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dc.rights.licenseopenen_US
hal.structure.identifierCentre de résonance magnétique des systèmes biologiques [CRMSB]
dc.contributor.authorCORBIN, Nadège
dc.contributor.authorOLIVEIRA, Rita
dc.contributor.authorRAYNAUD, Quentin
dc.contributor.authorDI DOMENICANTONIO, Giulia
dc.contributor.authorDRAGANSKI, Bogdan
dc.contributor.authorKHERIF, Ferath
dc.contributor.authorCALLAGHAN, Martina F
dc.contributor.authorLUTTI, Antoine
dc.date.accessioned2023-11-16T10:07:06Z
dc.date.available2023-11-16T10:07:06Z
dc.date.issued2023-10-01
dc.identifier.issn1872-678Xen_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/184805
dc.description.abstractEnConsistent noise variance across data points (i.e. homoscedasticity) is required to ensure the validity of statistical analyses of MRI data conducted using linear regression methods. However, head motion leads to degradation of image quality, introducing noise heteroscedasticity into ordinary-least square analyses. The recently introduced QUIQI method restores noise homoscedasticity by means of weighted least square analyses in which the weights, specific for each dataset of an analysis, are computed from an index of motion-induced image quality degradation. QUIQI was first demonstrated in the context of brain maps of the MRI parameter R2 * , which were computed from a single set of images with variable echo time. Here, we extend this framework to quantitative maps of the MRI parameters R1, R2 * , and MTsat, computed from multiple sets of images. QUIQI restores homoscedasticity in analyses of quantitative MRI data computed from multiple scans. QUIQI allows for optimization of the noise model by using metrics quantifying heteroscedasticity and free energy. QUIQI restores homoscedasticity more effectively than insertion of an image quality index in the analysis design and yields higher sensitivity than simply removing the datasets most corrupted by head motion from the analysis. QUIQI provides an optimal approach to group-wise analyses of a range of quantitative MRI parameter maps that is robust to inherent homoscedasticity.
dc.language.isoENen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subject.enAlgorithms
dc.subject.enReproducibility of Results
dc.subject.enMagnetic Resonance Imaging
dc.subject.enBrain
dc.subject.enMotion
dc.title.enStatistical analyses of motion-corrupted MRI relaxometry data computed from multiple scans
dc.title.alternativeJ Neurosci Methodsen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1016/j.jneumeth.2023.109950en_US
dc.subject.halSciences du Vivant [q-bio]en_US
dc.subject.halSciences de l'ingénieur [physics]en_US
dc.identifier.pubmed37598941en_US
bordeaux.journalJournal of Neuroscience Methodsen_US
bordeaux.page109950en_US
bordeaux.volume398en_US
bordeaux.hal.laboratoriesCentre de Résonance Magnétique des Systèmes Biologiques (CRMSB) - UMR 5536en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.identifier.funderIDPartridge Foundationen_US
bordeaux.identifier.funderIDFondation Roger de Spoelberchen_US
bordeaux.identifier.funderIDWellcomeen_US
bordeaux.identifier.funderIDFondation Leenaardsen_US
bordeaux.import.sourcepubmed
hal.identifierhal-04288800
hal.version1
hal.date.transferred2023-11-16T10:07:11Z
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
workflow.import.sourcepubmed
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal%20of%20Neuroscience%20Methods&rft.date=2023-10-01&rft.volume=398&rft.spage=109950&rft.epage=109950&rft.eissn=1872-678X&rft.issn=1872-678X&rft.au=CORBIN,%20Nad%C3%A8ge&OLIVEIRA,%20Rita&RAYNAUD,%20Quentin&DI%20DOMENICANTONIO,%20Giulia&DRAGANSKI,%20Bogdan&rft.genre=article


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