Assessing Mitochondrial Metabolism by Magnetization Transfer MR Fingerprinting

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DESCRIPTION (provided by applicant): Magnetic Resonance Spectroscopy (MRS) provides a powerful tool to interrogate various aspects to tissue metabolism. In particular, phosphorus-31 (31P) magnetization transfer spectroscopy (MT-MRS) has long been proposed as a means of measuring ATP synthesis rate in vivo. However, current 31P MT-MRS methods require prohibitively long data acquisition time to accurately quantify ATP synthesis rate. On the other hand, recent development of magnetic resonance fingerprinting (MRF) method provides a completely new framework of data acquisition that allows simultaneous measurement of several tissue properties, including relaxation times, at drastically reduced acquisition time. The measurement of chemical exchange rate in MT-MRS involves the measurement of the apparent relaxation time (T1app), i.e., the chemical exchange modified T1 relaxation, which is highly analogous to the measurement of T1 in proton imaging. Therefore, the overall objective of this proposal is to develop and validate novel 31P MT-MRF technique for fast and accurate quantification of ATP synthesis rate in hearts. This project has two specific aims. Aim 1 has three parts: 1) designing and evaluating 31P MT-MRF methods by computer simulation; 2) implementing and optimizing the 31P MT-MRF methods in phantom experiments, and 3) validating the 31P MT-MRF methods against established 31P MT-MRS methods in perfused hearts under varying workload. In Aim 2, the feasibility of performing spatially resolved measurement of chemical exchange rate by 31P MT-MRF will be investigated. A compressed sensing spiral 31P chemical shift imaging (CSI) sequence will be developed that will lead to 92-fold acceleration over the Cartesian CSI method. The 31P MT-MRF CSI method will be validated in rat model of ischemia/reperfusion injury in skeletal muscle. Methods developed in this pre-clinical project will lay the foundation for the development of clinical methods that can be applied to evaluating metabolic function in a variety of metabolic diseases such as diabetes and obesity.