Vulnerable Carotid Artery Plaque Evaluation: Detection Agreement between Advanced Ultrasound, Computed Tomography,...

Imaging plaque morphology, in addition to luminal grading, may improve stroke risk-management by identifying structural atherosclerotic plaques alterations responsible for cerebrovascular events. The purpose of this study was to evaluate the agreement between our enhanced ultrasound (US) imaging method and high-resolution cross-sectional imaging modalities, such as multidetector-row computed tomography (CT) and magnetic resonance imaging (MRI), in the characterization of vulnerable plaques.

Sixty tissue-like phantoms were created to simulate various types of diseased plaque segments. We prospectively assessed each sample with US, CT, and MRI. Plaque characteristics considered included surface irregularity, ulceration, fissure, and presence of internal fluid core(s). We evaluated the agreement between and among the three modalities, as well as the accuracy of each compared with the true pathology.

There was moderate to substantial agreement among the three modalities in the detection of morphologic characteristics. There was no significant difference in accuracy between US and CT in the presence of ulceration(s) (P = .23), lucency (P = .23), or fissures (P = .07); however, US was significantly more accurate than MRI for each of these characteristics (P = .0001, P = .0001, P = .02, respectively). None of the three modalities did display any significant difference in accuracy in the identification of irregular surface. There was substantial agreement among the three radiologists (intraclass correlation coefficient, 0.61; 95% confidence interval, 0.46-0.74) in their assessment of plaque subtype, ranging from 80%-85% accuracy in identifying the plaque subtypes for each classification.

Enhanced plaque imaging can identify potentially significant plaque characteristics and provide insight into early causative conditions of carotid atherosclerosis. Our results suggest that the types of plaque pathologies derived from our US method showed good agreement with CT and surpass information gathered on MRI. This imaging protocol could potentially shift the paradigm in early carotid plaque imaging likely to predict the onset of vulnerable plaques, thus improving preventative management of atherosclerosis.