Characterization of carotid artery plaques with USPIO-enhanced MRI: assessment of inflammation and vascularity as in vivo imaging biomarkers for plaque vulnerability

Abstract

To evaluate ultra small superparamagnetic iron oxide particles (USPIO) enhanced magnetic resonance (MR) imaging for characterization of atherosclerotic carotid plaques by assessing vascularity and plaque inflammation, besides contrast-enhanced MR angiography (CE-MRA) of the carotid artery stenosis. Twelve patients with severe carotid artery stenosis, scheduled for endarterectomy, underwent MRI of the carotid artery bifurcation using SHU 555 C at a dose of 40 μmol Fe/kg BW. The MR imaging protocol comprised pre- and post-contrast T2*-w, a first-pass CE-MRA and dynamic T1-w sequences. For quantitative data analysis, the signal intensities (SI) were measured and SNR-data (SNR = SI(blood/plaque/bone marrow)/standard deviation(noise)) as well as ΔSI-data (SNR(post)-SNR(pre)) were calculated. In addition, two radiologists rated the diagnostic performance of first-pass MRA according to a four level decision scale. Staining of anti-dextran (SHU 555 C) and anti-CD68 (macrophages) was performed for immunohistological confirmation. Plaque sections with a T2*-w signal decline (intracellular USPIO accumulation in macrophages) showed significantly changes (mean -14%, 95% CI, -5 to -20%; P < 0.01) and corresponding plaque regions had significantly higher (15.15 ± 1.76 vs. 5.22 ± 1.50; P < 0.01) T1-w enhancement data (global estimation of vascularity). The first-pass MRA of the supra-aortal vessels provided images of diagnostic quality. Representative immunohistology sections revealed colocalization of dextran- and CD68-immunoreactive cells. USPIO-enhanced MRI is feasible for in vivo assessment of vascularity and macrophage content in atherosclerotic carotid plaques, determining an association of these potential imaging biomarkers of plaque vulnerability. Diagnostic MRA of the supra-aortal vessels can be imaged additionally with a single administration of SHU 555 C.

Anti-inflammatory Nanoparticle for Prevention of Atherosclerotic Vascular Diseases

“…For example, magnetic nanoparticles with iron cores are available in MRI for macrophage imaging 26) . These so-called superparamagnetic iron oxide (SPIO) nanoparticles are used as a negative contrast agent in MRI.…”

“…The iron core is modified with hydrophilic polymers including dextran, carboxymethylated dextran, polyvinyl alcohol, starches, chitosan, polymethyl methacrylate, PEG, poly (lactic-co-glycolic) acid (PLGA), polyvinylpyrrolidone, and polyacrylic acid 27) . These particles have been tested in patients to evaluate inflammation, plaque vulnerability, and therapeutic effects of lipid lowering drugs, especially in the carotid arteries of patients 26,28,29) . Adhesion molecules are also targets of molecular imaging.…”

Cardiovascular Hybrid Imaging using PET/MRI

“…While in these studies PET/CT was used, the application of PET/MRI could provide advantages, despite lower temporal and spatial resolution. Thus certain plaque elements could be better differentiated from one another using MRI, as shown in a preclinical study using contrast agents containing iron oxide [42]. Moreover, in the future, new techniques based on parallel MRI acquisition for movement and partial volume effect correction of the PET signal could particularly improve PET imaging of coronary arteries, since this is especially affected by motion artifacts [6, 43].…”

Small Animal Imaging in Development of New Generation Diagnostic and Therapeutic Agents

“…the brain areas are imaged. Ferric, gadolinium or manganese are common contrast agents Ultra small superparamagnetic iron oxide (USPIO) particles, size range of 10 -50 nm, are widely used for various applications like vascularity and macrophage content in atherosclerotic carotid plaques (Metz et al 2011), lymph node metastasis (Lei et al 2010), tumor vascular morphology and blood hemodynamics (Gambarota et al 2010), diffusion in the brain disorders (Chin et al 2009, Vellinga et al 2009), cell number quantification (Cheung et al 2006) and oncological studies (Gambarota et al 2006, Baghi et al 2005, Keller et al 2004). …”