This project will develop a new ultra-safe technique for myocardial perfusion stress testing in humans. Rationale: A growing number of patients in the United States require frequent cardiovascular assessment, to determine the presence and significance of coronary artery disease (CAD). Non-invasive myocardial perfusion stress testing is a method of choice, but we are not able to use current tests as frequently as we would like in these patients due to ionizing radiation and/or risks associated with contrast agents. Our proposed technique will not require any ionizing radiation or any potentially toxic contrast agents, and could therefore be performed repeatedly with no incremental risk to the patient. Innovation: We will utilize arterial spin labeled magnetic resonance imaging (ASL-MRI), an established technology for measuring brain perfusion in humans and myocardial perfusion in small animals. To our knowledge, its application to clinical myocardial perfusion imaging and stress testing is novel. Current methods for human cardiac ASL are able to detect increases in blood flow due to vasodilation, but provide only single slice coverage and barely adequate measurement variability (per-segment variations of roughly 0.16 mL-blood / g-tissue / min). We will address these limitations by developing and optimizing innovative new labeling schemes that enable evaluation of all 17 left ventricular segments, while taking into account cardiac motion, pulsatile flow, and potential sources of artifact. We will also integrate several new MRI technologies, for the first time, into the cardiac ASL experiment: simultaneous multi-slice imaging, background suppression, and blood pool suppression. Approach: The new test will be developed and experimentally optimized in a porcine model of CAD. We will first develop and optimize a labeling method that is compatible with whole-heart spatial coverage and maximizes the strength of the ASL signal. We will then develop and optimize an imaging method that interrogates all 17 left ventricular segments and maximizes the ASL temporal signal-to-noise ratio. After this is completed, we will perform a clinical evaluation of the optimized ASL-MRI stress test in patients with suspected CAD, and will compare the new test with both single-photon emitted computed tomography (SPECT) and invasive coronary angiography with fractional flow reserve (FFR). We will determine test-retest reproducibility of the new test in a subset of the patients. This study will enable whole-heart ASL-MRI stress testing, optimize and validate its ability to measure myocardial perfusion reserve, and enhance its feasibility as a firs-line test for CAD screening. Broader Impact: The proposed myocardial perfusion stress test could have a broader role for screening of patients with suspected CAD, due to its safety and its potential for simplicity and low cost. The technical work, particularly the labeling and imaging schemes, are likely to have implications for kidney and liver ASL-MRI. Finally, this work will provide training projects for postdoctoral, graduate, and undergraduate engineering students and clinical fellows interested in advanced cardiovascular imaging.

Public Health Relevance

Many patients undergo cardiac stress testing to check for signs of heart disease or to check their heart health before a major surgery. The goal of this research is to develop new safer testing options that may be more appropriate for use in patients who have to be checked often, such as those suffering from kidney failure.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL130494-01A1
Application #
9124428
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Danthi, Narasimhan
Project Start
2016-07-01
Project End
2020-06-30
Budget Start
2016-07-01
Budget End
2017-06-30
Support Year
1
Fiscal Year
2016
Total Cost
$446,944
Indirect Cost
$164,868
Name
University of Southern California
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90032
Landes, Vanessa L; Nayak, Krishna S (2018) Simple method for RF pulse measurement using gradient reversal. Magn Reson Med 79:2642-2651
Jao, Terrence R; Nayak, Krishna S (2018) Demonstration of velocity selective myocardial arterial spin labeling perfusion imaging in humans. Magn Reson Med 80:272-278