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Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive Impairment, and Alzheimer’s patients
BACKGROUND: Alzheimer’s disease is the most common form of dementia which is still difficult to be differentiated from other types of brain disorders. Moreover, Mild Cognitive Impairment refers to the presence of cognitive impairments that is not severe enough to meet the criteria of Alzheimer’s, an...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3082789/ https://www.ncbi.nlm.nih.gov/pubmed/21526064 |
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author | Oghabian, Mohammad Ali Batouli, Seyed Amir Hossein Norouzian, Maryam Ziaei, Maryam Sikaroodi, Hajir |
author_facet | Oghabian, Mohammad Ali Batouli, Seyed Amir Hossein Norouzian, Maryam Ziaei, Maryam Sikaroodi, Hajir |
author_sort | Oghabian, Mohammad Ali |
collection | PubMed |
description | BACKGROUND: Alzheimer’s disease is the most common form of dementia which is still difficult to be differentiated from other types of brain disorders. Moreover, Mild Cognitive Impairment refers to the presence of cognitive impairments that is not severe enough to meet the criteria of Alzheimer’s, and its diagnosis in early stages is so critical. There is currently no distinct method available for diagnosing Alzheimer’s or Mild Cognitive Impairment, and their diagnosis needs a combination of different methods and assessments. METHODS: The aim of this study was to evaluate the effectiveness of functional Magnetic Resonance Imaging (fMRI) in differentiating between Alzheimer’s, Mild Cognitive Impairment (MCI) and healthy aging. To prove fMRI’s ability, resting-state brain activation patterns between these three groups of subjects were compared using Independent Component Analysis (ICA) algorithm. Forty age- and sex-matched subjects, 15 elderly, 11 MCI and 14 Alzheimer’s subjects were examined. RESULTS: The results showed that during a certain resting-state session, healthy aging brain benefits from larger area and greater intensity of activation (compared with MCI and Alzheimer’s group) in Posterior Cingulate Cortex (PCC) region of the brain, as part of Default Mode Network. CONCLUSIONS: This difference in activation pattern can be used as a diagnostic criterion in using fMRI for differentiating between Alzheimer’s Disease (AD), MCI and healthy aging. |
format | Text |
id | pubmed-3082789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Medknow Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-30827892011-04-27 Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive Impairment, and Alzheimer’s patients Oghabian, Mohammad Ali Batouli, Seyed Amir Hossein Norouzian, Maryam Ziaei, Maryam Sikaroodi, Hajir J Res Med Sci Original Article BACKGROUND: Alzheimer’s disease is the most common form of dementia which is still difficult to be differentiated from other types of brain disorders. Moreover, Mild Cognitive Impairment refers to the presence of cognitive impairments that is not severe enough to meet the criteria of Alzheimer’s, and its diagnosis in early stages is so critical. There is currently no distinct method available for diagnosing Alzheimer’s or Mild Cognitive Impairment, and their diagnosis needs a combination of different methods and assessments. METHODS: The aim of this study was to evaluate the effectiveness of functional Magnetic Resonance Imaging (fMRI) in differentiating between Alzheimer’s, Mild Cognitive Impairment (MCI) and healthy aging. To prove fMRI’s ability, resting-state brain activation patterns between these three groups of subjects were compared using Independent Component Analysis (ICA) algorithm. Forty age- and sex-matched subjects, 15 elderly, 11 MCI and 14 Alzheimer’s subjects were examined. RESULTS: The results showed that during a certain resting-state session, healthy aging brain benefits from larger area and greater intensity of activation (compared with MCI and Alzheimer’s group) in Posterior Cingulate Cortex (PCC) region of the brain, as part of Default Mode Network. CONCLUSIONS: This difference in activation pattern can be used as a diagnostic criterion in using fMRI for differentiating between Alzheimer’s Disease (AD), MCI and healthy aging. Medknow Publications 2010 /pmc/articles/PMC3082789/ /pubmed/21526064 Text en © Journal of Research in Medical Sciences http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Oghabian, Mohammad Ali Batouli, Seyed Amir Hossein Norouzian, Maryam Ziaei, Maryam Sikaroodi, Hajir Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive Impairment, and Alzheimer’s patients |
title | Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive Impairment, and Alzheimer’s patients |
title_full | Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive Impairment, and Alzheimer’s patients |
title_fullStr | Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive Impairment, and Alzheimer’s patients |
title_full_unstemmed | Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive Impairment, and Alzheimer’s patients |
title_short | Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive Impairment, and Alzheimer’s patients |
title_sort | using functional magnetic resonance imaging to differentiate between healthy aging subjects, mild cognitive impairment, and alzheimer’s patients |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3082789/ https://www.ncbi.nlm.nih.gov/pubmed/21526064 |
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