MRI in the early identification and classification of high-risk atherosclerotic carotid plaques.
Stroke is a leading cause of mortality and long-term morbidity. As a means for stroke prevention, an estimated 99,000 carotid endarterectomy procedures were performed in the USA in 2006. Traditionally, the degree of luminal stenosis has been used as a marker of the stage of atherosclerosis and as an indication for surgical intervention. However, prospective clinical trials have shown that the majority of patients with a history of recent transient ischemic attack or stroke have mild-to-moderate carotid stenosis. Using stenosis criteria, many of these symptomatic individuals would be considered to have early-stage carotid atherosclerosis. It is evident that improved criteria are needed for identifying the high-risk carotid plaque across a range of stenoses. Histological studies have led to the hypothesis that plaques with larger lipid-rich necrotic cores, thin fibrous cap rupture, intraplaque hemorrhage, plaque neovasculature and vessel wall inflammation are characteristics of the high-risk, 'vulnerable plaque'. Despite the widespread consensus on the importance of these plaque features, testing the vulnerable plaque hypothesis in prospective clinical studies has been hindered by the lack of reliable imaging tools for in vivo plaque characterization. MRI has been shown to accurately identify key carotid plaque features, including the fibrous cap, lipid-rich necrotic core, intraplaque hemorrhage, neovasculature and vascular wall inflammation. Thus, MRI is a histologically validated technique that will permit prospective testing of the vulnerable plaque hypothesis. This article will provide a summary of the histological validation of carotid MRI, and highlight its application in prospective clinical studies aimed at early identification of the high-risk atherosclerotic carotid plaque.
Hatsukami
Thomas S
TS
Department of Surgery, Vascular Imaging Lab, University of Washington, 815 Mercer Street, Box 358050, Seattle, WA 98109, USA, Tel.: +1 206 543 3061, ,  tomhat@u.washington.edu.
Yuan
Chun
C