Metabolic Network Topology of Alzheimer's Disease and Dementia with Lewy Bodies Generated Using Fluorodeoxyglucose Positron Emission Tomography.


Journal

Journal of Alzheimer's disease : JAD
ISSN: 1875-8908
Titre abrégé: J Alzheimers Dis
Pays: Netherlands
ID NLM: 9814863

Informations de publication

Date de publication:
2020
Historique:
pubmed: 28 11 2019
medline: 20 4 2021
entrez: 28 11 2019
Statut: ppublish

Résumé

Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) are often misdiagnosed with each other because of similar symptoms including progressive memory loss. The metabolic network topology that describes inter-regional metabolic connections can be generated using fluorodeoxyglucose positron emission tomography (FDG-PET) data with the graph-theoretical method. We hypothesized that different metabolic connectivity underlies the symptoms of AD patients, DLB patients, and cognitively normal (CN) individuals. This study aimed to generate metabolic connectivity using FDG-PET data and assess the network topology to differentiate AD patients, DLB patients, and CN individuals. This study included 45 AD patients, 18 DLB patients, and 142 CN controls. We analyzed FDG-PET data using the graph-theoretical method and generated the network topology in AD patients, DLB patients, and CN individuals. We statistically assessed the topology with global and nodal parameters. The whole metabolic network was preserved in CN; however, diffusely decreased connection was found in AD and partially but more deeply decreased connection was observed in DLB. The metabolic topology revealed that the right posterior cingulate and the left transverse temporal gyrus were significantly different between AD and DLB. The present findings indicate that metabolic connectivity decreased in both AD and DLB, compared with CN. DLB was characterized restricted but deeper stereotyped network disruption compared with AD. The right posterior cingulate and the left transverse temporal gyrus are significant regions in the metabolic connectivity for differentiating AD from DLB.

Sections du résumé

BACKGROUND
Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) are often misdiagnosed with each other because of similar symptoms including progressive memory loss. The metabolic network topology that describes inter-regional metabolic connections can be generated using fluorodeoxyglucose positron emission tomography (FDG-PET) data with the graph-theoretical method. We hypothesized that different metabolic connectivity underlies the symptoms of AD patients, DLB patients, and cognitively normal (CN) individuals.
OBJECTIVE
This study aimed to generate metabolic connectivity using FDG-PET data and assess the network topology to differentiate AD patients, DLB patients, and CN individuals.
METHODS
This study included 45 AD patients, 18 DLB patients, and 142 CN controls. We analyzed FDG-PET data using the graph-theoretical method and generated the network topology in AD patients, DLB patients, and CN individuals. We statistically assessed the topology with global and nodal parameters.
RESULTS
The whole metabolic network was preserved in CN; however, diffusely decreased connection was found in AD and partially but more deeply decreased connection was observed in DLB. The metabolic topology revealed that the right posterior cingulate and the left transverse temporal gyrus were significantly different between AD and DLB.
CONCLUSION
The present findings indicate that metabolic connectivity decreased in both AD and DLB, compared with CN. DLB was characterized restricted but deeper stereotyped network disruption compared with AD. The right posterior cingulate and the left transverse temporal gyrus are significant regions in the metabolic connectivity for differentiating AD from DLB.

Identifiants

pubmed: 31771066
pii: JAD190843
doi: 10.3233/JAD-190843
pmc: PMC7029362
doi:

Substances chimiques

Biomarkers 0
Radiopharmaceuticals 0
Fluorodeoxyglucose F18 0Z5B2CJX4D

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

197-207

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Auteurs

Masamichi Imai (M)

Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
Toranomon Hospital, Tokyo, Japan.

Mika Tanaka (M)

Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.

Muneyuki Sakata (M)

Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.

Kei Wagatsuma (K)

Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.

Tetsuro Tago (T)

Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.

Jun Toyohara (J)

Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.

Renpei Sengoku (R)

Department of Neurology, Tokyo Metropolitan Geriatric Hosptal and Institute of Gerontology, Tokyo, Japan.

Yuji Nishina (Y)

Department of Neurology, Tokyo Metropolitan Geriatric Hosptal and Institute of Gerontology, Tokyo, Japan.

Kazutomi Kanemaru (K)

Department of Neurology, Tokyo Metropolitan Geriatric Hosptal and Institute of Gerontology, Tokyo, Japan.

Kenji Ishibashi (K)

Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.

Shigeo Murayama (S)

Department of Neurology, Tokyo Metropolitan Geriatric Hosptal and Institute of Gerontology, Tokyo, Japan.

Kenji Ishii (K)

Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.

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Classifications MeSH