Asymmetrical distribution of atherosclerosis in the carotid artery: identical patterns across age, race, and gender

Abstract

Small autopsy studies and clinical practice indicated that carotid atherosclerosis develops in an asymmetrical helical pattern coinciding with regions of low shear stress. We investigated the distribution of carotid atherosclerosis as determined by maximum carotid intima-media thickness (CIMT), to assess if we could confirm this atherosclerotic configuration across various populations with different cardiovascular risk. We used the individual baseline CIMT data from 3364 subjects from four recent international multicentre randomized controlled trials in which the carotid artery was systematically examined using the same ultrasound protocol and method to quantify CIMT. For each subject, circumferential information on the maximum CIMT of the left and right carotid arteries was obtained for the common carotid, bifurcation, and internal carotid artery segments. In each segment (common, bifurcation, internal), mixed modelling was used to study the differences in CIMT between angles, sides, gender, age, race, and studies. Each segment showed a different circumferential CIMT pattern. In all segments there were statistically significant differences between maximum CIMT across circumferential angles (p < 0.001); on average CIMT was highest in the posteromedial wall of the bifurcation and internal carotid segments and in the anterolateral wall of the common carotid segment. This asymmetric circumferential pattern was found to be identical in men and women, in young and old age, in different race groups, and across the studies. We confirmed the asymmetrical helix-like distribution of atherosclerosis in the carotid arteries and expand the evidence by showing that the atherosclerotic configuration is similar across populations with different vascular risks and across gender, age, and race. This has implications for future design of carotid ultrasound studies, as the angle of insonation is an important predictor of maximum CIMT.