The assessment of carotid plaque characteristics with Contrast Enhanced Ultrasound

Background: Carotid atherosclerosis is a leading cause of ischemic stroke, and accurate assessment of plaque vulnerability remains a major clinical challenge. Contrast-enhanced ultrasound (CEUS) enables in vivo visualization of intraplaque neovascularization and hemorrhage, two features strongly associated with future cerebrovascular events. Methods: This systematic review synthesized evidence from 13 studies published between 2010 and 2025. Eligible studies evaluated CEUS for carotid plaque characterization and correlated findings with clinical outcomes, systemic biomarkers, central nervous system imaging, or histology. A narrative comparative synthesis was performed due to methodological heterogeneity. Results: CEUS consistently demonstrated that symptomatic patients exhibit greater intraplaque enhancement than asymptomatic individuals. Quantitative time–intensity curve analysis provided stronger reproducibility and closer correlation with histology and biomarkers compared with visual grading. CEUS findings were associated with ischemic events even in patients with mild stenosis, highlighting its added prognostic value beyond luminal narrowing. Correlations with biomarkers such as hs-CRP, VEGF, and IL-6 were reported, although results varied across cohorts. Histological validation uniformly confirmed that CEUS enhancement reflects microvessel density and intraplaque hemorrhage. A smaller number of studies linked CEUS findings with silent brain infarcts and white matter lesions, suggesting a broader cerebrovascular impact. Despite differences in protocols, contrast agents, and follow-up durations, the overall evidence supports CEUS as a robust, non-invasive marker of plaque vulnerability. Conclusions: CEUS reliably detects biologically active carotid plaques and predicts adverse outcomes, with strong histological validation. Future research should focus on protocol standardization, integration with biomarkers and CNS imaging, and application of artificial intelligence and radiomics to further enhance reproducibility and clinical utility.