Abstract #0841

Improving temporal resolution of 3D Arterial Spin Labeling perfusion imaging by combining CAIPIRINHA encoding and spatio-temporal TGV reconstruction

Stefan M. Spann¹, Xingfeng Shao², Danny JJ Wang², Christoph S. Aigner¹, Matthias Schloegl¹, Kristian Bredies³, and Rudolf Stollberger^1,4

¹Institute of Medical Engineering, Graz University of Technology, Graz, Austria, ²Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, ³Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria, ⁴BioTechMed-Graz, Graz, Austria

Pseudo-continuous arterial spin labeling combined with 3D segmented readouts is recommended for acquiring ASL perfusion data. However, the total number of k-space encodings limits the trade-off between motion sensitivity and image blurring. To tackle this problem we implemented an accelerated 3D-GRASE sequence with a time-dependent 2D-CAIPIRINHA sampling pattern to increase the temporal incoherence between averages or PLDs. High quality images can be gained from the under-sampled time series by a variational image reconstruction approach with total-generalized-variation (TGV) regularization in space and time. This allows acquisition of single-shot 3mm isotropic ASL data with whole brain coverage within 1min22sec.

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