Abstract #3449

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

Adam V. Dvorak^1,2, Guillaume Gilbert³, Alex L. MacKay^1,4, and Shannon H. Kolind^1,2,4,5

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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