Robustness and classification capabilities of MRI radiomic features in identifying carotid plaque vulnerability.

ABSTRACT:

Objectives

To assess how radiomic features may be combined with plaque morphological and compositional features identified by multi-contrast MRI to improve upon conventional risk assessment models in determining culprit carotid artery lesions.

Methods

Fifty-five patients (mean age: 62.6; 35 males) with bilateral carotid stenosis who experienced transient ischaemic attack (TIA) or stroke were included from the CARE-II multi-centre carotid imaging trial (ClinicalTrials.gov Identifier: NCT02017756). They underwent MRI within 2 weeks of the event. Classification capability in distinguishing culprit lesions was assessed by machine learning. Repeatability and reproducibility of the results were investigated by assessing the robustness of the radiomic features.

Results

Radio

SUBMITTER: Meddings Z 

PROVIDER: S-EPMC11135795 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature