Structural Brain Imaging Phenotypes of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) Found by Hierarchical Clustering
Joint Authors
Tohka, Jussi
Neuroimaging Initiative, The Alzheimer’s Disease
Kärkkäinen, Mikko
Prakash, Mithilesh
Zare, Marzieh
Source
International Journal of Alzheimer's Disease
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-16
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
A hierarchical clustering algorithm was applied to magnetic resonance images (MRI) of a cohort of 751 subjects having a mild cognitive impairment (MCI), 282 subjects having received Alzheimer’s disease (AD) diagnosis, and 428 normal controls (NC).
MRIs were preprocessed to gray matter density maps and registered to a stereotactic space.
By first rendering the gray matter density maps comparable by regressing out age, gender, and years of education, and then performing the hierarchical clustering, we found clusters displaying structural features of typical AD, cortically-driven atypical AD, limbic-predominant AD, and early-onset AD (EOAD).
Among these clusters, EOAD subjects displayed marked cortical gray matter atrophy and atrophy of the precuneus.
Furthermore, EOAD subjects had the highest progression rates as measured with ADAS slopes during the longitudinal follow-up of 36 months.
Striking heterogeneities in brain atrophy patterns were observed with MCI subjects.
We found clusters of stable MCI, clusters of diffuse brain atrophy with fast progression, and MCI subjects displaying similar atrophy patterns as the typical or atypical AD subjects.
Bidirectional differences in structural phenotypes were found with MCI subjects involving the anterior cerebellum and the frontal cortex.
The diversity of the MCI subjects suggests that the structural phenotypes of MCI subjects would deserve a more detailed investigation with a significantly larger cohort.
Our results demonstrate that the hierarchical agglomerative clustering method is an efficient tool in dividing a cohort of subjects with gray matter atrophy into coherent clusters manifesting different structural phenotypes.
American Psychological Association (APA)
Kärkkäinen, Mikko& Prakash, Mithilesh& Zare, Marzieh& Tohka, Jussi& Neuroimaging Initiative, The Alzheimer’s Disease. 2020. Structural Brain Imaging Phenotypes of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) Found by Hierarchical Clustering. International Journal of Alzheimer's Disease،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1167843
Modern Language Association (MLA)
Kärkkäinen, Mikko…[et al.]. Structural Brain Imaging Phenotypes of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) Found by Hierarchical Clustering. International Journal of Alzheimer's Disease No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1167843
American Medical Association (AMA)
Kärkkäinen, Mikko& Prakash, Mithilesh& Zare, Marzieh& Tohka, Jussi& Neuroimaging Initiative, The Alzheimer’s Disease. Structural Brain Imaging Phenotypes of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) Found by Hierarchical Clustering. International Journal of Alzheimer's Disease. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1167843
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1167843