Literature DB >> 23707579

Pushing the limits of in vivo diffusion MRI for the Human Connectome Project.

K Setsompop1, R Kimmlingen, E Eberlein, T Witzel, J Cohen-Adad, J A McNab, B Keil, M D Tisdall, P Hoecht, P Dietz, S F Cauley, V Tountcheva, V Matschl, V H Lenz, K Heberlein, A Potthast, H Thein, J Van Horn, A Toga, F Schmitt, D Lehne, B R Rosen, V Wedeen, L L Wald.   

Abstract

Perhaps more than any other "-omics" endeavor, the accuracy and level of detail obtained from mapping the major connection pathways in the living human brain with diffusion MRI depend on the capabilities of the imaging technology used. The current tools are remarkable; allowing the formation of an "image" of the water diffusion probability distribution in regions of complex crossing fibers at each of half a million voxels in the brain. Nonetheless our ability to map the connection pathways is limited by the image sensitivity and resolution, and also the contrast and resolution in encoding of the diffusion probability distribution. The goal of our Human Connectome Project (HCP) is to address these limiting factors by re-engineering the scanner from the ground up to optimize the high b-value, high angular resolution diffusion imaging needed for sensitive and accurate mapping of the brain's structural connections. Our efforts were directed based on the relative contributions of each scanner component. The gradient subsection was a major focus since gradient amplitude is central to determining the diffusion contrast, the amount of T2 signal loss, and the blurring of the water PDF over the course of the diffusion time. By implementing a novel 4-port drive geometry and optimizing size and linearity for the brain, we demonstrate a whole-body sized scanner with G(max) = 300 mT/m on each axis capable of the sustained duty cycle needed for diffusion imaging. The system is capable of slewing the gradient at a rate of 200 T/m/s as needed for the EPI image encoding. In order to enhance the efficiency of the diffusion sequence we implemented a FOV shifting approach to Simultaneous MultiSlice (SMS) EPI capable of unaliasing 3 slices excited simultaneously with a modest g-factor penalty allowing us to diffusion encode whole brain volumes with low TR and TE. Finally we combine the multi-slice approach with a compressive sampling reconstruction to sufficiently undersample q-space to achieve a DSI scan in less than 5 min. To augment this accelerated imaging approach we developed a 64-channel, tight-fitting brain array coil and show its performance benefit compared to a commercial 32-channel coil at all locations in the brain for these accelerated acquisitions. The technical challenges of developing the over-all system are discussed as well as results from SNR comparisons, ODF metrics and fiber tracking comparisons. The ultra-high gradients yielded substantial and immediate gains in the sensitivity through reduction of TE and improved signal detection and increased efficiency of the DSI or HARDI acquisition, accuracy and resolution of diffusion tractography, as defined by identification of known structure and fiber crossing. Published by Elsevier Inc.

Entities:  

Keywords:  DSI; Diffusion imaging; Gradient hardware; HARDI; MRI; Structural connectivity

Mesh:

Year:  2013        PMID: 23707579      PMCID: PMC3725309          DOI: 10.1016/j.neuroimage.2013.05.078

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


  63 in total

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Authors:  Antonio Tristán-Vega; Carl-Fredrik Westin
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4.  Reconstruction of MRI data encoded with arbitrarily shaped, curvilinear, nonbijective magnetic fields.

Authors:  Gerrit Schultz; Peter Ullmann; Heinrich Lehr; Anna M Welz; Jürgen Hennig; Maxim Zaitsev
Journal:  Magn Reson Med       Date:  2010-09-16       Impact factor: 4.668

5.  Quality assessment of high angular resolution diffusion imaging data using bootstrap on Q-ball reconstruction.

Authors:  Julien Cohen-Adad; Maxime Descoteaux; Lawrence L Wald
Journal:  J Magn Reson Imaging       Date:  2011-05       Impact factor: 4.813

6.  Spatially regularized compressed sensing for high angular resolution diffusion imaging.

Authors:  Oleg Michailovich; Yogesh Rathi; Sudipto Dolui
Journal:  IEEE Trans Med Imaging       Date:  2011-05       Impact factor: 10.048

7.  Sparse multi-shell diffusion imaging.

Authors:  Yogesh Rathi; O Michailovich; K Setsompop; S Bouix; M E Shenton; C F Westin
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Authors: 
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Authors:  David A Feinberg; Steen Moeller; Stephen M Smith; Edward Auerbach; Sudhir Ramanna; Matthias Gunther; Matt F Glasser; Karla L Miller; Kamil Ugurbil; Essa Yacoub
Journal:  PLoS One       Date:  2010-12-20       Impact factor: 3.240

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  203 in total

1.  Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited.

Authors:  Cibu Thomas; Frank Q Ye; M Okan Irfanoglu; Pooja Modi; Kadharbatcha S Saleem; David A Leopold; Carlo Pierpaoli
Journal:  Proc Natl Acad Sci U S A       Date:  2014-11-03       Impact factor: 11.205

Review 2.  A Comprehensive Review of Brain Connectomics and Imaging to Improve Deep Brain Stimulation Outcomes.

Authors:  Joshua K Wong; Erik H Middlebrooks; Sanjeet S Grewal; Leonardo Almeida; Christopher W Hess; Michael S Okun
Journal:  Mov Disord       Date:  2020-04-12       Impact factor: 10.338

3.  Population-averaged atlas of the macroscale human structural connectome and its network topology.

Authors:  Fang-Cheng Yeh; Sandip Panesar; David Fernandes; Antonio Meola; Masanori Yoshino; Juan C Fernandez-Miranda; Jean M Vettel; Timothy Verstynen
Journal:  Neuroimage       Date:  2018-05-24       Impact factor: 6.556

Review 4.  Magnetic Resonance Imaging technology-bridging the gap between noninvasive human imaging and optical microscopy.

Authors:  Jonathan R Polimeni; Lawrence L Wald
Journal:  Curr Opin Neurobiol       Date:  2018-05-11       Impact factor: 6.627

5.  Precise Inference and Characterization of Structural Organization (PICASO) of tissue from molecular diffusion.

Authors:  Lipeng Ning; Evren Özarslan; Carl-Fredrik Westin; Yogesh Rathi
Journal:  Neuroimage       Date:  2016-10-14       Impact factor: 6.556

6.  The impact of gradient strength on in vivo diffusion MRI estimates of axon diameter.

Authors:  Susie Y Huang; Aapo Nummenmaa; Thomas Witzel; Tanguy Duval; Julien Cohen-Adad; Lawrence L Wald; Jennifer A McNab
Journal:  Neuroimage       Date:  2014-12-09       Impact factor: 6.556

7.  In vivo magnetic resonance imaging and spectroscopy. Technological advances and opportunities for applications continue to abound.

Authors:  Peter van Zijl; Linda Knutsson
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8.  g-Ratio weighted imaging of the human spinal cord in vivo.

Authors:  T Duval; S Le Vy; N Stikov; J Campbell; A Mezer; T Witzel; B Keil; V Smith; L L Wald; E Klawiter; J Cohen-Adad
Journal:  Neuroimage       Date:  2016-09-22       Impact factor: 6.556

Review 9.  The Human Connectome Project's neuroimaging approach.

Authors:  Matthew F Glasser; Stephen M Smith; Daniel S Marcus; Jesper L R Andersson; Edward J Auerbach; Timothy E J Behrens; Timothy S Coalson; Michael P Harms; Mark Jenkinson; Steen Moeller; Emma C Robinson; Stamatios N Sotiropoulos; Junqian Xu; Essa Yacoub; Kamil Ugurbil; David C Van Essen
Journal:  Nat Neurosci       Date:  2016-08-26       Impact factor: 24.884

10.  Denoising of diffusion MRI using random matrix theory.

Authors:  Jelle Veraart; Dmitry S Novikov; Daan Christiaens; Benjamin Ades-Aron; Jan Sijbers; Els Fieremans
Journal:  Neuroimage       Date:  2016-08-11       Impact factor: 6.556

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