In vivo Detection of Vulnerable Atherosclerotic Plaque by MRI in a Rabbit Model

Abstract

Background— The ability to identify atherosclerotic plaques with a high risk for sudden disruption before stroke or myocardial infarction would be of great utility. We used a rabbit model of controlled atherothrombosis to test whether in vivo MRI can noninvasively distinguish between plaques that disrupt after pharmacological triggering (vulnerable) and those that do not (stable). Methods and Results— Atherosclerosis was induced in male New Zealand White (n=17) rabbits by cholesterol diet and endothelial denudation of the abdominal aorta. After baseline (pretrigger) MRI with and without gadolinium contrast, the rabbits underwent 2 pharmacological triggerings to induce atherothrombosis, followed by another MRI 48 hours later (post-triggering). Atherosclerosis was identified by the pretriggered images in all rabbits, and thrombosis was identified in 9 of 17 animals (53%) by post-trigger MRI. After the animals were euthanized, 95 plaques were analyzed; 28 (29.5%) had thrombi (vulnerable) and 67 did not (stable) (70.5%). Pretriggered MRI revealed comparable stenosis in stable and vulnerable plaques, but vulnerable plaques had a larger plaque area (4.8�1.6 versus 3.0�1.0 mm 2 ; P =0.01), vessel area (9.2�3.0 versus. 15.8�4.9 mm 2 ; P =0.01), and higher remodeling ratio (1.16�0.2 versus 0.93�0.2; P =0.01) compared with stable plaques. Furthermore, vulnerable plaques more frequently exhibited (1) positive remodeling (67.8% versus 22.3%; P =0.01), in which the plaque is hidden within the vessel wall instead of occluding the lumen; and (2) enhanced gadolinium uptake (78.6% versus 20.9%; P =0.01) associated with histological findings of neovascularization, inflammation, and tissue necrosis. Conclusions— We demonstrate that in vivo MRI at 3.0 T detects features of vulnerable plaques in an animal model of controlled atherothrombosis. These findings suggest that MRI may be used as a noninvasive modality for localization of plaques that are prone to disruption.