Optimization and Acceleration of Multi-Band EPI Reconstruction Using the Reduced Reference K-Space Window

Wanyong Shin¹, Erik B. Beall¹, Mark J. Lowe¹

Simultaneous excitation of multiple slices using multi-band (MB) radio-frequency (RF) excitation echo planar imaging (EPI) has shown potential to increase the spatial and temporal resolution. The Slice-GRAPPA method calculates a linear interpolation kernel for each slice of MB accelerated k-space and de-aliases images using the estimated kernel. It is known that the interpolation kernel size, acceleration factor (R value) and the number of reference lines (ACS line number) determine the reconstructed image quality in in-plane parallel imaging (PI) technique. Since Slice-GRAPPA employs the same basic principle as the GRAPPA technique, we hypothesize that the size of the interpolation kernel and data used to estimate the kernel could affect the performance of MB de-aliasing. In this study, we evaluate MB de-aliasing performance while varying the sizes of interpolation kernel size and fitted data using simulation and show considerable reductions in compute time are possible with no apparent loss in data quality.