Magnetic Resonance Imaging (MRI) has been well established for non-invasive measurement of dynamic physiological process, such as neuronal activation coupled to relatively slow hemodynamic responses at temporal resolution of seconds. Due to the advantages of RF technology, particularly multiple channel RF array systems, MRI can obtain spatial information embedded in the RF coil array directly with minimal phase encoding steps. This potentially enables order- of-magnitude acceleration or minimal acoustic noise during data acquisitions because of minimal gradient switching. In this grant, we propose the dynamic inverse imaging (InI) to achieve millisecond temporal resolution. InI is implemented based on the large-N array coil technology, modified pulse sequence in contrast preparation and data acquisition, as well as image reconstruction algorithms inspired by electroencephalography (EEG) and magnetoencephagraphy (MEG) in to order to generate time-resolved statistical inference on dynamics of the MR measurements. In this proposal, we seek the development and optimization of MR InI on RF array coil and sequence development, as well as data reconstruction and analysis. We will explore the application of dynamic MR InI to two major applications in the proposed pilot studies, including (1) characterization of extremely high temporal BOLD hemodynamic time curves and (2) reduction of acoustic noise during dynamic MRI acquisitions due to minimal gradient switching used in InI. ? ? ?
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