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  Maximising BOLD sensitivity through automated EPI protocol optimisation

Volz, S., Callaghan, M. F., Josephs, O., & Weiskopf, N. (2019). Maximising BOLD sensitivity through automated EPI protocol optimisation. NeuroImage: Clinical, 189, 159-170. doi:10.1016/j.neuroimage.2018.12.052.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0002-C0AA-5 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-9095-1
Genre: Journal Article

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 Creators:
Volz, Steffen1, 2, Author              
Callaghan, Martina F.2, Author
Josephs, Oliver2, Author
Weiskopf, Nikolaus1, 2, Author              
Affiliations:
1Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              
2Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, United Kingdom, ou_persistent22              

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 Abstract: Gradient echo echo-planar imaging (GE EPI) is used for most fMRI studies but can suffer substantially from image distortions and BOLD sensitivity (BS) loss due to susceptibility-induced magnetic field inhomogeneities. While there are various post-processing methods for correcting image distortions, signal dropouts cannot be recovered and therefore need to be addressed at the data acquisition stage. Common approaches for reducing susceptibility-related BS loss in selected brain areas are: z-shimming, inverting the phase encoding (PE) gradient polarity, optimizing the slice tilt and increasing spatial resolution. The optimization of these parameters can be based on atlases derived from multiple echo-planar imaging (EPI) acquisitions. However, this requires resource and time, which imposes a practical limitation on the range over which parameters can be optimised meaning that the chosen settings may still be sub-optimal. To address this issue, we have developed an automated method that can be used to optimize across a large parameter space. It is based on numerical signal simulations of the BS loss predicted by physical models informed by a large database of magnetic field (B0) maps acquired on a broad cohort of participants. The advantage of our simulation-based approach compared to previous methods is that it saves time and expensive measurements and allows for optimizing EPI protocols by incorporating a broad range of factors, including different resolutions, echo times or slice orientations. To verify the numerical optimisation, results are compared to those from an earlier study and to experimental BS measurements carried out in six healthy volunteers.

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Language(s): eng - English
 Dates: 2018-12-232018-09-112018-12-242018-12-262019-04-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2018.12.052
PMID: 30593904
Other: Epub ahead of print
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Project name : Taking imaging into the therapeutic domain: Self-regulation of brain systems for mental disorders / BRAINTRAIN
Grant ID : 602186
Funding program : Funding Programme 7
Funding organization : European Commission (EC)
Project name : -
Grant ID : 091593/Z/10/Z
Funding program : -
Funding organization : The Wellcome Centre for Human Neuroimaging

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Title: NeuroImage: Clinical
Source Genre: Journal
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Pages: - Volume / Issue: 189 Sequence Number: - Start / End Page: 159 - 170 Identifier: ISSN: 2213-1582
CoNE: https://pure.mpg.de/cone/journals/resource/2213-1582