Blipped-Controlled Aliasing in Parallel Imaging (blipped-CAIPI) for simultaneous multi-slice EPI with reduced g-factor penalty

By Kawin Setsompop, Borjan A. Gagoski, Jonathan R. Polimeni, Thomas Witzel, Van J. Wedeen, Lawrence L. Wald. Magnetic Resonance in Medicine, 2011

1,292 citations recorded by the source corpus.

Simultaneous multislice Echo Planar Imaging (EPI) acquisition using parallel imaging can decrease the acquisition time for diffusion imaging and allow full‐brain, high‐resolution functional MRI (fMRI) acquisitions at a reduced repetition time (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 interslice 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 3 T and 7 T using 32‐channel radio frequency (RF) coil brain arrays. The Monte‐Carlo simulated average g‐factor penalty of the 3‐fold slice‐accelerated acquisition with interslice shifts is <1% at 3 T (compared with 32% without slice shift). Combining 3× slice acceleration with 2× inplane acceleration, the g‐factor penalty becomes 19% at 3 T and 10% at 7 T (compared with 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 3‐fold faster acquisition showed no noticeable degradation. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc.

Subfields: Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/374b5fcf4b17df02f93fd0bc73c3a5f095ef1eaf

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In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

ICA-based artefact and accelerated fMRI acquisition for improved Resting State Network imaging (2014, methodology): “…MR images were acquired using a MEMPRAGE sequence (TR = 2530 ms, TE = 1.79/3.65/5.51/7.37 ms, (Feinberg et al., 2010; Moeller et al., 267 2010; Setsompop et al., 2012; Xu et al., 2013); The same pre-processing was performed on both Standard and 278 MB6 rfMRI data using FSL (Jenkinson et al.,…”
An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging (2016, background): “Recent advances in multi-band imaging (Moeller et al., 2010; Setsompop et al., 2012 or Uğurbil et al., 2013)mean that data of unprecedented quality can be acquired with several hundred diffusion directions and multiple shells/b-values (S.N. Sotiropoulos et al., 2013 or Setsompop et al., 2013).”
Differentiating BOLD and Non-BOLD Signals in fMRI Time Series Using Multi-Echo EPI (2011, background): “, 2006) and multislice excitation (Feinberg et al., 2010; Moeller et al., 2010; Setsompop et al., 2011) should allow for substantial increases in resolution and efficiency.”
Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project (2013, methodology): “A coil-by-coil data driven (CCDD) slice-GRAPPA technique was therefore proposed as a solution (Setsompop et al., 2012), which is employed in our HCP data production at 3 T and in our distribution of image acquisition and reconstruction software to Siemens sites through the “C2P” agreement (there are”
Advances in diffusion MRI acquisition and processing in the Human Connectome Project (2013, methodology): “A multiband factor of 3 and a controlled aliasing PE shift by FOV/3 (Setsompop et al., 2012) is used.”
Simultaneous multislice (SMS) imaging techniques (2015, methodology): “The 3D perspective of slice encoding is equivalent to a 2D perspective with shifted slices (7,18), and RF phase encoding is equivalent to kz -phase encoding across the slices.”
Multi-compartment microscopic diffusion imaging (2016, methodology): “52 s was performed using a multi-band sequence (Setsompop et al., 2012) with slice acceleration factor of 3.”
A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series (2014, methodology): “Finally, we acknowledge that motion artifact control may also benefit from alternate acquisition approaches, which have not been explicitly discussed here, such as high-speed imaging (Setsompop et al., 2012), 3D imaging, multi-band imaging, multi-echo imaging (Poser et al.”
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The Human Connectome Project’s Neuroimaging Approach (2016, methodology): “It also provides data entry and import tools Hopf’s area 55b, Brodmann’s area 44, retrosplenial cortex (RSC), ventral lateral intraparietal cortex (LIPv), the superior frontal language area (SFL), the second parieto-occipital sulcus area (POS2), the perisylvian language area (PSL), the middle…”
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The WU-Minn Human Connectome Project: An Overview (2013, methodology): “The most significant pulse sequence development for the HCP was the implementation and optimization of slice-accelerated multiband (MB) acquisitions for fMRI and dMRI (Feinberg et al., 2010; Larkman et al., 2001; Moeller et al., 2008, 2010; Setsompop et al., 2012; Ugurbil et al., 2013).”