Quantification of human atherosclerotic plaques using spatially enhanced cluster analysis of multicontrast-weighted magnetic resonance images

Abstract

One of the current limitations of magnetic resonance imaging (MRI) is the lack of an objective method to classify plaque components. Here we present a cluster analysis technique that can objectively quantify and classify MR images of atherosclerotic plaques. We obtained three-dimensional (3D) images from 12 human coronary artery specimens on a 9.4T imaging system using multicontrast-weighted fast spin-echo (T1-, proton density-, and T2-weighted) imaging with an isotropic voxel size of 39 micro. Spatially enhanced cluster analysis (SECA) was performed on multicontrast MR images, and the resulting segmentation was evaluated against histological tracings. To visualize the overall structure of plaques, the MR images were rendered in 3D. The specimens exhibited lesions of American Heart Association (AHA) plaque classification types I-VI. Both MR images and histological sections were independently reviewed, categorized, and compared. Overall, the classification obtained from the cluster-analyzed MR and histopathology images showed very good agreement for all AHA types (92%, Cohen's kappa = 0.89, P < 0.0001). All plaque types were identified and quantified by SECA with a high degree of correlation between cluster-analyzed MR and manually traced histopathology data. MRI combined with SECA provides an objective method for atherosclerotic plaque component characterization and quantification.