Clinical-Radiomics Nomogram Model Based on CT Angiography for Prediction of Intracranial Aneurysm Rupture: A Multicenter Study.

Objective: Risk estimation of intracranial aneurysm rupture is critical in determining treatment strategy. There is a scarcity of multicenter studies on the predictive power of clinical-radiomics models for aneurysm rupture. This study aims to develop a clinical-radiomics model and explore its additional value in the discrimination of aneurysm rupture.

Radiomics-Based Prediction of Microvascular Invasion Grade in Nodular Hepatocellular Carcinoma Using Contrast-Enhanced Magnetic Resonance Imaging.

Objective: The aim of this study is to develop and verify a magnetic resonance imaging (MRI)-based radiomics model for predicting the microvascular invasion grade (MVI) before surgery in individuals diagnosed with nodular hepatocellular carcinoma (HCC).

Methods: A total of 198 patients were included in the study and were randomly stratified into two groups: a training group consisting of 139 patients and a test group comprising 59 patients. The tumor lesion was manually segmented on the largest cross-sectional slice using ITK SNAP, with agreement reached between two radiologists.