ArticleEuropean journal of radiology open2024
Construction of a nomogram combining CEUS and MRI imaging for preoperative diagnosis of microvascular invasion in hepatocellular carcinoma.
Article in European journal of radiology open, 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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3 citing papers in PubMed.
- Relationship between contrast-enhanced ultrasound combined with ultrasound resolution microscopy imaging and histological features of hepatocellular carcinoma.Abdominal radiology (New York) · 2025Article
- Role of Superb Microvascular Imaging (SMI) vascularity index values and vascularity patterns in the differential diagnosis of malignant liver lesions.Abdominal radiology (New York) · 2025Article
- Diagnostic value of a lactylation-related gene signature in hepatocellular carcinoma.Translational cancer research · 2025Article
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9 authors.
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Abstract
Purpose: To use Sonazoid contrast-enhanced ultrasound (S-CEUS) and Gadolinium-Ethoxybenzyl-Diethylenetriamine Penta-Acetic Acid magnetic-resonance imaging (EOB-MRI), exploring a non-invasive preoperative diagnostic strategy for microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Methods: 111 newly developed HCC cases were retrospectively collected. Both S-CEUS and EOB-MRI examinations were performed within one month of hepatectomy. The following indicators were investigated: size; vascularity in three phases of S-CEUS; margin, signal intensity, and peritumoral wedge shape in EOB-MRI; tumoral homogeneity, presence and integrity of the tumoral capsule in S-CEUS or EOB-MRI; presence of branching enhancement in S-CEUS; baseline clinical and serological data. The least absolute shrinkage and selection operator regression and multivariate logistic regression analysis were applied to optimize feature selection for the model. A nomogram for MVI was developed and verified by bootstrap resampling. Results: Of the 16 variables we included, wedge and margin in HBP of EOB-MRI, capsule integrity in AP or HBP/PVP images of EOB-MRI/S-CEUS, and branching enhancement in AP of S-CEUS were identified as independent risk factors for MVI and incorporated into construction of the nomogram. The nomogram achieved an excellent diagnostic efficiency with an area under the curve of 0.8434 for full data training set and 0.7925 for bootstrapping validation set for 500 repetitions. In evaluating the nomogram, Hosmer-Lemeshow test for training set exhibited a good model fit with Conclusions: The MVI Nomogram established in this study may provide a strategy for optimizing the preoperative diagnosis of MVI, which in turn may improve the treatment and prognosis of MVI-related HCC.
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