Summary: Ischemic heart disease (IHD), also called coronary artery disease, is a major healthcare problem that affects over 20 million Americans and costs our nation an estimated $82.8 billion each year. Myocardial perfusion imaging is a proven tool to detect and characterize IHD. While Single Photon Emission Computed Tomography (SPECT) imaging is widely used in the U.S., MRI offers higher resolution perfusion images without ionizing radiation. However, perfusion MRI requires injecting gadolinium-based contrast agents to identify regions of perfusion deficit. Gadolinium is problematic in patients with poor kidney function, who are excluded from these cardiac MR perfusion studies. Cardiac T1 mapping recently has shown promise to identify and characterize coronary artery disease without the use of gadolinium. T1 mapping is performed in a pharmacologically induced stress state and again in the resting state of the heart to compute T1 differences as a percentage known as T1 reactivity. By reflecting blood volume changes, T1 reactivity has shown to be promising to identify ischemic regions in the myocardium. T1 reactivity is a promising biomarker not only for triaging patients for catheterization but also in longitudinal studies to determine the efficacy of therapy and to predict future cardiac events. However, existing protocols are sub-optimal to reliably detect T1 changes at stress. It is also difficult for patients to hold their breath for long durations at stress and inadequate motion compensation leads to poor T1 map quality. The limited time window of pharmacological stress can limit the slice coverage. In order to fully evaluate the potential of the non-contrast T1 approach, we plan to develop a robust T1 mapping method that optimizes the T1 mapping protocol, by developing a robust motion compensation method and obtaining whole heart coverage within the limited time window and significantly reduce the breath-hold duration. Specific aims of the project are (1) to optimize T1 mapping protocol and develop a robust image registration method for large breathing motion at stress (2) to develop novel simultaneous multi-slice acquisition methods and state-of-the-art deep learning techniques for rapid, whole- heart T1 mapping, and (3) to validate the new rapid T1 mapping by comparing it to the current gadolinium- based perfusion method for IHD detection. Our team and institution have deep cardiac MRI experience and the technology needed to successfully execute all aspects of this project. The success of our project will deliver a game-changing MRI technology for patients with suspected IHD: rapid, whole-heart coverage T1 mapping without the use of gadolinium, and validation studies that accurately characterize the performance of the new method.