Coronary artery disease (CAD) is the leading cause of death with responsible for one in six deaths in the US. Its burden on the health care system is gradually increasing and it is expected to pass $300 billion by 2035. Numerous methods are used to diagnose CAD. Invasive fractional flow reserve (FFR) measurements are considered the current clinical gold standard to diagnose CAD. However, its invasive nature increases risks and costs. Therefore, alternative non-invasive methods are appealing. Cardiac magnetic resonance imaging (CMR) is a radiation-free and non-invasive alternative to the FFR method. Recently, perfusion CMR was shown to be non-inferior to FFR. However, spatio-temporal resolution and coverage are still limited in CMR studies, hampering further clinical utility. In this project, my aim is to develop novel simultaneous multi-slice (SMS) image acquisition and reconstruction strategies to achieve higher resolution with whole heart coverage. On the image acquisition side, this project will optimize a recently proposed method in our lab, where outer volume suppression was utilized to suppress extra-cardiac signal (e.g. from the chest wall and the back). On the reconstruction side, my aim is to develop a new approach that combines advantages of different k-space interpolation methods to reduce leakage artifacts and noise artifacts in cardiac SMS imaging. Joint utilization of the two methods will enable highly accelerated perfusion imaging with 1.4 mm2 spatial resolution and 80 ms temporal resolution, as well as whole heart coverage. Successful completion of this study will result in robust high-quality whole-heart perfusion CMR, beyond what the current technology allows.
|Program type||Predoctoral Fellowship|
|Effective start/end date||01/01/2020 → 12/31/2021|