ArticleiLIVER2025
Multiphase MRI radiomics model for predicting microvascular invasion in HCC: Development and clinical validation.
Article in iLIVER, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Artificial intelligence-enabled clinical decision support systems in preadmission testing: a scoping review of risk prediction, triage, and perioperative workflows (2020-2025).Journal of clinical monitoring and computing · 2026Article
- Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and aims: Accurate preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is crucial for treatment planning. This study aimed to develop and validate a multi-phase magnetic resonance imaging (MRI)-based radiomics model for predicting MVI in HCC patients. Methods: This retrospective study included 110 HCC patients (training: Results: The four-phase radiomics model with logistic regression classifier showed optimal performance in both the training (AUC = 0.896; 95% confidence interval, 0.792-0.963) and validation cohorts (AUC = 0.889, 95% confidence interval, 0.781-0.982), outperforming the single-phase (AUC = 0.789), two-phase (AUC = 0.815), and three-phase models (AUC = 0.848) in the validation cohort. In the validation cohort, the model achieved balanced performance with sensitivity, specificity, accuracy, and precision all reaching 0.857. Conclusions: The multi-phase MRI-based radiomics model significantly improves MVI prediction accuracy in HCC patients. This non-invasive approach could enhance preoperative assessment and treatment planning.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.