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dc.contributor.authorMcCarthy, Jillian
dc.contributor.authorBorroni, Barbara
dc.contributor.authorSanchez-Valle, Raquel
dc.contributor.authorMoreno, Fermin
dc.contributor.authorLaforce, Robert
dc.contributor.authorGraff, Caroline
dc.contributor.authorSynofzik, Matthis
dc.contributor.authorGalimberti, Daniela
dc.contributor.authorRowe, James
dc.contributor.authorMasellis, Mario
dc.contributor.authorTartaglia, Maria Carmela
dc.contributor.authorFinger, Elizabeth
dc.contributor.authorVandenberghe, Rik
dc.contributor.authorde Mendonça, Alexandre
dc.contributor.authorTagliavini, Fabrizio
dc.contributor.authorSantana, Isabel
dc.contributor.authorButler, Chris
dc.contributor.authorGerhard, Alex
dc.contributor.authorDanek, Adrian
dc.contributor.authorLevin, Johannes
dc.contributor.authorOtto, Markus
dc.contributor.authorFrisoni, Giovanni
dc.contributor.authorGhidoni, Roberta
dc.contributor.authorSorbi, Sandro
dc.contributor.authorJiskoot, Lize C
dc.contributor.authorSeelaar, Harro
dc.contributor.authorvan Swieten, John C
dc.contributor.authorRohrer, Jonathan D
dc.contributor.authorIturria-Medina, Yasser
dc.contributor.authorDucharme, Simon
dc.contributor.authorGENetic Frontotemporal Dementia Initiative (GENFI)
dc.date.accessioned2022-02-04T09:14:26Z
dc.date.available2022-02-04T09:14:26Z
dc.date.issued2022-04-15
dc.date.submitted2021-06-07
dc.identifier.issn1065-9471
dc.identifier.otherhbm25727
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/333639
dc.descriptionFunder: Fondation Brain Canada; Id: http://dx.doi.org/10.13039/100009408
dc.descriptionFunder: Fonds de Recherche du Québec ‐ Santé; Id: http://dx.doi.org/10.13039/501100000156
dc.descriptionFunder: Health Canada; Id: http://dx.doi.org/10.13039/501100000008
dc.descriptionFunder: Brain Canada Foundation; Id: http://dx.doi.org/10.13039/100009408
dc.description.abstractFrontotemporal dementia in genetic forms is highly heterogeneous and begins many years to prior symptom onset, complicating disease understanding and treatment development. Unifying methods to stage the disease during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. Here we used the contrastive trajectory inference (cTI), an unsupervised machine learning algorithm that analyzes temporal patterns in high-dimensional large-scale population datasets to obtain individual scores of disease stage. We used cross-sectional MRI data (gray matter density, T1/T2 ratio as a proxy for myelin content, resting-state functional amplitude, gray matter fractional anisotropy, and mean diffusivity) from 383 gene carriers (269 presymptomatic and 115 symptomatic) and a control group of 253 noncarriers in the Genetic Frontotemporal Dementia Initiative. We compared the cTI-obtained disease scores to the estimated years to onset (age-mean age of onset in relatives), clinical, and neuropsychological test scores. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. Mean cTI scores were higher in the presymptomatic carriers than controls, indicating that the method may capture subtle pre-dementia cerebral changes, although this change was not replicated in a subset of subjects with complete data. This study provides a proof of concept that cTI can identify data-driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics.
dc.languageen
dc.publisherWiley
dc.subjectRESEARCH ARTICLE
dc.subjectRESEARCH ARTICLES
dc.subjectdisease progression
dc.subjectfrontotemporal dementia
dc.subjectmagnetic resonance imaging
dc.subjectunsupervised machine learning
dc.titleData-driven staging of genetic frontotemporal dementia using multi-modal MRI.
dc.typeArticle
dc.date.updated2022-02-04T09:14:25Z
prism.publicationNameHum Brain Mapp
dc.identifier.doi10.17863/CAM.81055
dcterms.dateAccepted2021-11-11
rioxxterms.versionofrecord10.1002/hbm.25727
rioxxterms.versionAO
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.contributor.orcidMcCarthy, Jillian [0000-0002-9285-0023]
dc.contributor.orcidBorroni, Barbara [0000-0001-9340-9814]
dc.contributor.orcidRowe, James [0000-0001-7216-8679]
dc.identifier.eissn1097-0193
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)
pubs.funder-project-idMedical Research Council (MC_UU_00005/12)
cam.issuedOnline2022-02-03


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