Noise and motion correction in dynamic contrast-enhanced MRI for analysis of atherosclerotic lesions

Dynamic contrast-enhanced MRI of atherosclerotic vessels after contrast agent injection may provide unique information regarding lesion structure and vulnerability. The high-resolution images necessary for viewing lesion substructures, however, are often corrupted by patient motion and low signal-to-noise ratios, making pixel-level analyses difficult. This article presents a postprocessing method that enables pixel-level analysis of dynamic images by eliminating motion and enhancing image quality. Noise and motion correction are performed using optimal statistical methods under the assumption that noise and contrast agent dynamics are random processes. The method is demonstrated and validated on dynamic images of atherosclerotic plaques in human carotid arteries.