Quantification of carotid atherosclerotic plaque components using feature space analysis and magnetic resonance imaging

Microstructural and mechanical insight into atherosclerotic plaques: an ex vivo DTI study to better assess plaque vulnerability

Non-invasive microstructural characterisation has the potential to determine the stability, or lack thereof, of atherosclerotic plaques and ultimately aid in better assessing plaques' risk to rupture. If linked with mechanical characterisation using a clinically relevant imaging technique, mechanically sensitive rupture risk indicators could be possible. This study aims to provide this link-between a clinically relevant imaging technique and mechanical characterisation within human atherosclerotic plaques. Ex vivo diffusion tensor imaging, mechanical testing, and histological analysis were carried out on human carotid atherosclerotic plaques. DTI-derived tractography was found to yield significant mechanical insight into the mechanical properties of more stable and more vulnerable microstructures. Coupled with insights from digital image correlation and histology, specific failure characteristics of different microstructural arrangements furthered this finding. More circumferentially uniform microstructures failed at higher stresses and strains when compared to samples which had multiple microstructures, like those seen in a plaque cap. The novel findings in this study motivate diagnostic measures which use non-invasive characterisation of the underlying microstructure of plaques to determine their vulnerability to rupture.

Ex Vivo Study Using Diffusion Tensor Imaging to Identify Biomarkers of Atherosclerotic Disease in Human Cadaveric Carotid Arteries

BACKGROUND

This study aims to address the potential of ex vivo diffusion tensor imaging to provide insight into the microstructural composition and morphological arrangement of aged human atherosclerotic carotid arteries.

METHODS

In this study, whole human carotid arteries were investigated both anatomically and by comparing healthy and diseased regions. Nonrigid image registration was used with unsupervised segmentation to investigate the influence of elastin, collagen, cell density, glycosaminoglycans, and calcium on diffusion tensor imaging derived metrics (fractional anisotropy and mean diffusivity). Early stage atherosclerotic features were also investigated in terms of microstructural components and diffusion tensor imaging metrics.

RESULTS

All vessels displayed a dramatic decrease in fractional anisotropy compared with healthy animal arterial tissue, while the mean diffusivity was sensitive to regions of advanced disease. Elastin content strongly correlated with both fractional anisotropy (r>0.7, P<0.001) and mean diffusivity (r>-0.79, P<0.0002), and the thickened intima was also distinguishable from arterial media by these metrics.

CONCLUSIONS

These different investigations point to the potential of diffusion tensor imaging to identify characteristics of arterial disease progression, at early and late-stage lesion development.

Quantitative segmentation of principal carotid atherosclerotic lesion components by feature space analysis based on multicontrast MRI at 1.5 T

The purpose of this paper is to evaluate the capability of feature space analysis (FSA) for quantifying the relative volumes of principal components (thrombus, calcification, fibrous, normal intima, and lipid) of atherosclerotic plaque tissue in multicontrast magnetic resonance images (mc-MRI) acquired in a setup resembling clinical conditions ex vivo. Utilizing endogenous contrast, proton density, T1-weighted, and T2-weighted images were acquired for 13 carotid endarterectomy (CEA) tissues under near-clinical conditions (human 1.5 T GE Excite scanner with sequence parameters comparable to an in vivo acquisition). An FSA algorithm was utilized to segment and quantify the principal components of atherosclerotic plaques. Pilot in vivo mc-MRI images were analyzed in the same way as the ex vivo images for exploring the possible adaptation of this technique to in vivo imaging. Relative abundance of principal plaque components in CEA tissues as determined by mc-MRI/FSA were compared to those measured by histology. Mean differences +/- standard deviations were 5.8 +/- 4.1% for thrombus, 1.5 +/-1.4 % for calcification, 4.0 +/-2.8% for fibrous, 8.2 +/- 10% for normal intima, and 2.4 +/- 2.2% for lipid. Reasonable quantitative agreement between the classification results obtained with FSA and histological data was obtained for near-clinical imaging conditions. Combination of mc-MRI and FSA may have an application for determining atherosclerotic lesion composition and monitoring treatment in vivo.