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dc.contributor.authorPremi, Enrico
dc.contributor.authorCosta, Tommaso
dc.contributor.authorGazzina, Stefano
dc.contributor.authorBenussi, Alberto
dc.contributor.authorCauda, Franco
dc.contributor.authorGasparotti, Roberto
dc.contributor.authorArchetti, Silvana
dc.contributor.authorAlberici, Antonella
dc.contributor.authorvan Swieten, John C
dc.contributor.authorSanchez-Valle, Raquel
dc.contributor.authorMoreno, Fermin
dc.contributor.authorSantana, Isabel
dc.contributor.authorLaforce, Robert
dc.contributor.authorDucharme, Simon
dc.contributor.authorGraff, Caroline
dc.contributor.authorGalimberti, Daniela
dc.contributor.authorMasellis, Mario
dc.contributor.authorTartaglia, Carmela
dc.contributor.authorRowe, James B
dc.contributor.authorFinger, Elizabeth
dc.contributor.authorTagliavini, Fabrizio
dc.contributor.authorde Mendonça, Alexandre
dc.contributor.authorVandenberghe, Rik
dc.contributor.authorGerhard, Alexander
dc.contributor.authorButler, Chris R
dc.contributor.authorDanek, Adrian
dc.contributor.authorSynofzik, Matthis
dc.contributor.authorLevin, Johannes
dc.contributor.authorOtto, Markus
dc.contributor.authorGhidoni, Roberta
dc.contributor.authorFrisoni, Giovanni
dc.contributor.authorSorbi, Sandro
dc.contributor.authorPeakman, Georgia
dc.contributor.authorTodd, Emily
dc.contributor.authorBocchetta, Martina
dc.contributor.authorRohrer, Johnathan D
dc.contributor.authorBorroni, Barbara
dc.contributor.authorGENFI Consortium Members
dc.date.accessioned2022-07-26T08:20:32Z
dc.date.available2022-07-26T08:20:32Z
dc.date.issued2022
dc.identifier.issn1387-2877
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/339501
dc.description.abstractBACKGROUND: Magnetic resonance imaging (MRI) measures may be used as outcome markers in frontotemporal dementia (FTD). OBJECTIVES: To predict MRI cortical thickness (CT) at follow-up at the single subject level, using brain MRI acquired at baseline in preclinical FTD. METHODS: 84 presymptomatic subjects carrying Granulin mutations underwent MRI scans at baseline and at follow-up (31.2±16.5 months). Multivariate nonlinear mixed-effects model was used for estimating individualized CT at follow-up based on baseline MRI data. The automated user-friendly preGRN-MRI script was coded. RESULTS: Prediction accuracy was high for each considered brain region (i.e., prefrontal region, real CT at follow-up versus predicted CT at follow-up, mean error ≤1.87%). The sample size required to detect a reduction in decline in a 1-year clinical trial was equal to 52 subjects (power = 0.80, alpha = 0.05). CONCLUSION: The preGRN-MRI tool, using baseline MRI measures, was able to predict the expected MRI atrophy at follow-up in presymptomatic subjects carrying GRN mutations with good performances. This tool could be useful in clinical trials, where deviation of CT from the predicted model may be considered an effect of the intervention itself.
dc.format.mediumPrint
dc.publisherIOS Press
dc.rightsAll Rights Reserved
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserved
dc.subjectFrontotemporal dementia
dc.subjectgranulin
dc.subjectmagnetic resonance imaging
dc.subjectmutation
dc.subjectpreclinical
dc.subjectpresymptomatic
dc.titleAn Automated Toolbox to Predict Single Subject Atrophy in Presymptomatic Granulin Mutation Carriers.
dc.typeArticle
dc.publisher.departmentDepartment of Clinical Neurosciences
dc.date.updated2022-04-01T10:55:17Z
prism.endingPage218
prism.issueIdentifier1
prism.publicationDate2022
prism.publicationNameJ Alzheimers Dis
prism.startingPage205
prism.volume86
dc.identifier.doi10.17863/CAM.86915
rioxxterms.versionofrecord10.3233/JAD-215447
rioxxterms.versionAM
dc.contributor.orcidRowe, James [0000-0001-7216-8679]
dc.identifier.eissn1875-8908
rioxxterms.typeJournal Article/Review
pubs.funder-project-idMedical Research Council (MC_UU_00005/12)
pubs.funder-project-idCambridge University Hospitals NHS Foundation Trust (CUH) (146281)
pubs.funder-project-idMedical Research Council (MR/J009482/1)
pubs.funder-project-idMedical Research Council (MR/M008983/1)
pubs.funder-project-idMedical Research Council (MC_U105597119)
cam.orpheus.success2022-07-26 - Embargo set during processing via Fast-track
cam.depositDate2022-04-01
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement


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