ArticleInsights into imaging2024
Multiparametric MRI-based intratumoral and peritumoral radiomics for predicting the pathological differentiation of hepatocellular carcinoma.
Article in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- "Liver stiffness variations after locoregional treatment do not predict outcomes in liver cancer: limitations of elastography as a prognostic tool".Abdominal radiology (New York) · 2026Article
- APASA: adaptive selection of informative peritumoral regions for improved automated cancer lesion analysis.Scientific reports · 2026Article
- Prediction of Ki-67 expression in hepatocellular carcinoma: a dual-center study based on T2-weighted imaging habitat analysis.Radiology and oncology · 2026Article
- 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
- Multicenter peritumoral radiomics in oncology: advances, challenges, and future directions.Radiation oncology (London, England) · 2026Review
- Gadoxetic Acid-enhanced MRI Radiomics Features of Tumor Margins for Predicting High-Risk Solitary Hepatocellular Carcinoma Aggressiveness and Prognosis.Radiology. Imaging cancer · 2026Article
- Interpretable ensemble learning model using intratumoral and peritumoral multi-sequence MR-radiomics predicts high-grade cervical cancer with lymphovascular space invasion.Frontiers in oncology · 2026Article
- Leveraging vision transformer for histological grade prediction in laryngeal and hypopharyngeal squamous cell carcinoma: a large-scale multicenter study.Neuroradiology · 2026Article
- Interpretable machine learning integrating intra-/peritumoral CT radiomics and serum indicators for predicting poorly differentiated esophageal squamous cell carcinoma.Frontiers in oncology · 2026Article
- Intratumoral and peritumoral radiomics of MRI predict pathological differentiation in patients with rectal cancer.Oncology letters · 2026Article
- A fusion model based on tumor and peritumoral CT radiomics for differentiating bronchiolar adenoma from lung adenocarcinoma.Frontiers in oncology · 2026Article
- MRI Radiomics for Distinguishing HBV-Related Early Hepatocellular Carcinoma from Precancerous Nodules.Journal of hepatocellular carcinoma · 2026Article
- MRI Radiomics-Based Evaluation of Vessels Encapsulating Tumor Clusters and Microvascular Invasion in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2026Article
- Development and validation of a DWI-based intra- and peri-infarction radiomics model for predicting neurological deterioration in acute ischemic stroke.Frontiers in neurology · 2026Article
- Interpretable model based on multisequence magnetic resonance imaging radiomics for predicting the pathological grades of hepatocellular carcinomas.World journal of radiology · 2025Article
- Radiomics-based prediction of HCC response to atezolizumab/bevacizumab.Oncology letters · 2025Article
- Multiparametric magnetic resonance imaging of deep learning-based super-resolution reconstruction for predicting histopathologic grade in hepatocellular carcinoma.World journal of gastroenterology · 2025Article
- Integrative radiomics of intra- and peri-tumoral features for enhanced risk prediction in thymic tumors: a multimodal analysis of tumor microenvironment contributions.BMC medical imaging · 2025Article
- Radiomics analysis based on dynamic contrast-enhanced MRI for predicting early recurrence after hepatectomy in hepatocellular carcinoma patients.Scientific reports · 2025Article
- Preoperative model for predicting early recurrence in hepatocellular carcinoma patients using radiomics and deep learning: A multicenter study.World journal of gastrointestinal oncology · 2025Article
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10 authors.
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Abstract
purposeTo explore the predictive potential of intratumoral and multiregion peritumoral radiomics features extracted from multiparametric MRI for predicting pathological differentiation in hepatocellular carcinoma (HCC) patients.
methodsA total of 265 patients with 277 HCCs (training cohort n = 193, validation cohort n = 84) who underwent preoperative MRI were retrospectively analyzed. The risk factors identified through stepwise regression analysis were utilized to construct a clinical model. Radiomics models based on MRI (arterial phase, portal venous phase, delayed phase) across various regions (entire tumor, Peri_5mm, Peri_10mm, Peri_20mm) were developed using the LASSO approach. The features obtained from the intratumoral region and the optimal peritumoral region were combined to design the IntraPeri fusion model. Model performance was assessed using the area under the curve (AUC).
resultsLarger size, non-smooth margins, and mosaic architecture were risk factors for poorly differentiated HCC (pHCC). The clinical model achieved AUCs of 0.77 and 0.73 in the training and validation cohorts, respectively, while the intratumoral model achieved corresponding AUC values of 0.92 and 0.82. The Peri_10mm model demonstrated superior performance to the Peri_5mm and Peri_20mm models, with AUC values of 0.87 vs. 0.84 vs. 0.73 in the training cohort and 0.80 vs. 0.77 vs. 0.68 in the validation cohort, respectively. The IntraPeri model exhibited remarkable AUC values of 0.95 and 0.86 in predicting pHCC in the training and validation cohorts, respectively.
conclusionsOur study highlights the potential of a multiparametric MRI-based radiomic model that integrates intratumoral and peritumoral features as a tool for predicting HCC differentiation. CRITICAL RELEVANCE STATEMENT: Both clinical and multiparametric MRI-based radiomic models, particularly the intratumoral radiomic model, are non-invasive tools for predicting HCC differentiation. Importantly, the IntraPeri fusion model exhibited remarkable predictiveness for individualized HCC differentiation. KEY POINTS: • Both the intratumoral radiomics model and clinical features were useful for predicting HCC differentiation. • The Peri_10mm radiomics model demonstrated better diagnostic ability than other peritumoral region-based models. • The IntraPeri radiomics fusion model outperformed the other models for predicting HCC differentiation.
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