Cardiovascular disease is a leading cause of death in the United States. Atherosclerosis is a well recognized cause of cardiovascular disease that develops over decades typically without symptoms. As a result, many major cardiovascular events, such as heart attacks and strokes, occur without forewarning. Methods of risk assessment and early detection of atherosclerosis are important tools for clinicians. However, current methods of assessment, including the Framingham Risk Score, computed tomography, and ultrasound have been limited either in accuracy or application. More recently, magnetic resonance imaging (MRI)-derived biomarkers, such as wall shear stress (WSS) and pulse wave velocity (PWV) have shown potential in the early detection of atherosclerosis. WSS is a measure of drag forces on vessel walls, low values of which are predictive for the development of atherosclerotic plaques. PWV is a measure of the propagation of blood down the aorta and thus reflects stiffness of the arterial wall;high values of PWV are indicative of atherosclerotic burden. However, past studies with these biomarkers have either been limited in spatial resolution for the measurement of WSS, in temporal resolution for the measurement of PWV, or in anatomic coverage. Additionally, WSS and PWV were evaluated with separate MRI acquisitions.
The aim of this study is to develop and evaluate a three-dimensional (3D), three-directional flow-sensitive MRI technique that provides high spatial resolution, high temporal resolution, and large anatomic coverage in a single ten minute acquisition. Our proposed technique, termed PC VIPR, already provides superior spatial resolution and anatomic coverage compared to studies in the literature, but greater temporal resolution is needed, especially for an accurate analysis of PWV. Therefore, we will first investigate the use of an algorithm, termed HYPR that has the potential to accelerate the PC VIPR acquisition. We will use this acceleration to improve the temporal resolution while maintaining the same ten-minute scan time. Once the HYPR algorithm is incorporated into the PC VIPR acquisition, flow measurements derived from the acquisition will be validated with a flow phantom study. Given our unique 3D MRI data set, analysis tools and algorithms will be developed to compute the WSS and PWV measurements. The accelerated PC VIPR acquisition will thus allow for the simultaneous evaluation of WSS and PWV from a single ten-minute scan. Finally, we will investigate these measurements of WSS and PWV longitudinally in a swine model of atherosclerosis secondary to familial hypercholesterolemia (FH). These FH pigs develop atherosclerosis by one year of age without intervention or diet modifications as a result of their genetic mutation. We will compare our WSS and PWV measurements in both FH and normal swine at 2-, 5-, 8-, and 12-months of age. Such a study will allow us to investigate the ability of these MRI-derived biomarkers to predict and assess atherosclerotic burden, particularly in the early stages of disease.

Public Health Relevance

This research proposal aims to develop non-invasive magnetic resonance imaging (MRI) methods for evaluating and detecting atherosclerosis. This project includes an unprecedented evaluation of early detection techniques in an animal model of atherosclerosis. Such an evaluation is useful, as the early detection of atherosclerotic plaques aids in treatment planning and encourages lifestyle changes and patient compliance.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
Project #
5F30HL108539-03
Application #
8474835
Study Section
Special Emphasis Panel (ZRG1-F15-D (20))
Program Officer
Carlson, Drew E
Project Start
2011-06-01
Project End
2016-05-31
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
3
Fiscal Year
2013
Total Cost
$39,601
Indirect Cost
Name
University of Wisconsin Madison
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
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