Literature DB >> 28732674

3D-MB-MUSE: A robust 3D multi-slab, multi-band and multi-shot reconstruction approach for ultrahigh resolution diffusion MRI.

Iain P Bruce1, Hing-Chiu Chang2, Christopher Petty3, Nan-Kuei Chen4, Allen W Song3.   

Abstract

Recent advances in achieving ultrahigh spatial resolution (e.g. sub-millimeter) diffusion MRI (dMRI) data have proven highly beneficial in characterizing tissue microstructures in organs such as the brain. However, the routine acquisition of in-vivo dMRI data at such high spatial resolutions has been largely prohibited by factors that include prolonged acquisition times, motion induced artifacts, and low SNR. To overcome these limitations, we present here a framework for acquiring and reconstructing 3D multi-slab, multi-band and interleaved multi-shot EPI data, termed 3D-MB-MUSE. Through multi-band excitations, the simultaneous acquisition of multiple 3D slabs enables whole brain dMRI volumes to be acquired in-vivo on a 3 T clinical MRI scanner at high spatial resolution within a reasonably short amount of time. Representing a true 3D model, 3D-MB-MUSE reconstructs an entire 3D multi-band, multi-shot dMRI slab at once while simultaneously accounting for coil sensitivity variations across the slab as well as motion induced artifacts commonly associated with both 3D and multi-shot diffusion imaging. Such a reconstruction fully preserves the SNR advantages of both 3D and multi-shot acquisitions in high resolution dMRI images by removing both motion and aliasing artifacts across multiple dimensions. By enabling ultrahigh resolution dMRI for routine use, the 3D-MB-MUSE framework presented here may prove highly valuable in both clinical and research applications.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  3D multi-slab EPI; MUSE; Multi-band imaging; Multi-shot EPI; Ultrahigh spatial resolution diffusion MRI

Mesh:

Year:  2017        PMID: 28732674      PMCID: PMC5676310          DOI: 10.1016/j.neuroimage.2017.07.035

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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Journal:  Neuroimage       Date:  2013-01-28       Impact factor: 6.556

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9.  Diffusion imaging of whole, post-mortem human brains on a clinical MRI scanner.

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10.  Scan time reduction for readout-segmented EPI using simultaneous multislice acceleration: Diffusion-weighted imaging at 3 and 7 Tesla.

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3.  High-fidelity, high-isotropic-resolution diffusion imaging through gSlider acquisition with B 1 + and T1 corrections and integrated ΔB0 /Rx shim array.

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Journal:  Magn Reson Med       Date:  2019-08-01       Impact factor: 4.668

4.  Motion-robust sub-millimeter isotropic diffusion imaging through motion corrected generalized slice dithered enhanced resolution (MC-gSlider) acquisition.

Authors:  Fuyixue Wang; Berkin Bilgic; Zijing Dong; Mary Kate Manhard; Ned Ohringer; Bo Zhao; Melissa Haskell; Stephen F Cauley; Qiuyun Fan; Thomas Witzel; Elfar Adalsteinsson; Lawrence L Wald; Kawin Setsompop
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5.  Self-navigation for 3D multishot EPI with data-reference.

Authors:  Steen Moeller; Sudhir Ramanna; Christophe Lenglet; Pramod K Pisharady; Edward J Auerbach; Lance Delabarre; Xiaoping Wu; Mehmet Akcakaya; Kamil Ugurbil
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6.  Simultaneous and inherent correction of B0 and eddy-current induced distortions in high-resolution diffusion MRI using reversed polarity gradients and multiplexed sensitivity encoding (RPG-MUSE).

Authors:  Iain P Bruce; Christopher Petty; Allen W Song
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7.  qModeL: A plug-and-play model-based reconstruction for highly accelerated multi-shot diffusion MRI using learned priors.

Authors:  Merry Mani; Vincent A Magnotta; Mathews Jacob
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8.  Distortion-free, high-isotropic-resolution diffusion MRI with gSlider BUDA-EPI and multicoil dynamic B0 shimming.

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Review 9.  Diffusion Imaging in the Post HCP Era.

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10.  High-fidelity, accelerated whole-brain submillimeter in vivo diffusion MRI using gSlider-spherical ridgelets (gSlider-SR).

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