Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease.

SuStain model alzheiemer’s disease inter-cohort validation patient staging patient subtyping

Journal

Frontiers in big data
ISSN: 2624-909X
Titre abrégé: Front Big Data
Pays: Switzerland
ID NLM: 101770603

Informations de publication

Date de publication:
2021
Historique:
received: 30 01 2021
accepted: 04 05 2021
entrez: 7 6 2021
pubmed: 8 6 2021
medline: 8 6 2021
Statut: epublish

Résumé

Alzheimer's disease (AD) is a neurodegenerative disorder which spans several years from preclinical manifestations to dementia. In recent years, interest in the application of machine learning (ML) algorithms to personalized medicine has grown considerably, and a major challenge that such models face is the transferability from the research settings to clinical practice. The objective of this work was to demonstrate the transferability of the Subtype and Stage Inference (SuStaIn) model from well-characterized research data set, employed as training set, to independent less-structured and heterogeneous test sets representative of the clinical setting. The training set was composed of MRI data of 1043 subjects from the Alzheimer's disease Neuroimaging Initiative (ADNI), and the test set was composed of data from 767 subjects from OASIS, Pharma-Cog, and ViTA clinical datasets. Both sets included subjects covering the entire spectrum of AD, and for both sets volumes of relevant brain regions were derived from T1-3D MRI scans processed with Freesurfer v5.3 cross-sectional stream. In order to assess the predictive value of the model, subpopulations of subjects with stable mild cognitive impairment (MCI) and MCIs that progressed to AD dementia (pMCI) were identified in both sets. SuStaIn identified three disease subtypes, of which the most prevalent corresponded to the typical atrophy pattern of AD. The other SuStaIn subtypes exhibited similarities with the previously defined hippocampal sparing and limbic predominant atrophy patterns of AD. Subject subtyping proved to be consistent in time for all cohorts and the staging provided by the model was correlated with cognitive performance. Classification of subjects on the basis of a combination of SuStaIn subtype and stage, mini mental state examination and amyloid-β

Identifiants

pubmed: 34095821
doi: 10.3389/fdata.2021.661110
pii: 661110
pmc: PMC8173213
doi:

Types de publication

Journal Article

Langues

eng

Pagination

661110

Subventions

Organisme : Medical Research Council
ID : MR/T027800/1
Pays : United Kingdom

Informations de copyright

Copyright © 2021 Archetti, Young, Oxtoby, Ferreira, Mårtensson, Westman, Alexander, Frisoni and Redolfi.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Damiano Archetti (D)

Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.

Alexandra L Young (AL)

Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
Department of Computer Science, UCL Centre for Medical Image Computing, London, United Kingdom.

Neil P Oxtoby (NP)

Department of Computer Science, UCL Centre for Medical Image Computing, London, United Kingdom.

Daniel Ferreira (D)

Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
Department of Radiology, Mayo Clinic, Rochester, MN, United States.

Gustav Mårtensson (G)

Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.

Eric Westman (E)

Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.

Daniel C Alexander (DC)

Department of Computer Science, UCL Centre for Medical Image Computing, London, United Kingdom.

Giovanni B Frisoni (GB)

Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland.
Laboratory of Alzheimer's Neuroimaging and Epidemiology - LANE, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.

Alberto Redolfi (A)

Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.

Classifications MeSH