Rapid Real-Time Cardiovascular MRI for Detecting Coronary Artery Disease

Project Summary/Abstract: Coronary artery disease (CAD) is a leading cause of sickness and death in the US. Noninvasive cardiac imaging plays a vital role in diagnosing, risk stratifying, and guiding treatment decisions in patients with known or suspected CAD. However, the limitations of current imaging strategies are well documented. In a previous study of nearly 400,000 patients without known heart disease undergoing elective cardiac catheterization following a positive pre-test (mostly stress echocardiography and nuclear perfusion imaging), approximately 60% of them were found to not have obstructive CAD. According to recent AHA guidelines, radiation risk is an important consideration when choosing a diagnostic test. Indeed, there is an unmet clinical need to advance radiation-free diagnostic imaging tests for accurate diagnosis of functionally significant obstructive CAD. Since no single test is 100% accurate, one cost-effective approach to increase accuracy is to perform a comprehensive assessment within a single modality. Among available cardiac imaging modalities, MRI is arguably the most versatile and capable of a comprehensive evaluation of CAD, including cardiac function, perfusion, coronary angiography, and viability, while not requiring ionizing radiation. Despite substantial successes from both basic research and clinical trials, and even after decades of advancements, cardiac MRI continues to be hampered by (i) long exam times (~ 60-90 min), (ii) complexities in operation such as breathholding requirements, and (iii) poor performance in patients with arrhythmias. To overcome these obstacles, we will develop a rapid (15 min), real-time (arrhythmia and motion insensitive) cardiovascular MRI protocol that can be performed during free breathing, while producing diagnostic accuracy comparable to a standard clinical MRI protocol (60-90 min). The central hypothesis of this application is that a rapid (15-min) MRI protocol produces diagnostic accura