Ultra-fast cerebral blood flow imaging for quantifying brain dynamics

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Abstract/Project Summary Blood oxygenation level dependent (BOLD) fMRI is widely used in neuroscience studies. Technical advancement in the recently years has enabled BOLD signals to be acquired at sub-second temporal resolution, opening a new window for examining functional dynamics of the human brain, e.g. resting- state fMRI. The BOLD signal originates from the mismatch between cerebral blood flow (CBF) and metabolism changes, and is complex; it serves as an indirect measure of neural activities. A direct observation of CBF changes can provide information that is more closely coupled to neural activities. Arterial spin labeling (ASL) fMRI measures CBF changes noninvasively and quantitatively, therefore may provide valuable dynamic information that is not readily measured with BOLD alone. Currently the existing ASL fMRI methods are limited by low temporal resolution and signal-to-noise ratio (SNR), mainly due to acquisition delays required for the labeled blood to reach the brain tissue. Velocity- selective (VS) ASL shows promises in reducing the delays, but the existing labeling strategies are not optimal for imaging CBF at high temporal resolution, such as below 2 s, or do not have sufficient coverage of the brain. In this proof-of-concept development project, we propose a completely new VS labeling strategy to overcome the problems of existing labeling methods, aiming for functional CBF measurements with substantially increased temporal resolution (~ 1.5 s), SNR efficiency and a good coverage. The ultra-fast and quantitative CBF imaging method developed in this project should help advance our understanding of brain dynamics under healthy and diseased conditions, and may be an imaging tool of choice for individual comparison and/or longitudinal studies.