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Abstract #2053

A Flexible Framework of Perfusion FMRI Using Asymmetric Label and Control Acquisitions with Background Suppressed PCASL GRASE

MAGNA25Lirong Yan1, Emily Kilroy1, Danny JJ Wang1

1Neurology, University of California, Los Angeles, Los Angeles, CA, United States

Perfusion fMRI using arterial spin labeling (ASL) is advantageous for quantifying perfusion both at rest and during task activation. However, it is limited by low temporal resolution and sensitivity. With pseudo-continuous ASL (pCASL) with background suppressed (BS) 3D GRASE, the temporal resolution and sensitivity of perfusion fMRI can be improved by skipping control acquisitions without compromising the quantification of cerebral blood flow. In this study, a flexible framework of perfusion fMRI was introduced by using asymmetric label and control acquisitions in pCASL with BS 3D GRASE which was validated using visual cortex stimulation.

Keywords

acquisition acquisitions activation adapted addition adjacent advantage advent allows analyses anatomic asymmetric background block blood bold cerebral channel checkerboard coil columns comprises compromised contamination continuous control correction cortex counterpart covariates defined degree delay design designed detected directly done duration dynamic easy efficiency error estimation event example existing explore expressed fern fewer flashing flexible flow framework full furthermore general gradient greater head healthy hybrid implemented improve improved included induced intensity inversion investigated label linear listed little maps matrix model modeled moreover motion much neurology normalization offers optimal outlined pairwise participated perfusion post processed processing product pseudo pulse quantification random reduced related relatively representative resolution respectively rest robust sensitive sensitivity separation series simultaneously slices smoothing spin stability steps stimulation studies subject subjects subtraction suggest suppressed system task temporal theory thereby took trio uneven unique vector visual volunteers