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Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer’s dementia: a meta-analysis
Brain (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) has been utilized to monitor disease conversion from amnestic mild cognitive impairment (aMCI) to Alzheimer’s dementia (AD). However, the conversion patterns of FDG-PET metabolism across studies are not conclusive. We conducted a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5911957/ https://www.ncbi.nlm.nih.gov/pubmed/29713467 http://dx.doi.org/10.1186/s40035-018-0114-z |
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author | Ma, Hai Rong Sheng, Li Qin Pan, Ping Lei Wang, Gen Di Luo, Rong Shi, Hai Cun Dai, Zhen Yu Zhong, Jian Guo |
author_facet | Ma, Hai Rong Sheng, Li Qin Pan, Ping Lei Wang, Gen Di Luo, Rong Shi, Hai Cun Dai, Zhen Yu Zhong, Jian Guo |
author_sort | Ma, Hai Rong |
collection | PubMed |
description | Brain (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) has been utilized to monitor disease conversion from amnestic mild cognitive impairment (aMCI) to Alzheimer’s dementia (AD). However, the conversion patterns of FDG-PET metabolism across studies are not conclusive. We conducted a voxel-wise meta-analysis using Seed-based d Mapping that included 10 baseline voxel-wise FDG-PET comparisons between 93 aMCI converters and 129 aMCI non-converters from nine longitudinal studies. The most robust and reliable metabolic alterations that predicted conversion from aMCI to AD were localized in the left posterior cingulate cortex (PCC)/precuneus. Furthermore, meta-regression analyses indicated that baseline mean age and severity of cognitive impairment, and follow-up duration were significant moderators for metabolic alterations in aMCI converters. Our study revealed hypometabolism in the left PCC/precuneus as an early feature in the development of AD. This finding has important implications in understanding the neural substrates for AD conversion and could serve as a potential imaging biomarker for early detection of AD as well as for tracking disease progression at the predementia stage. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40035-018-0114-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5911957 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59119572018-04-30 Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer’s dementia: a meta-analysis Ma, Hai Rong Sheng, Li Qin Pan, Ping Lei Wang, Gen Di Luo, Rong Shi, Hai Cun Dai, Zhen Yu Zhong, Jian Guo Transl Neurodegener Review Brain (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) has been utilized to monitor disease conversion from amnestic mild cognitive impairment (aMCI) to Alzheimer’s dementia (AD). However, the conversion patterns of FDG-PET metabolism across studies are not conclusive. We conducted a voxel-wise meta-analysis using Seed-based d Mapping that included 10 baseline voxel-wise FDG-PET comparisons between 93 aMCI converters and 129 aMCI non-converters from nine longitudinal studies. The most robust and reliable metabolic alterations that predicted conversion from aMCI to AD were localized in the left posterior cingulate cortex (PCC)/precuneus. Furthermore, meta-regression analyses indicated that baseline mean age and severity of cognitive impairment, and follow-up duration were significant moderators for metabolic alterations in aMCI converters. Our study revealed hypometabolism in the left PCC/precuneus as an early feature in the development of AD. This finding has important implications in understanding the neural substrates for AD conversion and could serve as a potential imaging biomarker for early detection of AD as well as for tracking disease progression at the predementia stage. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40035-018-0114-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-23 /pmc/articles/PMC5911957/ /pubmed/29713467 http://dx.doi.org/10.1186/s40035-018-0114-z Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Review Ma, Hai Rong Sheng, Li Qin Pan, Ping Lei Wang, Gen Di Luo, Rong Shi, Hai Cun Dai, Zhen Yu Zhong, Jian Guo Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer’s dementia: a meta-analysis |
title | Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer’s dementia: a meta-analysis |
title_full | Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer’s dementia: a meta-analysis |
title_fullStr | Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer’s dementia: a meta-analysis |
title_full_unstemmed | Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer’s dementia: a meta-analysis |
title_short | Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer’s dementia: a meta-analysis |
title_sort | cerebral glucose metabolic prediction from amnestic mild cognitive impairment to alzheimer’s dementia: a meta-analysis |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5911957/ https://www.ncbi.nlm.nih.gov/pubmed/29713467 http://dx.doi.org/10.1186/s40035-018-0114-z |
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