Objective To predict preoperative microvascular invasion (MVI) risk grade by analyzing the
radiomics signatures of tumors and peritumors on enhanced magnetic resonance imaging …

Purpose To develop a prediction model that combined magnetic resonance images (MRI)-
based radiomics features with clinical factors to predict recurrence-free survival (RFS) of …

Hepatocellular carcinoma (HCC) is the fifth most common malignancy and the third leading
cause of cancer‐related death worldwide. HCC exhibits strong inter‐tumor heterogeneity …

Predicting the biological characteristics of hepatocellular carcinoma (HCC) is essential for
personalized treatment. This study explored the role of ultrasound-based radiomics of …

Purpose The prognosis of early-stage hepatocellular carcinoma (HCC) patients after radical
resection has received widespread attention, but reliable prediction methods are lacking …

Purpose To establish and validate a nomogram model incorporating both liver imaging
reporting and data system (LI-RADS) features and contrast enhanced magnetic resonance …

Purpose To compare the efficacy of radiomics models via five machine learning algorithms
in predicting the histological grade of hepatocellular carcinoma (HCC) before surgery and to …

Objectives To explore the usefulness of spleen radiomics features based on contrast-
enhanced computed tomography (CECT) in predicting early and late recurrences of …

Objective To investigate the value of differential diagnosis of hepatocellular carcinoma
(HCC) and non-hepatocellular carcinoma (non-HCC) based on CT and MR multiphase …

Background Early stage hepatocellular carcinoma (HCC) is the ideal candidate for resection
in patients with preserved liver function; however, cancer will recur in half of these patients …