Imaging vulnerable plaques by targeting inflammation in atherosclerosis using fluorescent-labeled dual-ligand microparticles of iron oxide and magnetic resonance imaging

Abstract Objective Identification of patients with high-risk asymptomatic carotid plaques remains an elusive but essential step in stroke prevention. Inflammation is a key process in plaque destabilization and a prelude to clinical sequelae. There are currently no clinical imaging tools to assess the inflammatory activity within plaques. This study characterized inflammation in atherosclerosis using dual-targeted microparticles of iron oxide (DT-MPIO) as a magnetic resonance imaging (MRI) probe. Methods DT-MPIO were used to detect and characterize inflammatory markers, vascular cell adhesion molecule 1 (VCAM-1). and P-selectin on (1) tumor necrosis factor-α-treated cells by immunocytochemistry and (2) aortic root plaques of apolipoprotein-E deficient mice by in vivo MRI. Furthermore, apolipoprotein E-deficient mice with focal carotid plaques of different phenotypes were developed by means of periarterial cuff placement to allow in vivo molecular MRI using these probes. The association between biomarkers and the magnetic resonance signal in different contrast groups was assessed longitudinally in these models. Results Immunocytochemistry confirmed specificity and efficacy of DT-MPIO to VCAM-1 and P-selectin. Using this in vivo molecular MRI strategy, we demonstrated (1) the DT-MPIO-induced magnetic resonance signal tracked with VCAM-1 ( r  = 0.69; P  = .014), P-selectin ( r  = 0.65; P  = .022), and macrophage content ( r  = 0.59; P  = .045) within aortic root plaques and (2) high-risk inflamed plaques were distinguished from noninflamed plaques in the murine carotid artery within a practical clinical imaging time frame. Conclusions These molecular MRI probes constitute a novel imaging tool for in vivo characterization of plaque vulnerability and inflammatory activity in atherosclerosis. Further development and translation into the clinical arena will facilitate more accurate risk stratification in carotid atherosclerotic disease in the future.