ArticleJournal of hepatocellular carcinoma2022
Preoperative Radiomics Analysis of Contrast-Enhanced CT for Microvascular Invasion and Prognosis Stratification in Hepatocellular Carcinoma.
Article in Journal of hepatocellular carcinoma, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Computed tomography-based artificial intelligence for predicting preoperative microvascular invasion in hepatocellular carcinoma: a systematic review and meta-analysis.La Radiologia medica · 2026Pooled it
- Interpretable stacking model integrating intra-/peritumoral CT-radiomics and serum biomarkers for predicting microvascular invasion in HCC: a dual-center retrospective study.BMC gastroenterology · 2026Article
- Pathological features and biomarkers of hepatocellular carcinoma: a bibliometric analysis from 2005 to 2025.Translational cancer research · 2026Article
- Dynamic Vascular Spatiotemporal Heterogeneity on Multiphase CT for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2026Article
- [Diagnosis and treatment of liver diseases in the era of artificial intelligence].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2025Review
- Development of a nomogram for predicting microvascular invasion in patients with hepatocellular carcinoma.BMC cancer · 2025Article
- Preoperative prediction of microvascular invasion and relapse-free survival in hepatocellular Carcinoma ≥3 cm using CT radiomics: Development and external validation.BMC medical imaging · 2025Article
- Article
- Predictive value of a constructed artificial neural network model for microvascular invasion in hepatocellular carcinoma: A retrospective study.World journal of gastrointestinal oncology · 2025Article
- Correlation Between Dynamic Contrast-Enhanced CT Imaging Signs and Differentiation Grade and Microvascular Invasion of Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025Article
- Early identification of hepatocellular carcinoma patients at high-risk of recurrence using the ADV score: a multicenter retrospective study.World journal of surgical oncology · 2024Article
- Preoperative prediction of microvascular invasion: new insights into personalized therapy for early-stage hepatocellular carcinoma.Quantitative imaging in medicine and surgery · 2024Review
- Article
- A Nomogram of Magnetic Resonance Imaging for Preoperative Assessment of Microvascular Invasion and Prognosis of Hepatocellular Carcinoma.Digestive diseases and sciences · 2023Article
- Review
- Increased Platelet Distribution Width Predicts 3-Year Recurrence in Patients with Hepatocellular Carcinoma After Surgical Resection.Cancer management and research · 2023Article
- From imaging to clinical outcome: dual-region CT radiomics predicting FOXM1 expression and prognosis in hepatocellular carcinoma.Frontiers in oncology · 2023Article
- Role of radiomics in the diagnosis and treatment of gastrointestinal cancer.World journal of gastroenterology · 2022Review
- Accurate prediction of microvascular invasion occurrence and effective prognostic estimation for patients with hepatocellular carcinoma after radical surgical treatment.World journal of surgical oncology · 2022Article
- [Research progress in radiomics based on CT and MRI images for prediction of microvascular invasion in hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2022Article
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11 authors.
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Abstract
Purpose: Microvascular invasion (MVI) impairs long-term prognosis of patients with hepatocellular carcinoma (HCC). We aimed to develop a novel nomogram to predict MVI and patients' prognosis based on radiomic features of contrast-enhanced CT (CECT). Patients and Methods: HCC patients who underwent curative resection were enrolled. The radiomic features were extracted from the region of tumor, and the optimal MVI-related radiomic features were selected and applied to construct radiomic signature (Rad-score). The prediction models were created according to the logistic regression and evaluated. Biomarkers were analyzed via q-PCR from randomly selected HCC patients. Correlations between biomarkers and radiomic signature were analyzed. Results: A total of 421 HCC patients were enrolled. A total of 1962 radiomic features were extracted from the region of tumor, and the 11 optimal MVI-related radiomic features showed a favor predictive ability with area under the curves (AUCs) of 0.796 and 0.810 in training and validation cohorts, respectively. Aspartate aminotransferase (AST), tumor number, alpha-fetoprotein (AFP) level, and radiomics signature were independent risk factors of MVI. The four factors were integrated into the novel nomogram, named as CRM, with AUCs of 0.767 in training cohort and 0.793 in validation cohort for predicting MVI, best among radiomics signature alone and clinical model. The nomogram was well-calibrated with favorable clinical value demonstrated by decision curve analysis and can divide patients into high- or low-risk subgroups of recurrence and mortality. In addition, gene BCAT1, DTGCU2, DOCK3 were analyzed via q-PCR and serum AFP were identified as having significant association with radiomics signature. Conclusion: The novel nomogram demonstrated good performance in preoperatively predicting the probability of MVI, which might guide clinical decision.
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