ArticleQuantitative imaging in medicine and surgery2024
Identification of vessels encapsulating tumor clusters in solitary hepatocellular carcinoma via imaging biomarkers in preoperative contrast-enhanced magnetic resonance imaging.
Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effectiveness of Machine Learning in Detecting Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Preoperative contrast-enhanced CT prediction of distinct vascular patterns in solitary early-stage hepatocellular carcinoma and its prognostic value.Insights into imaging · 2026Article
- The diagnostic accuracy of imaging methods in preoperative prediction of vessels encapsulating tumor clusters in hepatocellular carcinoma in East Asian populations: a systematic review and meta-analysis.Quantitative imaging in medicine and surgery · 2026Article
- Spectral computed tomography parameters for predicting vessels encapsulating tumor clusters (VETC) pattern in hepatocellular carcinoma: a pilot study.Quantitative imaging in medicine and surgery · 2025Article
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11 authors.
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Abstract
Background: The value of Liver Imaging Reporting and Data System (LI-RADS) radiological features and tumor three-dimensional volumetric quantification in preoperative magnetic resonance imaging (MRI) for predicting the vessels encapsulating tumor clusters (VETC) pattern of solitary hepatocellular carcinoma (HCC) is unknown. This study aimed to assess the value of these indicators for predicting the VETC pattern of solitary HCC. Methods: In total, 36 patients with HCC were selected from a cohort containing 126 patients for further data evaluation. VETC was evaluated by histopathologists, and the three-dimensional tumor volume (TV) was analyzed in the arterial phase (AP) and portal venous phase. LI-RADS radiological characteristics were defined on the basis of LI-RADS version 2018. Quantitative parameters were derived from multiparametric MRI data. Significant MRI biomarkers for predicting VETC-positive status in solitary HCC were ascertained via logistic regression analysis. A nomogram was accordingly constructed and evaluated in terms of discrimination, calibration, clinical utility, and accuracy. Results: A total of 15 cases were VETC positive, while 21 cases were VETC negative. The values for nodule-in-nodule architecture, mosaic architecture, total liver volume, TV, necrosis tumor volumetric percentage, necrosis tumor burden, and tumor-to-liver signal intensity (SI) ratio on AP images were higher in VETC-positive HCCs than in VETC-negative HCCs (P<0.05). Multivariate logistic analysis indicated that necrosis tumor volumetric percentage, tumor-to-liver SI ratio on AP images, and nodule-in-nodule architecture were independent predictive factors of VETC status (P<0.05). The calibration and discrimination performance of the nomogram were good, with an area under curve of 0.942, and the prediction accuracy was a satisfactory 88.89%, indicating that the nomogram possessed potential clinical benefits. Conclusions: Preoperative MRI features possess the potential to identify VETC pattern in solitary HCC.
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