Radiomics-based diagnosis of carotid artery stenosis using non-contrast CT: model development and validation.

ABSTRACT:

Background

Early detection of carotid artery stenosis is critical for effective stroke prevention. We investigated the feasibility and diagnostic efficacy of radiomics analysis based on non-contrast computed tomography (NCCT) in identifying carotid artery stenosis, and aimed to establish a radiomics-based machine-learning model as a non-invasive, cost-effective auxiliary diagnostic tool.

Methods

This retrospective study included 260 patients who underwent both non-contrast and contrast-enhanced carotid computed tomography (CT) scans at Jiaxing First Hospital between January 2021 and December 2024. The degree of carotid stenosis was confirmed by CT angiography. Patients were enrolled according to predefined inclusion and exclusion criteria. Clinical data from 260 eligible pat

SUBMITTER: Wang G 

PROVIDER: S-EPMC12706977 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature