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dc.contributor.authorLawrence, Andrew Jen
dc.contributor.authorTozer, Danielen
dc.contributor.authorStamatakis, Emmanuelen
dc.contributor.authorMarkus, Hughen
dc.date.accessioned2018-04-19T10:04:26Z
dc.date.available2018-04-19T10:04:26Z
dc.date.issued2018-01en
dc.identifier.issn2213-1582
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/275004
dc.description.abstractObjective: MRI measures of network integrity may be useful disease markers in cerebral small vessel disease (SVD). We compared the sensitivity and reproducibility of MRI derived structural and functional network measures in healthy controls and SVD subjects. Methods: Diffusion tractography and resting state fMRI were used to create connectivity matrices from 26 subjects with symptomatic MRI confirmed lacunar stroke and 19 controls. Matrices were constructed at multiple scales based on a multi-resolution cortical atlas and at multiple thresholds for the matrix density. Network parameters were calculated over the multiple resolutions and thresholds. In addition the reproducibility of structural and functional network parameters was determined in a subset of the subjects (15 SVD, 10 controls) who were scanned twice. Results: Structural networks showed a highly significant loss of network integrity in SVD cases compared to controls, for all network measures. In contrast functional networks showed no difference between SVD and controls. Structural network measures were highly reproducible in both cases and controls, with ICC values consistently over 0.8. In contrast functional network measures showed much poorer reproducibility with ICC values in the range 0.4-0.6 overall, and even lower in SVD cases. Conclusions: Structural networks identify impaired network integrity, and are highly reproducible, in SVD, supporting their use as markers of SVD disease severity. In contrast, functional networks showed low reproducibility, particularly in SVD cases, and were unable to detect differences between SVD cases and controls with this sample size.
dc.format.mediumElectronic-eCollectionen
dc.languageengen
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectNeural Pathwaysen
dc.subjectHumansen
dc.subjectMagnetic Resonance Imagingen
dc.subjectReproducibility of Resultsen
dc.subjectNeuropsychological Testsen
dc.subjectImage Processing, Computer-Assisteden
dc.subjectAgeden
dc.subjectMiddle Ageden
dc.subjectFemaleen
dc.subjectMaleen
dc.subjectDiffusion Tensor Imagingen
dc.subjectCerebral Small Vessel Diseasesen
dc.subjectWhite Matteren
dc.subjectCorrelation of Dataen
dc.titleA comparison of functional and tractography based networks in cerebral small vessel disease.en
dc.typeArticle
prism.endingPage432
prism.publicationDate2018en
prism.publicationNameNeuroImage. Clinicalen
prism.startingPage425
prism.volume18en
dc.identifier.doi10.17863/CAM.22161
dcterms.dateAccepted2018-02-07en
rioxxterms.versionofrecord10.1016/j.nicl.2018.02.013en
rioxxterms.versionVoR*
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2018-01en
dc.contributor.orcidLawrence, Andrew J [0000-0002-1420-3381]
dc.contributor.orcidTozer, Daniel [0000-0002-0404-3214]
dc.contributor.orcidStamatakis, Emmanuel Andreas [0000-0001-6955-9601]
dc.contributor.orcidMarkus, Hugh [0000-0002-9794-5996]
dc.identifier.eissn2213-1582
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idAlzheimer's Research UK (ARUK-EXT2015B-1)
pubs.funder-project-idAlzheimer's Research UK (ARUK-PG2013-2)
cam.orpheus.successThu Jan 30 12:59:07 GMT 2020 - The item has an open VoR version.*
rioxxterms.freetoread.startdate2100-01-01


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's licence is described as Attribution-NonCommercial-NoDerivatives 4.0 International