessed with respect to discrimination calibration, and clinical usefulness with external validation. A score (m-score) was constructed to stratify the patients and explored whether it could accurately predict patient who benefit from PA-TACE.
resultsA radiomics nomogram integrated with the radiomics signature, max-D(iameter) > 5.1 cm, peritumoral low intensity (PTLI), incomplete capsule, and irregular morphology had favorable discrimination in the training cohort (AUC = 0.982), the standardized external validation cohort (AUC = 0.969), and the non-standardized external validation cohort (AUC = 0.981). Decision curve analysis confirmed the clinical usefulness of the novel radiomics nomogram. The log-rank test revealed that PA-TACE significantly decreased the early recurrence in the high-risk group (p = 0.006) with no significant effect in the low-risk group (p = 0.270).
conclusionsThe novel radiomics nomogram combining the radiomics signature and clinical radiological features achieved preoperative non-invasive MVI risk prediction and patient benefit assessment after PA-TACE, which may help clinicians implement more appropriate interventions. CLINICAL RELEVANCE STATEMENT: Our radiomics nomogram could represent a novel biomarker to identify patients who may benefit from the postoperative adjuvant transarterial chemoembolization, which may help clinicians to implement more appropriate interventions and perform individualized precision therapies. KEY POINTS: • The novel radiomics nomogram developed based on Gd-EOB-DTPA MRI achieved preoperative non-invasive MVI risk prediction. • An m-score based on the radiomics nomogram could stratify HCC patients and further identify individuals who may benefit from the PA-TACE. • The radiomics nomogram could help clinicians to implement more appropriate interventions and perform individualized precision therapies.
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