Predicting symptomatic carotid artery plaques with radiomics-based carotid perivascular adipose tissue characteristics: a multicenter, multiclassifier study.

ABSTRACT:

Objective

This study aims to differentiate between symptomatic and asymptomatic plaques using a computed tomography angiography (CTA)-based radiomics model of perivascular adipose tissue (PVAT).

Methods

Patients were categorized into symptomatic and asymptomatic groups based on the presence or absence of acute ischemic stroke or transient ischemic attack in the anterior cerebral circulation within two weeks prior to the CTA examination. The clinical information of all patients was collected and analyzed, and the PVAT features of CTA images were further analyzed to clarify their correlation with plaque classification. K-nearest neighbors (KNN), support vector machine (SVM), logistic regression (LR), random forest (RF), linear discriminant analysis (LDA), multinomial naive Bay

SUBMITTER: Zhao T 

PROVIDER: S-EPMC12363075 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature