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dc.contributor.authorThapaliya, Kiran
dc.contributor.authorVegh, Viktor
dc.contributor.authorBollmann, Steffen
dc.contributor.authorBarth, Markus
dc.date.accessioned2020-06-01T05:07:28Z
dc.date.available2020-06-01T05:07:28Z
dc.date.issued2020
dc.identifier.issn1662-4548
dc.identifier.doi10.3389/fnins.2020.00271
dc.identifier.urihttp://hdl.handle.net/10072/394264
dc.description.abstractQuantitative assessment of tissue microstructure is important in studying human brain diseases and disorders. Ultra-high field magnetic resonance imaging (MRI) data obtained using a multi-echo gradient echo sequence have been shown to contain information on myelin, axonal, and extracellular compartments in tissue. Quantitative assessment of water fraction, relaxation time (T2*), and frequency shift using multi-compartment models has been shown to be useful in studying white matter properties via specific tissue parameters. It remains unclear how tissue parameters vary with model selection based on 7T multiple echo time gradient-recalled echo (GRE) MRI data. We applied existing signal compartment models to the corpus callosum and investigated whether a three-compartment model can be reduced to two compartments and still resolve white matter parameters [i.e., myelin water fraction (MWF) and g-ratio]. We show that MWF should be computed using a three-compartment model in the corpus callosum, and the g-ratios obtained using three compartment models are consistent with previous reports. We provide results for other parameters, such as signal compartment frequency shifts.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherFrontiers Media SA
dc.relation.ispartofpagefrom271:1
dc.relation.ispartofpageto271:13
dc.relation.ispartofjournalFrontiers in Neuroscience
dc.relation.ispartofvolume14
dc.subject.fieldofresearchNeurosciences
dc.subject.fieldofresearchPsychology
dc.subject.fieldofresearchCognitive Sciences
dc.subject.fieldofresearchcode1109
dc.subject.fieldofresearchcode1701
dc.subject.fieldofresearchcode1702
dc.subject.keywordscorpus callosum
dc.subject.keywordsfrequency shift
dc.subject.keywordsmyelin imaging
dc.subject.keywordsphase unwrapping
dc.subject.keywordssignal compartmentalization
dc.titleInfluence of 7T GRE-MRI Signal Compartment Model Choice on Tissue Parameters
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationThapaliya, K; Vegh, V; Bollmann, S; Barth, M, Influence of 7T GRE-MRI Signal Compartment Model Choice on Tissue Parameters, Frontiers in Neuroscience, 2020, 14, pp. 271:1-271:13
dcterms.dateAccepted2020-03-10
dcterms.licensehttps://creativecommons.org/licenses/by/4.0/
dc.date.updated2020-06-01T04:50:50Z
dc.description.versionPublished
gro.rights.copyright© 2020 Thapaliya, Vegh, Bollmann and Barth. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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gro.griffith.authorThapaliya, Kiran


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