Atherosclerosis is the root cause behind most heart attacks and strokes, making it the number one cause of mortality and morbidity in the United States. Methods are needed that permit evaluation of atherosclerotic lesion composition and morphology in vivo. Such methods would enable medical professionals to base treatment decisions on accurate risk assessments, support pre-interventional planning, and facilitate pharmaceutical trials that evaluate drug effects directly on the lesions. The goal of this proposal is to help meet these needs by performing the clinical trials necessary to obtain FDA approval to market our Quantitative Vascular Analysis System (QVAS) for two uses. The first use will employ the unique plaque lesion characterization methods of QVAS to generate a comprehensive risk score indicating whether a patient with carotid stenosis would benefit from surgical intervention such as carotid endarterectomy (CEA) or stenting. This use would allow the clinical guidelines for such interventions developed by the American Heart Association, which currently employ a single quantitative measure (carotid stenosis), to be updated with a more effective predictor of treatment outcome. For the second use, QVAS will generate a 3D visualization of the involved section of the carotid artery for use in pre-intervention treatment planning. This visualization would allow a surgeon to examine the full spatial extent and distribution of the different plaque components in order to select the intervention most likely to produce a positive outcome. We will also bring QVAS into compliance with the DICOM image exchange standard and the Clinical Data Interchange (CDISC) standard, as well as use the results and feedback from the trials to improve the reliability and effectiveness of QVAS. In order to meet this goal, we will continue the strategic relationship with the University of Washington's Vascular Imaging Lab (VIL) that has successfully developed the QVAS product under Phase I and Phase II SBIR grants. The VIL will develop a standardized training program, train the participating clinical sites, and act as the overall clinical data manager. ? ? ?

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
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Special Emphasis Panel (ZRG1-CVS-K (10))
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Goldberg, Suzanne H
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Vpdiagnostics, Inc.
United States
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Kerwin, William S (2012) Carotid artery disease and stroke: assessing risk with vessel wall MRI. ISRN Cardiol 2012:180710
Chiu, Bernard; Sun, Jie; Zhao, Xihai et al. (2011) Fast plaque burden assessment of the femoral artery using 3D black-blood MRI and automated segmentation. Med Phys 38:5370-84
Yang, Eric Y; Polsani, Venkateshwar R; Washburn, Michael J et al. (2011) Real-time co-registration using novel ultrasound technology: ex vivo validation and in vivo applications. J Am Soc Echocardiogr 24:720-8
Mughal, Majid M; Khan, Mohsin K; DeMarco, J Kevin et al. (2011) Symptomatic and asymptomatic carotid artery plaque. Expert Rev Cardiovasc Ther 9:1315-30
Dong, Li; Kerwin, William S; Ferguson, Marina S et al. (2009) Cardiovascular magnetic resonance in carotid atherosclerotic disease. J Cardiovasc Magn Reson 11:53
Kerwin, William S; Liu, Fei; Yarnykh, Vasily et al. (2008) Signal features of the atherosclerotic plaque at 3.0 Tesla versus 1.5 Tesla: impact on automatic classification. J Magn Reson Imaging 28:987-95
Kerwin, William; Xu, Dongxiang; Liu, Fei et al. (2007) Magnetic resonance imaging of carotid atherosclerosis: plaque analysis. Top Magn Reson Imaging 18:371-8
Liu, Fei; Xu, Dongxiang; Ferguson, Marina S et al. (2006) Automated in vivo segmentation of carotid plaque MRI with Morphology-Enhanced probability maps. Magn Reson Med 55:659-68