Publication :
Patch-wise brain age longitudinal reliability (2020)

Notice brève
ali.license-refhttps://creativecommons.org/licenses/by/4.0fr
ali.license-ref.start-date2020-12-16fr
bul.description.provenanceembre chlacfr
bul.rights.dateAccepPubl2020-11-18fr
bul.rights.periodeEmbargoP0Mfr
bul.rights.typeDatedatePublicationfr
dc.audience.peerreview1fr
dc.contributor.authorPotvin, Olivier
dc.contributor.authorBeheshti, Iman
dc.contributor.authorDuchesne, Simon
dc.date.accessioned2020-12-18T02:36:07Z
dc.date.available2020-12-18T02:36:07Z
dc.date.issued2020-11-18
dc.description.abstractWe recently introduced a patch‐wise technique to estimate brain age from anatomical T1‐weighted magnetic resonance imaging (T1w MRI) data. Here, we sought to assess its longitudinal reliability by leveraging a unique dataset of 99 longitudinal MRI scans from a single, cognitively healthy volunteer acquired over a period of 17 years (aged 29–46 years) at multiple sites. We built a robust patch‐wise brain age estimation framework on the basis of 100 cognitively healthy individuals from the MindBoggle dataset (aged 19–61 years) using the Desikan‐Killiany‐Tourville atlas, then applied the model to the volunteer dataset. The results show a high prediction accuracy on the independent test set (R2 = .94, mean absolute error of 0.63 years) and no statistically significant difference between manufacturers, suggesting that the patch‐wise technique has high reliability and can be used for longitudinal multi‐centric studies.fr
dc.identifier.doi10.1002/hbm.25253 Obtenir@ULavalfr
dc.identifier.issn1065-9471fr
dc.identifier.pubmed33205863fr
dc.identifier.urihttp://hdl.handle.net/20.500.11794/67547
dc.languageengfr
dc.publisherJohn Wiley & Sonsfr
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subjectAnatomical MRIfr
dc.subjectBrain agefr
dc.subjectEstimationfr
dc.subjectLongitudinal studyfr
dc.subjectPatch-wise gradingfr
dc.subjectReliabilityfr
dc.subject.rvmCerveau -- Vieillissement -- Mesurefr
dc.subject.rvmImagerie par résonance magnétiquefr
dc.subject.rvmÉtudes longitudinalesfr
dc.titlePatch-wise brain age longitudinal reliability (2020)fr
dc.typearticle de recherche
dc.type.legacyCOAR1_1::Texte::Périodique::Revue::Contribution à un journal::Article::Article de recherchefr
dcterms.bibliographicCitationHuman brain mappingfr
dspace.accessstatus.time2023-05-24 18:00:36
dspace.entity.typePublication
relation.isAuthorOfPublication0811cd63-d509-4ac1-b0a7-962c11daa39d
relation.isAuthorOfPublication284aea65-4d16-4e45-9e17-eccb7c714a87
relation.isAuthorOfPublication84604d26-3403-4629-89b1-f701347fb39f
relation.isAuthorOfPublication.latestForDiscovery0811cd63-d509-4ac1-b0a7-962c11daa39d
relation.isResourceTypeOfPublication4c433ef5-3937-4530-8252-cca17d715747
relation.isResourceTypeOfPublication.latestForDiscovery4c433ef5-3937-4530-8252-cca17d715747
rioxxterms.project.funder-nameAlzheimer’s Society of Canadafr
rioxxterms.project.funder-nameCanadian Institutes of Health Researchfr
rioxxterms.project.funder-nameFonds de Recherche du Québec - Santéfr
rioxxterms.project.funder-nameFonds de recherche du Québec – Santé / Pfizer Canadafr
rioxxterms.versionVersion of Record (VoR)fr
rioxxterms.version-of-recordhttps://doi.org/10.1002/hbm.25253fr
Fichiers
Bundle original
Voici les éléments 1 - 1 sur 1
Vignette d'image
Nom :
Beheshti20.pdf
Taille :
3.93 MB
Format :
Adobe Portable Document Format
Description :
Télécharger
Collections
Articles publiés dans des revues avec comité de lecture