ArticleOncology letters2024
Preoperative prediction of microvascular invasion classification in hepatocellular carcinoma based on clinical features and MRI parameters.
Article in Oncology letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Gadoxetic Acid-enhanced MRI Radiomics Features of Tumor Margins for Predicting High-Risk Solitary Hepatocellular Carcinoma Aggressiveness and Prognosis.Radiology. Imaging cancer · 2026Article
- Advancing microvascular invasion diagnosis: a multi-center investigation of novel MRI-based models for precise detection and classification in early-stage small hepatocellular carcinoma (≤ 3 cm).Abdominal radiology (New York) · 2025Article
- Article
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5 authors.
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Abstract
Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a critical pathological factor and the degree of MVI influences treatment decisions and patient prognosis. The present study aimed to predict the MVI classification based on preoperative MRI features and clinical parameters. The present retrospective cohort study included 150 patients (training cohort, n=108; validation cohort, n=42) with pathologically confirmed HCC. Clinical and imaging characteristics data were collected from Shengli Oilfield Central Hospital (Dongying, China). Univariate and multivariate logistic regression analyses were conducted to assess the association of clinical variables and MRI parameters with MVI (grade M1 and M2) and the M2 classification. Nomograms were developed based on the predictive factors of MVI and the M2 classification. The discrimination capability, calibration and clinical usefulness of the nomograms were evaluated. Multivariate analysis revealed an association between the
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