Multimodal brain-age prediction and cardiovascular risk: The Whitehall II MRI sub-study.

Aged Aging Brain / physiology Cardiovascular Diseases / physiopathology Cognition / physiology Female Gray Matter / physiopathology Heart Disease Risk Factors Humans Magnetic Resonance Imaging / methods Male Middle Aged Neuroimaging / methods Risk Factors White Matter / physiology
Brain age prediction Cardiovascular risk Machine learning Multimodal MRI

Journal

NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515

Informations de publication

Date de publication:
15 11 2020
Historique:
received: 20 07 2020
revised: 14 08 2020
accepted: 17 08 2020
pubmed: 25 8 2020
medline: 30 3 2021
entrez: 25 8 2020
Statut: ppublish

Résumé

Brain age is becoming a widely applied imaging-based biomarker of neural aging and potential proxy for brain integrity and health. We estimated multimodal and modality-specific brain age in the Whitehall II (WHII) MRI cohort using machine learning and imaging-derived measures of gray matter (GM) morphology, white matter microstructure (WM), and resting state functional connectivity (FC). The results showed that the prediction accuracy improved when multiple imaging modalities were included in the model (R

Identifiants

DOI: 10.1016/j.neuroimage.2020.117292 PMID: 32835819 PMC: PMC8121758
pubmed: 32835819
pii: S1053-8119(20)30778-3
doi: 10.1016/j.neuroimage.2020.117292
pmc: PMC8121758
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

117292

Subventions

Organisme : Medical Research Council
ID : MR/K013351/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : G1001354
Pays : United Kingdom
Organisme : Department of Health
ID : HQR00984
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 203139/Z/16/Z
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R024227/1
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : RF1 AG062553
Pays : United States
Organisme : Medical Research Council
ID : MR/L023784/2
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R024790/2
Pays : United Kingdom
Organisme : Medical Research Council
ID : S011676
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R024790/1
Pays : United Kingdom
Organisme : Parkinson's UK
ID : J-0901
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/S011676/1
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Medical Research Council
ID : R024227
Pays : United Kingdom

Informations de copyright

Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.

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Auteurs

Ann-Marie G de Lange (AG)

Department of Psychiatry, University of Oxford, Oxford, UK; Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. Electronic address: a.m.g.d.lange@psykologi.uio.no.

Melis Anatürk (M)

Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.

Sana Suri (S)

Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.

Tobias Kaufmann (T)

NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.

James H Cole (JH)

Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK; Dementia Research Centre, Institute of Neurology, University College London, London, UK.

Ludovica Griffanti (L)

Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.

Enikő Zsoldos (E)

Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.

Daria E A Jensen (DEA)

Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.

Nicola Filippini (N)

Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.

Archana Singh-Manoux (A)

Epidemiology of Ageing and Neurodegenerative Diseases, Universit de Paris, INSERM U1153, Paris France; Department of Epidemiology and Public Health, University College London, London, UK.

Mika Kivimäki (M)

Department of Epidemiology and Public Health, University College London, London, UK.

Lars T Westlye (LT)

Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway.

Klaus P Ebmeier (KP)

Department of Psychiatry, University of Oxford, Oxford, UK.

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Recherchemedicale.com › Personnes › Tranches d'âge › Adulte › Sujet âgé › Multimodal brain-age prediction and...
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