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Collagen-specific peptide conjugated HDL nanoparticles as MRI contrast agent to evaluate compositional changes in atherosclerotic plaque regression.

ABSTRACT: This study sought to develop magnetic resonance contrast agents based on high-density lipoprotein (HDL) nanoparticles to noninvasively visualize intraplaque macrophages and collagen content in mouse atherosclerotic plaques.Macrophages and collagen are important intraplaque components that play central roles in plaque progression and/or regression. In a Reversa mouse model, plaque regression with compositional changes (from high macrophage, low collagen to low macrophage, high collagen) can be induced.This study labeled HDL nanoparticles with amphiphilic gadolinium chelates to enable target-specific imaging of intraplaque macrophages. To render HDL nanoparticles specific for the extracellular matrix, labeled HDL nanoparticles were functionalized with collagen-specific EP3533 peptides (EP3533-HDL) via poly(ethylene glycol) spacers embedded in the HDL lipid layers. The association of nanoparticles with collagen was examined in vitro by optical methods. The in vivo magnetic resonance efficacy of these nanoparticles was evaluated in a Reversa mouse model of atherosclerosis regression. Ex vivo confocal microscopy was applied to corroborate the in vivo findings and to evaluate the fate of the different HDL nanoparticles.All nanoparticles had similar sizes (10 ± 2 nm) and longitudinal relaxivity r1 (9 ± 1 s(-1) mmol/l(-1)). EP3533-HDL showed strong association with collagen in vitro. After 28 days of plaque regression in Reversa mice, EP3533-HDL showed significantly increased (p < 0.05) in vivo magnetic resonance signal in aortic vessel walls (normalized enhancement ratio [NERw] = 85 ± 25%; change of contrast-to-noise ratio [?CNRw] = 17 ± 5) compared with HDL (NERw = -7 ± 23%; ?CNRw = -2 ± 4) and nonspecific control EP3612-HDL (NERw = 4 ± 24%; ?CNRw = 1 ± 6) at 24 h after injection. Ex vivo confocal images revealed the colocalization of EP3533-HDL with collagen. Immunohistostaining analysis confirmed the changes of collagen and macrophage contents in the aortic vessel walls after regression.This study shows that the HDL nanoparticle platform can be modified to monitor in vivo plaque compositional changes in a regression environment, which will facilitate understanding plaque regression and the search for therapeutic interventions.

SUBMITTER: Chen W

PROVIDER: S-EPMC3653172 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

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Collagen-specific peptide conjugated HDL nanoparticles as MRI contrast agent to evaluate compositional changes in atherosclerotic plaque regression.

Chen Wei W Cormode David P DP Vengrenyuk Yuliya Y Herranz Beatriz B Feig Jonathan E JE Klink Ahmed A Mulder Willem J M WJ Fisher Edward A EA Fayad Zahi A ZA

JACC. Cardiovascular imaging 20130220 3

<h4>Objectives</h4>This study sought to develop magnetic resonance contrast agents based on high-density lipoprotein (HDL) nanoparticles to noninvasively visualize intraplaque macrophages and collagen content in mouse atherosclerotic plaques.<h4>Background</h4>Macrophages and collagen are important intraplaque components that play central roles in plaque progression and/or regression. In a Reversa mouse model, plaque regression with compositional changes (from high macrophage, low collagen to lo ...[more]

PMID: 23433925

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Project description:BACKGROUND:Compromised structural integrity of the endothelium and higher microvessel density increase vascular permeability. We investigated whether vascular permeability measured in vivo by magnetic resonance imaging using the albumin-binding contrast agent, gadofosveset, is a surrogate marker of rupture-prone atherosclerotic plaque in a rabbit model. METHODS AND RESULTS:New Zealand white rabbits (n=10) were rendered atherosclerotic by cholesterol-diet and endothelial denudation. Plaque rupture was triggered with Russell's viper venom and histamine. Animals were imaged pre-triggering, at 3 and 12 weeks, to quantify plaque area, vascular permeability, vasodilation, and stiffness and post-triggering to identify thrombus. Plaques identified on the pretrigger scans were classified as stable or rupture-prone based on the absence or presence of thrombus on the corresponding post-trigger magnetic resonance imaging, respectively. All rabbits had developed atherosclerosis, and 60% had ruptured plaques. Rupture-prone plaques had higher vessel wall relaxation rate (R1; 2.30±0.5 versus 1.86±0.3 s-1; P<0.001), measured 30 minutes after gadofosveset administration, and higher R1/plaque area ratio (0.70±0.06 versus 0.47±0.02, P= 0.01) compared with stable plaque at 12 weeks. Rupture-prone plaques had higher percent change in R1 between the 3 and 12 weeks compared with stable plaque (50.80±7.2% versus 14.22±2.2%; P<0.001). Immunohistochemistry revealed increased vessel wall albumin and microvessel density in diseased aortas and especially in ruptured plaque. Electron microscopy showed lack of structural integrity in both luminal and microvascular endothelium in diseased vessels. Functionally, the intrinsic vasodilation of the vessel wall decreased at 12 weeks compared with 3 weeks (18.60±1.0% versus 23.43±0.8%; P<0.001) and in rupture-prone compared with stable lesions (16.40±2.0% versus 21.63±1.2%; P<0.001). Arterial stiffness increased at 12 weeks compared with 3 weeks (5.00±0.1 versus 2.53±0.2 m/s; P<0.001) both in animals with stable and rupture-prone lesions. CONCLUSIONS:T1 mapping using an albumin-binding contrast agent (gadofosveset) could quantify the changes in vascular permeability associated with atherosclerosis progression and rupture-prone plaques.

Project description:Coronary artery disease is defined by the existence of atherosclerotic plaque on the arterial wall, which can cause blood flow impairment, or plaque rupture, and ultimately lead to myocardial ischemia. Intravascular ultrasound (IVUS) imaging can provide a detailed characterization of lumen and vessel features, and so plaque burden, in coronary vessels. Prediction of the regions in a vascular segment where plaque burden can either increase (progression) or decrease (regression) following a certain therapy, has remained an elusive major milestone in cardiology. Studies like IBIS-4 showed an association between plaque burden regression and high-intensity rosuvastatin therapy over 13 months. Nevertheless, it has not been possible to predict if a patient would respond in a favorable/adverse fashion to such a treatment. This work aims to (i) Develop a framework that processes lumen and vessel cross-sectional contours and extracts geometric descriptors from baseline and follow-up IVUS pullbacks; and to (ii) Develop, train, and validate a machine learning model based on baseline/follow-up IVUS datasets that predicts future percent of atheroma volume changes in coronary vascular segments using only baseline information, i.e. geometric features and clinical data. This is a post hoc analysis, revisiting the IBIS-4 study. We employed 140 arteries, from 81 patients, for which expert delineation of lumen and vessel contours were available at baseline and 13-month follow-up. Contour data from baseline and follow-up pullbacks were co-registered and then processed to extract several frame-wise features, e.g. areas, plaque burden, eccentricity, etc. Each pullback was divided into regions of interest (ROIs), following different criteria. Frame-wise features were condensed into region-wise markers using tools from statistics, signal processing, and information theory. Finally, a stratified 5-fold cross-validation strategy (20 repetitions) was used to train/validate an XGBoost regression models. A feature selection method before the model training was also applied. When the models were trained/validated on ROI defined by the difference between follow-up and baseline plaque burden, the average accuracy and Mathews correlation coefficient were 0.70 and 0.41 respectively. Using a ROI partition criterion based only on the baseline's plaque burden resulted in averages of 0.60 accuracy and 0.23 Mathews correlation coefficient. An XGBoost model was capable of predicting plaque progression/regression changes in coronary vascular segments of patients treated with rosuvastatin therapy in 13 months. The proposed method, first of its kind, successfully managed to address the problem of stratification of patients at risk of coronary plaque progression, using IVUS images and standard patient clinical data.

Dataset Information

Collagen-specific peptide conjugated HDL nanoparticles as MRI contrast agent to evaluate compositional changes in atherosclerotic plaque regression.

Publications

Collagen-specific peptide conjugated HDL nanoparticles as MRI contrast agent to evaluate compositional changes in atherosclerotic plaque regression.

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