  Simultaneous multi-slice (SMS) imaging accelerates MRI data acquisition by
exciting multiple image slices simultaneously. Overlapping slices are then
separated using a mathematical model. Several parameters used in SMS
reconstruction impact the quality of final images. Therefore, finding an
optimal set of reconstruction parameters is critical to ensure that SMS
acceleration does not significantly degrade resulting image quality.
  Gradient-echo echo planar imaging (EPI) data were acquired with a range of
SMS acceleration factors from volunteers. Images were collected using two head
coils (a 48-channel array and a smaller 32-channel array). Data from these
coils were reconstructed offline using a range of coil compression factors and
reconstruction kernel parameters. A hybrid space (ky-x), externally-calibrated
coil-by-coil slice unaliasing approach was used for image reconstruction. The
resulting SMS images were compared with identical EPI data acquired without
SMS. A functional MRI (fMRI) experiment was also performed and group analysis
results were compared between data sets reconstructed with different coil
compression levels.
  The 32-channel coil with smaller dimensions outperformed the larger
48-channel coil in our experiments. Generally, a large calibration region and
small kernel sizes in ky direction improved image quality. Use of
regularization in the kernel fitting procedure had a notable impact. With
optimal selection of other hyperparameters in the hybrid space SMS unaliasing
algorithm, coil compression caused small reduction in quality in SMS
accelerated images. Similarly, group analysis of fMRI results did not show a
significant influence of coil compression on resulting image quality.
  Hyperparameters used in SMS reconstruction need to be fine-tuned once the
experimental factors such as the RF receive coil and SMS factor have been
determined.
