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Metabolic Network Topology of Alzheimer's Disease and Dementia with Lewy Bodies Generated Using Fluorodeoxyglucose Positron Emission Tomography.
Imai, Masamichi; Tanaka, Mika; Sakata, Muneyuki; Wagatsuma, Kei; Tago, Tetsuro; Toyohara, Jun; Sengoku, Renpei; Nishina, Yuji; Kanemaru, Kazutomi; Ishibashi, Kenji; Murayama, Shigeo; Ishii, Kenji.
Afiliación
  • Imai M; Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
  • Tanaka M; Toranomon Hospital, Tokyo, Japan.
  • Sakata M; Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
  • Wagatsuma K; Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
  • Tago T; Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
  • Toyohara J; Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
  • Sengoku R; Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
  • Nishina Y; Department of Neurology, Tokyo Metropolitan Geriatric Hosptal and Institute of Gerontology, Tokyo, Japan.
  • Kanemaru K; Department of Neurology, Tokyo Metropolitan Geriatric Hosptal and Institute of Gerontology, Tokyo, Japan.
  • Ishibashi K; Department of Neurology, Tokyo Metropolitan Geriatric Hosptal and Institute of Gerontology, Tokyo, Japan.
  • Murayama S; Team for Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
  • Ishii K; Department of Neurology, Tokyo Metropolitan Geriatric Hosptal and Institute of Gerontology, Tokyo, Japan.
J Alzheimers Dis ; 73(1): 197-207, 2020.
Article en En | MEDLINE | ID: mdl-31771066
ABSTRACT

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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad por Cuerpos de Lewy / Redes y Vías Metabólicas / Enfermedad de Alzheimer Límite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: J Alzheimers Dis Asunto de la revista: GERIATRIA / NEUROLOGIA Año: 2020 Tipo del documento: Article País de afiliación: Japón

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad por Cuerpos de Lewy / Redes y Vías Metabólicas / Enfermedad de Alzheimer Límite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: J Alzheimers Dis Asunto de la revista: GERIATRIA / NEUROLOGIA Año: 2020 Tipo del documento: Article País de afiliación: Japón
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