Abstract #1145

The impact of optimal RF coil-combination on whole-brain sub-millimetre resolution perfusion imaging at 7T

Sriranga Kashyap^1,2, Dimo Ivanov², Roy A. M. Haast³, Francisco J. Fritz⁴, Robbert L. Harms², Benedikt A. Poser², and Kamil Uludag^5,6

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

Synopsis

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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