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  Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking

Todd, N., Josephs, O., Callaghan, M. F., Lutti, A., & Weiskopf, N. (2015). Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking. NeuroImage, 113, 1-12. doi:10.1016/j.neuroimage.2015.03.013.

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 Creators:
Todd, Nick1, Author
Josephs, Oliver1, Author
Callaghan, Martina F.1, Author
Lutti, Antoine1, 2, Author
Weiskopf, Nikolaus1, Author           
Affiliations:
1Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom, ou_persistent22              
2Département des Neurosciences Cliniques, Laboratoire de Recherche en Neuroimagerie (LREN), Centre hospitalier universitaire vaudois, Lausanne, Switzerland, ou_persistent22              

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Free keywords: 3D imaging; EPI; Functional MRI; Optical tracking; Prospective motion correction
 Abstract: We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement. Task-free fMRI experiments on five healthy volunteers followed a 2×2×3 factorial design with the following factors: PMC on or off; 3.0mm or 1.5mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels (p<0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcome one of the main roadblocks to their widespread use in fMRI studies.

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Language(s): eng - English
 Dates: 2014-09-192015-03-082015-03-142015-06
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2015.03.013
PMID: 25783205
PMC: PMC4441089
Other: Epub 2015
 Degree: -

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Project name : Non-invasive in vivo histology in health and disease using Magnetic Resonance Imaging (MRI) / HMRI
Grant ID : 616905
Funding program : FP7 (ERC-2013-CoG)
Funding organization : European Research Council
Project name : -
Grant ID : 091593/Z10/Z
Funding program : -
Funding organization : Wellcome Trust
Project name : -
Grant ID : -
Funding program : -
Funding organization : SLMS Capital Equipment Fund (UCL)

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 113 Sequence Number: - Start / End Page: 1 - 12 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166