Blipped‐controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g‐factor penalty

Abstract

Simultaneous multi-slice EPI acquisition using parallel imaging can decrease the acquisition time for diffusion imaging and allow full-brain, high resolution fMRI acquisitions at a reduced TR. However, the unaliasing of simultaneously acquired, closely spaced slices can be difficult, leading to a high g-factor penalty. We introduce a method to create inter-slice image shifts in the phase encoding direction to increase the distance between aliasing pixels. The shift between the slices is induced using sign- and amplitude-modulated slice-select gradient blips simultaneous with the EPI phase encoding blips. This achieves the desired shifts but avoids an undesired “tilted voxel” blurring artifact associated with previous methods. We validate the method in 3× slice-accelerated spin-echo and gradient-echo EPI at 3T and 7T using 32-channel RF coil brain arrays. The Monte-Carlo simulated average g-factor penalty of the 3-fold slice accelerated acquisition with inter-slice shifts is <1% at 3T (compared to 32% without slice-shift). Combining 3× slice acceleration with 2× in-plane acceleration, the g-factor penalty becomes 19% at 3T and 10% at 7T (compared to 41% and 23% without slice-shift). We demonstrate the potential of the method for accelerating diffusion imaging by comparing the fiber orientation uncertainty, where the three-fold faster acquisition showed no noticeable degradation.

Quantitative mapping of the per‐axon diffusion coefficients in brain white matter

“…The spin‐echo echo‐planar scan with nominal flip angle of ${78}^{°}$ and refocusing flip angle of ${160}^{°}$ was performed using a multiband sequence 38, 39, 40 with slice acceleration factor of 3. The diffusion data were acquired with in‐plane phase encoding in both right‐to‐left and left‐to‐right directions.…”

“…The acquisition time was circa $36\hspace{0.17em}\min$. After unaliasing the simultaneously acquired slices channel by channel 38, 39, 40, SENSE1 multiple‐coil combination was applied 41 and the magnitude signal was stored. The dataset used in the study came from an adult male in the age group between 25 and 35 years.…”

Accurate modeling of temporal correlations in rapidly sampled fMRI time series

“…This sequence utilizes the blipped‐CAIPI approach for controlled aliasing of simultaneously excited slices (Setsompop et al, 2012). Sequence parameters were chosen to be similar to those typically used for moderate resolution whole‐brain fMRI studies at 3 T and are summarized in Table 1.…”

“…Increasing the number of samples is an effective way of increasing statistical power. The emergence of advanced MRI acquisition strategies such as parallel (Griswold et al, 2002; Pruessmann, Weiger, Scheidegger, & Boesiger, 1999) and multiband (or simultaneous multi‐slice) imaging (Breuer et al, 2005; Larkman et al, 2001; Setsompop et al, 2012) have enabled sampling rates to be greatly increased by reducing the time taken to acquire a single volume. Reducing the volume acquisition time not only allows the acquisition of more samples within the same total duration but also reduces sensitivity to intravolume motion and improves the sampling of physiological noise, which can then be more effectively removed by low‐pass filtering the time series (Narsude, Gallichan, van der Zwaag, Gruetter, & Marques, 2016; Todd et al, 2017).…”

High‐resolution gradient‐recalled echo imaging at 9.4T using 16‐channel parallel transmit simultaneous multislice spokes excitations with slice‐by‐slice flip angle homogenization

“…The 10‐s averaged maximum local SAR estimated for this protocol was 9.8 W/kg. All SMS‐GRE images were reconstructed in MATLAB using slice‐GRAPPA 33 with a 7 × 6 kernel, using a low‐resolution (matrix size = 64 × 64) single‐band spokes acquisition as reference. The extra acquisition time for the reference and noise scans were 58 s for the 12‐slice protocols and 2:02 min for the 48‐slice protocol.…”