Long-term carotid plaque progression and the role of intraplaque hemorrhage: A deep learning-based analysis of longitudinal vessel wall imaging.

ABSTRACT:

Background

Carotid atherosclerosis is a major contributor to the etiology of ischemic stroke. Although intraplaque hemorrhage (IPH) is known to increase stroke risk and plaque burden, its long-term effects on plaque dynamics remain unclear. This study aimed to evaluate the long-term impact of IPH on carotid plaque burden progression using deep learning-based segmentation on multi-contrast magnetic resonance vessel wall imaging (VWI).

Methods

28 asymptomatic subjects with carotid atherosclerosis underwent an average of 4.7±0.6 VWI scans over 5.8±1.1 years. Deep learning pipelines were used to segment the carotid vessel walls and IPH. Bilateral plaque progression was analyzed using correlation coefficients and generalized estimating equations. Associations between IPH occurren

SUBMITTER: Guo Y 

PROVIDER: S-EPMC12808887 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature