van Engelen, Arna3; Wannarong, Thapat3; Parraga, Grace3; Niessen, Wiro J.3; Fenster, Aaron3; Spence, J. David3; de Bruijne, Marleen5
1 Administration, Department of Computer Science, Faculty of Science, Københavns Universitet2 The Image Section, Department of Computer Science, Faculty of Science, Københavns Universitet3 unknown4 Department of Computer Science, Faculty of Science, Københavns Universitet5 Department of Computer Science, Faculty of Science, Københavns Universitet
BACKGROUND AND PURPOSE: Carotid ultrasound atherosclerosis measurements, including those of the arterial wall and plaque, provide a way to monitor patients at risk of vascular events. Our objective was to examine carotid ultrasound plaque texture measurements and the change in carotid plaque texture during 1 year in patients at risk of events and to compare these with measurements of plaque volume and other risk factors as predictors of vascular events. METHODS: We evaluated 298 patients with carotid atherosclerosis using 3-dimensional (3D) ultrasound at baseline and after 1 year and measured carotid plaque volume and 376 measures of plaque texture. Patients were followed up to 5 years (median [range], 3.12 [0.77-4.66]) for myocardial infarction, transient ischemic attack, and stroke. Sparse Cox regression was used to select the most predictive plaque texture measurements in independent training sets using a 10-fold cross-validation, repeated 5×, to ensure unbiased results. RESULTS: Receiver operator curves and Kaplan-Meier analysis showed that changes in texture and total plaque volume combined provided the best predictor of vascular events. In multivariate Cox regression, changes in plaque texture (median hazard ratio, 1.4; P<0.001) and total plaque volume (median hazard ratio, 1.5 per 100 mm(3); P<0.001) were both significant predictors, whereas the Framingham risk score was not. CONCLUSIONS: Changes in both plaque texture and volume are strongly predictive of vascular events. In high-risk patients, 3D ultrasound plaque measurements should be considered for vascular event risk prediction.