The impact of optimal RF coil-combination on whole-brain sub-millimetre resolution perfusion imaging at 7T
Sriranga Kashyap1,2, Dimo Ivanov2, Roy A. M. Haast3, Francisco J. Fritz4, Robbert L. Harms2, Benedikt A. Poser2, and Kamil Uludag5,6
1Techna Institute, University Health Network, Toronto, ON, Canada, 2Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands, 3Aix-Marseille Universite, CNRS, CRMBM, Marseille, France, 4Institute for Systems Neuroscience, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany, 5Techna Institute & Koerner Scientist in MR Imaging, University Health Network, Toronto, ON, Canada, 6Center for Neuroscience Imaging Research, Institute for Basic Science & Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Korea, Republic of
In this work, we use 3D-EPI ASL to acquire perfusion maps of the human brain at an unprecedented spatial resolution of 0.7 mm isotropic at 7T. This multi-session, single-subject ASL dataset offers a unique opportunity to investigate the cortical distribution of baseline perfusion across and within brain areas, as well as studying the physiological basis for the interpretation of laminar and columnar fMRI. In this abstract, we use an open-source, memory-efficient, CPU/GPU accelerated coil-combine Python toolbox to probe the impact of using covariance-weighted sum-of-squares (CovSoS) and tSNR optimised RF coil-combination (STARC) on high-resolution perfusion imaging at 7T.
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