Alzheimer’s Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases

Dementia is broadly characterized by cognitive and psychological dysfunction that significantly impairs daily functioning. Dementia has many causes including Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD). Detection and differential diagnosis...

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Autores principales: Angus Lau, Iman Beheshti, Mandana Modirrousta, Tiffany A. Kolesar, Andrew L. Goertzen, Ji Hyun Ko
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Lenguaje:EN
Publicado: MDPI AG 2021
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Acceso en línea:https://doaj.org/article/5711df1740d7470facf7dee62a6332e1
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spelling oai:doaj.org-article:5711df1740d7470facf7dee62a6332e12021-11-25T17:20:51ZAlzheimer’s Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases10.3390/diagnostics111120232075-4418https://doaj.org/article/5711df1740d7470facf7dee62a6332e12021-11-01T00:00:00Zhttps://www.mdpi.com/2075-4418/11/11/2023https://doaj.org/toc/2075-4418Dementia is broadly characterized by cognitive and psychological dysfunction that significantly impairs daily functioning. Dementia has many causes including Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD). Detection and differential diagnosis in the early stages of dementia remains challenging. Fueled by AD Neuroimaging Initiatives (ADNI) (Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. As such, the investigators within ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.), a number of neuroimaging biomarkers for AD have been proposed, yet it remains to be seen whether these markers are also sensitive to other types of dementia. We assessed AD-related metabolic patterns in 27 patients with diverse forms of dementia (five had probable/possible AD while others had atypical cases) and 20 non-demented individuals. All participants had positron emission tomography (PET) scans on file. We used a pre-trained machine learning-based AD designation (MAD) framework to investigate the AD-related metabolic pattern among the participants under study. The MAD algorithm showed a sensitivity of 0.67 and specificity of 0.90 for distinguishing dementia patients from non-dementia participants. A total of 18/27 dementia patients and 2/20 non-dementia patients were identified as having AD-like patterns of metabolism. These results highlight that many underlying causes of dementia have similar hypometabolic pattern as AD and this similarity is an interesting avenue for future research.Angus LauIman BeheshtiMandana ModirroustaTiffany A. KolesarAndrew L. GoertzenJi Hyun KoMDPI AGarticleFDG-PETmachine learningsupport vector machinemetabolic classificationneurodegenerative diseasedementiaMedicine (General)R5-920ENDiagnostics, Vol 11, Iss 2023, p 2023 (2021)
institution DOAJ
collection DOAJ
language EN
topic FDG-PET
machine learning
support vector machine
metabolic classification
neurodegenerative disease
dementia
Medicine (General)
R5-920
spellingShingle FDG-PET
machine learning
support vector machine
metabolic classification
neurodegenerative disease
dementia
Medicine (General)
R5-920
Angus Lau
Iman Beheshti
Mandana Modirrousta
Tiffany A. Kolesar
Andrew L. Goertzen
Ji Hyun Ko
Alzheimer’s Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases
description Dementia is broadly characterized by cognitive and psychological dysfunction that significantly impairs daily functioning. Dementia has many causes including Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD). Detection and differential diagnosis in the early stages of dementia remains challenging. Fueled by AD Neuroimaging Initiatives (ADNI) (Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. As such, the investigators within ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.), a number of neuroimaging biomarkers for AD have been proposed, yet it remains to be seen whether these markers are also sensitive to other types of dementia. We assessed AD-related metabolic patterns in 27 patients with diverse forms of dementia (five had probable/possible AD while others had atypical cases) and 20 non-demented individuals. All participants had positron emission tomography (PET) scans on file. We used a pre-trained machine learning-based AD designation (MAD) framework to investigate the AD-related metabolic pattern among the participants under study. The MAD algorithm showed a sensitivity of 0.67 and specificity of 0.90 for distinguishing dementia patients from non-dementia participants. A total of 18/27 dementia patients and 2/20 non-dementia patients were identified as having AD-like patterns of metabolism. These results highlight that many underlying causes of dementia have similar hypometabolic pattern as AD and this similarity is an interesting avenue for future research.
format article
author Angus Lau
Iman Beheshti
Mandana Modirrousta
Tiffany A. Kolesar
Andrew L. Goertzen
Ji Hyun Ko
author_facet Angus Lau
Iman Beheshti
Mandana Modirrousta
Tiffany A. Kolesar
Andrew L. Goertzen
Ji Hyun Ko
author_sort Angus Lau
title Alzheimer’s Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases
title_short Alzheimer’s Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases
title_full Alzheimer’s Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases
title_fullStr Alzheimer’s Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases
title_full_unstemmed Alzheimer’s Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases
title_sort alzheimer’s disease-related metabolic pattern in diverse forms of neurodegenerative diseases
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/5711df1740d7470facf7dee62a6332e1
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AT mandanamodirrousta alzheimersdiseaserelatedmetabolicpatternindiverseformsofneurodegenerativediseases
AT tiffanyakolesar alzheimersdiseaserelatedmetabolicpatternindiverseformsofneurodegenerativediseases
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