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Abstract #3449

Multi-Component Quantitative T2 Shuffling: Accelerating Myelin Water Imaging by 20-30x

Adam V. Dvorak1,2, Guillaume Gilbert3, Alex L. MacKay1,4, and Shannon H. Kolind1,2,4,5
1Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, 2International Collaboration on Repair Discoveries (ICORD), Vancouver, BC, Canada, 3MR Clinical Science, Philips Canada, Markham, ON, Canada, 4Radiology, University of British Columbia, Vancouver, BC, Canada, 5Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada

Multi-component quantitative T2 mapping can provide a range of valuable, in-vivo biomarkers, but is limited by lengthy acquisition times. Here we introduce multi-component quantitative T2 shuffling, a subspace-constrained CS method for reconstructing highly under-sampled multi-component relaxation mapping data using principal components of a temporal basis. We demonstrated reconstruction of myelin water imaging data with simulated under-sampling acceleration factors of ~20-30, which could provide accurate images, higher resolution and fit-to-noise ratios, and improved metric maps in a fraction of the acquisition time.

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