Feiyu Chen^{1}, Valentina Taviani^{2}, Joseph Y Cheng^{3}, Tao Zhang^{4}, Brian A Hargreaves^{3}, John M Pauly^{1}, and Shreyas S Vasanawala^{3}

Wave encoding was implemented in a variable-density single-shot fast spin echo (VD-SSFSE) pulse sequence. Auto-calibrated estimation of the wave-encoding point-spread function (PSF) and coil sensitivity maps was used. Images were reconstructed with parallel imaging and compressed sensing reconstruction. Compared to non-wave-encoded Cartesian imaging, wave-encoded VD-SSFSE achieves improved image quality with reduced aliasing artifacts at higher acceleration factors and with full k-space coverage, providing fast acquisitions and clinically relevant echo times.

A sinusoidal wave-encoding gradient (5.5 cycles, 12 mT/m amplitude),
played out during the readout of each *k*_{x} encoding line, was added to
a VD-SSFSE pulse sequence (Fig. 1a). VD under-sampling patterns with 20 central
PE lines of auto-calibration signals (ACS), 50-70 *k*_{y} views, and an
effective acceleration factor of about 5 were used (Fig. 1b). Over-sampling of
1.6-2.0 in the frequency-encoding (FE) direction was used to account for voxel
spreading effects due to wave encoding^{2}. The VRF schedule was controlled by prescribing first, minimum, and last
flip angles as well as the flip angle corresponding to the center of k-space. A
90° minimum flip angle was used to minimize signal loss due to cardiac
pulsation in the left lobe of the liver.

The under-sampled wave-encoded k-space was used to estimate the
wave-PSF^{3}. Auto-calibrated estimation of coil sensitivity maps^{4}
(ESPIRiT^{5}), and CS-SENSE image reconstruction^{6} with $$$\ell$$$1-wavelet regularization were performed in MATLAB and C (the BART toolbox^{7}).
Simulated g-factor maps of wave-encoded and non-wave-encoded acquisitions with
uniform under-sampling were compared using estimated coil sensitivity maps of a
32-channel torso coil (NeoCoil, Pewaukee, WI) for uniform sampling patterns.

Phantom and volunteer scans were performed with Institutional Review Board approval and informed consent at 3T (GE MR750, Waukesha, WI) using a 32-channel receive-only torso coil (NeoCoil, Pewaukee, WI) with FE along R/L and PE along A/P. Conventional Cartesian acquisitions were performed for comparison using the same sampling pattern and reconstruction framework.

[1] Taviani V, Litwiller DV, Tamir JI, Loening AM, Hargreaves BA, and Vasanawala SS. Variable Density Compressed Sensing Single Shot Fast Spin Echo. Proc. Intl. Soc. Mag. Reson. Med. 2016; 24: 618.

[2] Bilgic B, Gagoski BA, Cauley SF, Fan AP, Polimeni JR, Grant PE, Wald LL, Setsompop K. Wave-CAIPI for highly accelerated 3D imaging. Magnetic Resonance in Medicine. 2015; 73: 2152-2162.

[3] Chen F, Zhang T, Cheng JY, Pauly JM, and Vasanawala SS. Auto-Calibrating Wave-CS for Motion-Robust Accelerated MRI. Proc. Intl. Soc. Mag. Reson. Med. 2016; 24: 1857.

[4] Uecker M, Lai P, Murphy MJ, Virtue P, Elad M, Pauly J, Vasanawala SS, Lustig M. ESPIRiT - An Eigenvalue Approach to Autocalibrating Parallel MRI: Where SENSE meets GRAPPA. Magn Reson Med 2014; 71:990-1001.

[5] Curtis A, Bilgic B, Setsompop K, Menon RS, Anand CK. Wave-CS: Combining wave encoding and compressed sensing. Proc. Intl. Soc. Mag. Reson. Med. 2015; 23: 0082.

[6] Cauley SF, Setsompop K, Bilgic B, Bhat H, Gagoski B, Wald LL. Autocalibrated wave-CAIPI reconstruction; Joint optimization of k-space trajectory and parallel imaging reconstruction. Magnetic Resonance in Medicine. 2016; Epub ahead of print.

[7] Uecker M, Ong F, Tamir JI, Bahri D, Virtue P, Cheng JY, Zhang T, Lustig M. Berkeley Advanced Reconstruction Toolbox. Proc. Intl. Soc. Mag. Reson. Med. 2015; 23:2486.