EFFICIENT MAPPING OF ARTERIAL SPIN LABELING USING 3D GRASE IMAGING

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The overall goal of this project is to develop optimized protocols for quantitative measurements of cerebral blood flow (CBF), which provide improved signal and contrast to noise, resolution as well as sensitivity and are optimized and validated for specific applications to support the research projects and clinical applications of the Resource Center. Specific Aim1: Develop Dynamic ASL with multi-bolus Hadamard encoding: Resent results show ATT measured in time series ASL images may be a useful biomarker in differentiating mild cognitive dementia for Alzheimer's disease. The time coarse data is obtained by repeating the ASL measurements with incremented TI to obtain signal time curves. A novel cycled labeling scheme will encode flow changes with multiple pulsed boli within each of several cycles of ASL image acquisition. We will develop a novel method of Hadamard encoding in cycled ASL sequences to obtain many boli of shorter durations and to obtain several times higher SNR or reduce acquisition time and improved curve fitting of different vascular compartments to evaluate dynamic signal. Specific Aim 2: Development of Multiple-Echo 3D GRASE Acquisition: We aim to extend 3D ASL GRASE to dual-echo and multiple echo time (TE) acquisitions that provide the T2-relaxation parameterization of the ASL signal. To obtain this information, we will develop well controlled pulse sequences timing changes utilizing both single acquisition and multiple data acquisitions with an encoded variable TE parameters. eter.