• Dionesia D Adraktas, Elizabeth Tong, Andre D Furtado, Su-Chun Cheng, and Max Wintermark.
• Department of Radiology, Neuroradiology Division, University of California, San Francisco, CA.
• J Neuroimaging. 2014 Jan 1;24(1):1-6.

PurposeThe purpose of this study was to identify imaging markers and clinical risk factors that significantly predict the evolution of computed tomography (CT) imaging features of carotid artery atherosclerotic disease over a 1-year period.MethodsOur prospective study involved 120 consecutive patients undergoing emergent CT evaluation for symptoms of acute stroke. These patients were asked to consent to a follow-up CT exam in 1 year. To evaluate for atherosclerotic plaque, both at baseline and on follow-up, we employed a comprehensive computed tomography angiography (CTA) protocol that captured the carotid, vertebral, aortic, and coronary arteries. To further evaluate carotid artery plaque components, we used an automated classifier computer algorithm that distinguishes among the histological components of the carotid artery wall (lipids, calcium, fibrous tissue) based on appropriate thresholds of CT density. Baseline values of carotid imaging features and clinical variables were assessed for their ability to significantly predict changes in these imaging features over 1 year.ResultsOf these 120 consecutive patients, 17 received both a baseline and a follow-up CTA exam. Wall volume increased more when the largest lipid cluster was located close to the lumen (coefficient -7.61, -13.83 to -1.40, P = .016). The volume of lipid increased with age (coefficient .36, .21 to .50, P = .000), in smokers (coefficient 8.89, 6.82 to 10.95, P = .000) and when fewer lipid clusters were present at baseline (coefficient -0.11, -0.17 to -.04, P = .001). The volume of calcium increased with greater volume of lipid at baseline (coefficient .35, .02 to .68, P = .035) and in patients on statins (coefficient 4.79, 1.73 to 7.86, P = .002).ConclusionsThere are a number of imaging markers and risk factors that significantly predict the evolution of CT imaging features of carotid artery atherosclerotic disease over a 1-year period.Copyright © 2012 by the American Society of Neuroimaging.

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