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PEC-GRAPPA reconstruction of simultaneous multislice EPI with slice-dependent 2D Nyquist ghost correction.

Research paper by Yilong Y Liu, Mengye M Lyu, Markus M Barth, Zheyuan Z Yi, Alex T L ATL Leong, Fei F Chen, Yanqiu Y Feng, Ed X EX Wu

Indexed on: 29 Oct '18Published on: 29 Oct '18Published in: Magnetic Resonance in Medicine



Abstract

To provide simultaneous multislice (SMS) EPI reconstruction with k-space implementation and robust Nyquist ghost correction. 2D phase error correction SENSE (PEC-SENSE) was recently developed for Nyquist ghost correction in SMS EPI reconstruction for which virtual coil simultaneous autocalibration and k-space estimation (VC-SAKE) was used to remove slice-dependent Nyquist ghosts and intershot 2D phase variations in multi-shot EPI reference scan. However, masking coil sensitivity maps to exclude background region in PEC-SENSE and manually selecting slice-wise target ranks in VC-SAKE are cumbersome procedures in practice. To avoid masking, the concept of PEC-SENSE is extended to k-space implementation and termed as PEC-GRAPPA. Furthermore, a singular value shrinkage scheme is incorporated in VC-SAKE to circumvent the empirical slice-wise target rank selection. PEC-GRAPPA was evaluated and compared to PEC-SENSE with/without masking and 1D linear phase correction GRAPPA. PEC-GRAPPA robustly reconstructed SMS EPI images from 7T phantom and human brain data, effectively removing the phase error-induced artifacts. The resulting residual artifact level and temporal SNR were comparable to those by PEC-SENSE with careful tuning. PEC-GRAPPA outperformed PEC-SENSE without masking and 1D linear phase correction GRAPPA. Our proposed PEC-GRAPPA approach effectively removes the artifacts caused by Nyquist ghosts in SMS EPI without cumbersome tuning. This approach provides a robust and practical implementation of SMS EPI reconstruction in k-space with slice-dependent 2D Nyquist ghost correction. © 2018 International Society for Magnetic Resonance in Medicine.