Key result
Macrophage-targeted GdMG nanoclusters significantly increased the contrast-to-noise ratio from 6.50 to 36.91 and enabled quantitative calculation of plaque vulnerability with an AUC of 0.875.
Why the study?
HR-VWI lacks sensitive and specific image markers, relying on plaque morphology, while studies in larger animals are needed for translating targeted nanoparticle contrast agents.
Does HR-VWI enhanced with macrophage-targeted GdMG nanoclusters improve the prediction of carotid plaque vulnerability compared to conventional gadobutrol in an atherosclerotic rabbit model?
Does HR-VWI enhanced with macrophage-targeted GdMG nanoclusters improve the prediction of carotid plaque vulnerability compared to conventional gadobutrol in an atherosclerotic rabbit model?
Absolute Event Rate: 36.91% vs 6.5%
p-value: p=<0.001
Macrophage-targeted GdMG nanoclusters significantly improve the non-invasive MRI prediction of carotid plaque vulnerability in an atherosclerotic rabbit model.
Supports preclinical development of targeted MRI agents; leaves open human translation for carotid plaque risk stratification.
OBJECTIVE To innovatively developed a macrophage-target nanoparticle based contrast-enhanced high-resolution magnetic resonance vessel wall imaging (HR-VWI) strategy to characterize the plaques’ vulnerable features on rabbits. BACKGROUND Lacking of sensitive and specific image-marker of HR-VWI leads this technique depending upon the plaque morphological characteristics. Nanoparticle-based contrast agents modified with targeting ligands allow amplifying MR signals of the interested components. The key to successful translation is the requirement that conducting studies in larger animals to provide reasonable diagnostic readouts. METHODS The HR-VWI enhanced with macrophage-targeted PP1-Au@GSH@Gd (GdMG) nanoclusters (NCs) and the conventional Gadovist were utilized for the plaque vulnerability evaluation by a systematic histogram analysis in atherosclerosis (AS) rabbit model. RESULTS Due to the compelling targeting capacity of GdMG NCs to foamy macrophages, the contrast-to-noise ratio (CNR) from pre-injection baseline dramatically raised from 6.50 to 36.91 ( p < 0.001), with an increment of 1.39-fold higher than that of the Gadovist approach. Spearman’ s correlation test confirmed that the coefficient of variation (CV) derived from the histogram analysis based on GdMG NCs HR-VWI was indeed positively linearly correlated with pathology vulnerability index (VI P ) significantly ( p < 0.05) with adjusted R 2 = 0.775. Finally, mathematic formulas with histogram-derived parameters as variables were fitted to quantitatively calculate the histogram vulnerability index (VI H ) with the strength of the adjusted R 2 = 0.952 ( p < 0.001), and Area under the curve (AUC) of 0.875 ( p < 0.001) to realize the in vivo and quantitative calculation of the plaque vulnerability. CONCLUSION Profiting from the splendid inflammation targeted capacity and excellent MRI performance of GdMG NCs, as well as the highly quantitative characteristics of histogram analysis, we disclosed that our established imaging protocol was able to identify the plaques’ vulnerability index that were comparable to pathological examinations in both retrospective and prospective experiments.
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Gong et al. (2023) studied Atherosclerosis (n=12). Macrophage-targeted PP1-Au@GSH@Gd (GdMG) nanoclusters vs. Gadovist was evaluated on Contrast-to-noise ratio (CNR) (p=<0.001). Macrophage-targeted GdMG nanoclusters significantly increased the contrast-to-noise ratio from 6.50 to 36.91 and enabled quantitative calculation of plaque vulnerability with an AUC of 0.875.
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