Cortical thickness modeling and variability in Alzheimer's disease and frontotemporal dementia

dc.contributor.authorPérez Millan, Agnès
dc.contributor.authorBorrego Écija, Sergi
dc.contributor.authorFalgàs Martínez, Neus
dc.contributor.authorJuncà Parella, Jordi
dc.contributor.authorBosch Capdevila, Beatriz
dc.contributor.authorTort Merino, Adrià
dc.contributor.authorAntonell Boixader, Anna, 1978-
dc.contributor.authorBargalló Alabart, Núria​
dc.contributor.authorRami González, Lorena
dc.contributor.authorBalasa, Mircea
dc.contributor.authorLladó Plarrumaní, Albert
dc.contributor.authorSala Llonch, Roser
dc.contributor.authorSánchez Valle, Raquel
dc.date.accessioned2024-02-13T11:53:07Z
dc.date.available2024-02-13T11:53:07Z
dc.date.issued2023-11-27
dc.date.updated2024-02-08T16:14:14Z
dc.description.abstractAlzheimer's disease (AD) and frontotemporal dementia (FTD) show different patterns of cortical thickness (CTh) loss compared with healthy controls (HC), even though there is relevant heterogeneity between individuals suffering from each of these diseases. Thus, we developed CTh models to study individual variability in AD, FTD, and HC.We used the baseline CTh measures of 379 participants obtained from the structural MRI processed with FreeSurfer. A total of 169 AD patients (63 ± 9 years, 65 men), 88 FTD patients (64 ± 9 years, 43 men), and 122 HC (62 ± 10 years, 47 men) were studied. We fitted region-wise temporal models of CTh using Support Vector Regression. Then, we studied associations of individual deviations from the model with cerebrospinal fluid levels of neurofilament light chain (NfL) and 14-3-3 protein and Mini-Mental State Examination (MMSE). Furthermore, we used real longitudinal data from 144 participants to test model predictivity.We defined CTh spatiotemporal models for each group with a reliable fit. Individual deviation correlated with MMSE for AD and with NfL for FTD. AD patients with higher deviations from the trend presented higher MMSE values. In FTD, lower NfL levels were associated with higher deviations from the CTh prediction. For AD and HC, we could predict longitudinal visits with the presented model trained with baseline data. For FTD, the longitudinal visits had more variability.We highlight the value of CTh models for studying AD and FTD longitudinal changes and variability and their relationships with cognitive features and biomarkers.© 2023. The Author(s).
dc.format.extent11 p.
dc.format.mimetypeapplication/pdf
dc.identifier.idgrec745410
dc.identifier.idimarina9379384
dc.identifier.idsira850772
dc.identifier.issn1432-1459
dc.identifier.pmid38012398
dc.identifier.urihttps://hdl.handle.net/2445/207530
dc.language.isoeng
dc.publisherSpringer Science and Business Media
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1007/s00415-023-12087-1
dc.relation.ispartofJournal of Neurology, 2023, vol. 271, p. 1428–1438
dc.relation.urihttps://doi.org/10.1007/s00415-023-12087-1
dc.rightscc-by (c) Pérez Millan et al., 2023
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.sourceArticles publicats en revistes (Biomedicina)
dc.subject.classificationDemència
dc.subject.classificationImatges per ressonància magnètica
dc.subject.otherDementia
dc.subject.otherMagnetic resonance imaging
dc.titleCortical thickness modeling and variability in Alzheimer's disease and frontotemporal dementia
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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