ArticleWorld journal of surgical oncology2022
Deep-learning-based analysis of preoperative MRI predicts microvascular invasion and outcome in hepatocellular carcinoma.
Article in World journal of surgical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy of Medical Image-Based Deep Learning for Detecting Microvascular Invasion in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- A novel deep learning and radiomics approach based on DCE-MRI for predicting the P53 mutation status in hepatocellular carcinoma.Journal of gastrointestinal oncology · 2026Article
- Impact of Annotation Level on Multisequence MRI Models for Preoperative Microvascular Invasion Prediction in Hepatocellular Carcinoma.Radiology. Imaging cancer · 2026Article
- Evaluation of therapeutic efficacy in hepatocellular carcinoma ablation based on CT radiomics and deep learning multimodal models.Frontiers in oncology · 2026Article
- A Transformer-Based Deep Learning Model for predicting Early Recurrence in Hepatocellular Carcinoma After Hepatectomy Using Intravoxel Incoherent Motion Images.Journal of hepatocellular carcinoma · 2026Article
- Interpretable and generalizable deep learning model for preoperative assessment of microvascular invasion and outcome in hepatocellular carcinoma based on MRI: a multicenter study.Insights into imaging · 2025Article
- Chinese expert consensus on the diagnosis and treatment of hepatocellular carcinoma with microvascular invasion (2024 edition).Hepatobiliary surgery and nutrition · 2025Review
- Microvascular invasion and early recurrence of hepatocellular carcinoma after CT-guided radiofrequency ablation: risk factor analysis.Frontiers in oncology · 2025Article
- Effective Tumor Annotation for Automated Diagnosis of Liver Cancer.IEEE journal of translational engineering in health and medicine · 2025Article
- Liver Transplant in Patients with Hepatocarcinoma: Imaging Guidelines and Future Perspectives Using Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2023Review
- Development and validation of a nomogram to predict the recurrence of hepatocellular carcinoma patients with dynamic changes in AFP undergoing locoregional treatments.Frontiers in oncology · 2023Article
- Lenvatinib plus anti-PD-1 therapy represents a feasible conversion resection strategy for patients with initially unresectable hepatocellular carcinoma: A retrospective study.Frontiers in oncology · 2022Article
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16 authors.
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Abstract
backgroundPreoperative prediction of microvascular invasion (MVI) is critical for treatment strategy making in patients with hepatocellular carcinoma (HCC). We aimed to develop a deep learning (DL) model based on preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict the MVI status and clinical outcomes in patients with HCC.
methodsWe retrospectively included a total of 321 HCC patients with pathologically confirmed MVI status. Preoperative DCE-MRI of these patients were collected, annotated, and further analyzed by DL in this study. A predictive model for MVI integrating DL-predicted MVI status (DL-MVI) and clinical parameters was constructed with multivariate logistic regression.
resultsOf 321 HCC patients, 136 patients were pathologically MVI absent and 185 patients were MVI present. Recurrence-free survival (RFS) and overall survival (OS) were significantly different between the DL-predicted MVI-absent and MVI-present. Among all clinical variables, only DL-predicted MVI status and a-fetoprotein (AFP) were independently associated with MVI: DL-MVI (odds ratio [OR] = 35.738; 95% confidence interval [CI] 14.027-91.056; p < 0.001), AFP (OR = 4.634, 95% CI 2.576-8.336; p < 0.001). To predict the presence of MVI, DL-MVI combined with AFP achieved an area under the curve (AUC) of 0.824.
conclusionsOur predictive model combining DL-MVI and AFP achieved good performance for predicting MVI and clinical outcomes in patients with HCC.
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