ArticleAbdominal radiology (New York)2022
Preoperative application of systemic inflammatory biomarkers combined with MR imaging features in predicting microvascular invasion of hepatocellular carcinoma.
Article in Abdominal radiology (New York), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Article
- 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
- Chinese expert consensus on the diagnosis and treatment of hepatocellular carcinoma with microvascular invasion (2024 edition).Hepatobiliary surgery and nutrition · 2025Review
- Nomograms established for predicting microvascular invasion and early recurrence in patients with small hepatocellular carcinoma.BMC cancer · 2024Article
- Article
- Preoperative evaluation of MRI features and inflammatory biomarkers in predicting microvascular invasion of combined hepatocellular cholangiocarcinoma.Abdominal radiology (New York) · 2024Article
- Multiple Machine-Learning Fusion Model Based on Gd-EOB-DTPA-Enhanced MRI and Aminotransferase-to-Platelet Ratio and Gamma-Glutamyl Transferase-to-Platelet Ratio to Predict Microvascular Invasion in Solitary Hepatocellular Carcinoma: A Multicenter Study.Journal of hepatocellular carcinoma · 2024Article
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6 authors.
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Abstract
purposeTo investigate whether systemic inflammatory biomarkers compared with the imaging features interpreted by radiologists can offer complementary value for predicting the risk of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).
methodsA total of 156 patients with histologically confirmed HCC between Jan 2018 and Dec 2020 were retrospectively enrolled in the primary cohort. Preoperative clinical-inflammatory biomarkers and MR imaging of the patients were recorded and then evaluated as an inflammatory score (Inflam-score) and imaging feature score (Radio-score). Six Inflam-scores and 12 Radio-scores were determined from each patient by univariate analysis. Logistic regression was performed to select risk factors for MVI and establish a predictive nomogram. Decision curve analysis was applied to estimate the incremental value of the Inflam-score to the Radio-score for predicting MVI.
resultsFour Radio-scores and 2 Inflam-scores, namely, larger tumor size, non-smooth tumor margin, presence of satellite nodules, presence of peritumoral enhance, higher neutrophil-lymphocyte ratio (NLR), and lower prognostic nutritional index (PNI), were significantly associated with MVI (p < 0.05). An MVI risk prediction nomogram was then constructed with an area under the curve (AUC) of 0.868 (95% CI 0.806-0.931). Adding Inflam-scores to Radio-scores improved the sensitivity of the model from 60.9 to 80.4% in receiver operating characteristic (ROC) curve analysis and led to a net benefit in decision curve analysis.
conclusionSystemic inflammatory biomarkers are complementary tools that provide additional benefit to conventional imaging estimation for predicting MVI in HCC patients.
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