Abstract
Purpose: To develop a reconstruction pipeline that intrinsically accounts for both simultaneous multislice echo planar imaging (SMS-EPI) reconstruction and dynamic slice-specific Nyquist ghosting correction in time-series data. Methods: After 1D slice-group average phase correction, the separate polarity (i.e., even and odd echoes) SMS-EPI data were unaliased by slice GeneRalized Autocalibrating Partial Parallel Acquisition. Both the slice-unaliased even and odd echoes were jointly reconstructed using a model-based framework, extended for SMS-EPI reconstruction that estimates a 2D self-phase map, corrects dynamic slice-specific phase errors, and combines data from all coils and echoes to obtain the final images. Results: The percentage ghost-to-signal ratios (%GSRs) and its temporal variations for MB3R(y)2 with a field of view/4 shift in a human brain obtained by the proposed dynamic 2D and standard 1D phase corrections were 1.37 +/- 0.11 and 2.66 +/- 0.16, respectively. Even with a large regularization parameter lambda applied in the proposed reconstruction, the smoothing effect in fMRI activation maps was comparable to a very small Gaussian kernel size 1 x 1 x 1 mm(3). Conclusion: The proposed reconstruction pipeline reduced slice-specific phase errors in SMS-EPI, resulting in reduction of GSR. It is applicable for functional MRI studies because the smoothing effect caused by the regularization parameter selection can be minimal in a blood-oxygen-level-dependent activation map.
