Cardiovascular disease due to atherosclerosis remains the leading cause of death in the United States. Clinical symptoms and morbidity that result from atherosclerotic disease are due to plaque instability and are manifested as ulceration, thrombosis, and/or intraplaque hemorrhage. Though much research has been directed at understanding the progression of atherosclerotic disease, little is known about how to identify 'vulnerable' lesions in vivo non-invasively, or how to monitor the lesion progression longitudinally. This proposal presents a plan to develop a quantitative vascular analysis system (QVAS) that can be used to measure atherosclerotic plaque features semi-automatically. In Phase I of the application, we will focus our development on: 1) preparing the image data for analysis (e.g. performance surface coil sensitivity profile correction, and image registration), 2) developing general image processing features to ease the image review process, and 3) developing basic functions for vascular wall quantitative measurement (e.g. wall area measurement, tissue region identification). The system is designed to analyze high resolution magnetic resonance (MR) images of the vascular wall (e.g., human carotid artery) taken with various contrast weightings. These features will later be integrated with our long term goal of developing a semi-automatic system for interactive vascular analysis of vascular MR imaging.
