Chest pain or cardiac angina affects about 8 million U.S. adults and leads to more than 1.5 million hospitalizations per year with $190 billion in associated costs. However, nearly half of stable patients with cardiac angina who undergo coronary angiography are found to have no obstructive coronary artery disease. Microvascular coronary dysfunction (MCD) is known to be a major underlying etiology for anginal symptoms in the absence of obstructive coronary disease. By incorporating cross-disciplinary training components and mentored research, the proposed project aims to improve the non-invasive diagnosis of MCD based on cardiac magnetic resonance (CMR) first-pass myocardial perfusion imaging. CMR perfusion imaging provides a radiation-free approach for this predominantly female population and achieves a high spatial resolution thereby allowing for delineation of the subendocardial layer. However, despite major advances, there are fundamental challenges that limit the capability of current CMR methods to reliably detect MCD, most importantly the presence of the so-called dark-rim artifacts, which significantly reduce the accuracy and reliability of subendocardial myocardial perfusion reserve (MPR) measurements. In this project, we propose to develop an innovative perfusion CMR method that overcomes such limitations. Our central hypothesis is that the developed technique will significantly outperform conventional CMR in identifying patients with MCD. We will build upon our recent breakthrough work on qualitative improvements for perfusion CMR, specifically minimizing dark-rim artifacts and non-ECG-gated imaging, and will develop an innovative perfusion CMR method that enables accurate quantification of subendocardial MPR. This transition from qualitative to quantitative cardiac imaging research for the candidate leverages unique strengths of the multi-disciplinary mentoring team involved in this proposal with a track record for developing innovative CMR methods and clinical imaging research applied to CAD and MCD, including the NHLBI-sponsored WISE study. The outlined mentoring plan for the K99 phase incorporates a cross-disciplinary program designed to provide the candidate with an in-depth yet inevitably broad training in developing and applying quantitative cardiac imaging methodology, and to obtain skills necessary for transitioning into an independent academic career in the field of cardiac imaging. The research strategy in the R00 independent phase is designed to systematically develop an innovative artifact-minimized CMR perfusion imaging methodology, and to conduct a pilot patient study to obtain initial data on the effectiveness of the developed CMR method, thereby laying the groundwork for a subsequent independent grant application. Successful completion of this project will overcome major technical challenges in quantitative perfusion CMR imaging and will empower it with the capability to reliably detect impaired subendocardial MPR, which may provide a reliable tool for diagnosis and long-term monitoring of patients with suspected MCD, and potentially an end-point for clinical trials involving such patients.

Public Health Relevance

This K99/R00 Pathway to Independence Award application incorporates inter-disciplinary training components and mentored research with the aim of improving the non-invasive diagnosis of microvascular coronary dysfunction, which is increasingly recognized as an important diagnostic and therapeutic target. The research strategy is designed to systematically develop an innovative high-resolution cardiac MRI method that overcomes major shortcomings of the conventional methods. Successful completion of this project will overcome major technical challenges in quantitative perfusion CMR imaging and will empower it with the capability to reliably and accurately detect microvascular coronary dysfunction.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Transition Award (R00)
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Special Emphasis Panel (NSS)
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Fleg, Jerome L
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Cedars-Sinai Medical Center
Los Angeles
United States
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Sharif, Behzad; Motwani, Manish; Arsanjani, Reza et al. (2018) Impact of incomplete ventricular coverage on diagnostic performance of myocardial perfusion imaging. Int J Cardiovasc Imaging 34:661-669
Shaw, Jaime L; Nelson, Michael D; Wei, Janet et al. (2018) Inverse association of MRI-derived native myocardial T1 and perfusion reserve index in women with evidence of ischemia and no obstructive CAD: A pilot study. Int J Cardiol 270:48-53
Zhou, Zhengwei; Bi, Xiaoming; Wei, Janet et al. (2017) First-pass myocardial perfusion MRI with reduced subendocardial dark-rim artifact using optimized Cartesian sampling. J Magn Reson Imaging 45:542-555