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Abstract #3936

Effect of Coil Compression on tSNR, DVARS and Computation Time on Simultaneous Multi Slice Imaging

Volkan Emre Arpinar1,2, Kevin Koch1,2, Sampada Bhave1, L Tugan Muftuler2,3, Baolian Yang4, S Sivaram Kaushik4, Suchandrima Banerjee4, and Andrew Nencka1,2

1Radiology, Medical College of Wisconsin, Milwaukee, WI, United States, 2Center for Imaging Research, Medical College of Wisconsin, Milwaukee, WI, United States, 3Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States, 4GE Healthcare, Waukesha, WI, United States

Simultaneous multi-slice (SMS) imaging requires the application of a parallel imaging algorithm for image unaliasing. Including coil compression in SMS image reconstruction offers a benefit of reducing the computational load of the reconstruction algorithm and can better condition the matrix which is inverted in the unaliasing algorithm. The goal of this abstract is to evaluate the optimal level of coil compression to utilize with slice-ARC in Human Connectome Project (HCP) compliant, and other SMS protocols with a Nova Medical 32-channel head coil. It was found that, for all levels of coil compression, application of the compression algorithm yielded a benefit in reconstruction performance. Additionally, it was found that the application of coil compression does not significantly impact the selection of a CAIPI shift factor unless a coil compression of 50% or greater is used.

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