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Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI

BACKGROUND: Alzheimer’s disease (AD) is a progressive, incurable neurodegenerative disease and the most common type of dementia. It cannot be prevented, cured or drastically slowed, even though AD research has increased in the past 5-10 years. Instead of focusing on the brain volume or on the single...

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Autores principales: Lillemark, Lene, Sørensen, Lauge, Pai, Akshay, Dam, Erik B, Nielsen, Mads
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4048460/
https://www.ncbi.nlm.nih.gov/pubmed/24889999
http://dx.doi.org/10.1186/1471-2342-14-21
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author Lillemark, Lene
Sørensen, Lauge
Pai, Akshay
Dam, Erik B
Nielsen, Mads
author_facet Lillemark, Lene
Sørensen, Lauge
Pai, Akshay
Dam, Erik B
Nielsen, Mads
author_sort Lillemark, Lene
collection PubMed
description BACKGROUND: Alzheimer’s disease (AD) is a progressive, incurable neurodegenerative disease and the most common type of dementia. It cannot be prevented, cured or drastically slowed, even though AD research has increased in the past 5-10 years. Instead of focusing on the brain volume or on the single brain structures like hippocampus, this paper investigates the relationship and proximity between regions in the brain and uses this information as a novel way of classifying normal control (NC), mild cognitive impaired (MCI), and AD subjects. METHODS: A longitudinal cohort of 528 subjects (170 NC, 240 MCI, and 114 AD) from ADNI at baseline and month 12 was studied. We investigated a marker based on Procrustes aligned center of masses and the percentile surface connectivity between regions. These markers were classified using a linear discriminant analysis in a cross validation setting and compared to whole brain and hippocampus volume. RESULTS: We found that both our markers was able to significantly classify the subjects. The surface connectivity marker showed the best results with an area under the curve (AUC) at 0.877 (p<0.001), 0.784 (p<0.001), 0,766 (p<0.001) for NC-AD, NC-MCI, and MCI-AD, respectively, for the functional regions in the brain. The surface connectivity marker was able to classify MCI-converters with an AUC of 0.599 (p<0.05) for the 1-year period. CONCLUSION: Our results show that our relative proximity markers include more information than whole brain and hippocampus volume. Our results demonstrate that our proximity markers have the potential to assist in early diagnosis of AD.
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spelling pubmed-40484602014-06-23 Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI Lillemark, Lene Sørensen, Lauge Pai, Akshay Dam, Erik B Nielsen, Mads BMC Med Imaging Research Article BACKGROUND: Alzheimer’s disease (AD) is a progressive, incurable neurodegenerative disease and the most common type of dementia. It cannot be prevented, cured or drastically slowed, even though AD research has increased in the past 5-10 years. Instead of focusing on the brain volume or on the single brain structures like hippocampus, this paper investigates the relationship and proximity between regions in the brain and uses this information as a novel way of classifying normal control (NC), mild cognitive impaired (MCI), and AD subjects. METHODS: A longitudinal cohort of 528 subjects (170 NC, 240 MCI, and 114 AD) from ADNI at baseline and month 12 was studied. We investigated a marker based on Procrustes aligned center of masses and the percentile surface connectivity between regions. These markers were classified using a linear discriminant analysis in a cross validation setting and compared to whole brain and hippocampus volume. RESULTS: We found that both our markers was able to significantly classify the subjects. The surface connectivity marker showed the best results with an area under the curve (AUC) at 0.877 (p<0.001), 0.784 (p<0.001), 0,766 (p<0.001) for NC-AD, NC-MCI, and MCI-AD, respectively, for the functional regions in the brain. The surface connectivity marker was able to classify MCI-converters with an AUC of 0.599 (p<0.05) for the 1-year period. CONCLUSION: Our results show that our relative proximity markers include more information than whole brain and hippocampus volume. Our results demonstrate that our proximity markers have the potential to assist in early diagnosis of AD. BioMed Central 2014-06-02 /pmc/articles/PMC4048460/ /pubmed/24889999 http://dx.doi.org/10.1186/1471-2342-14-21 Text en Copyright © 2014 Lillemark et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Research Article
Lillemark, Lene
Sørensen, Lauge
Pai, Akshay
Dam, Erik B
Nielsen, Mads
Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI
title Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI
title_full Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI
title_fullStr Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI
title_full_unstemmed Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI
title_short Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI
title_sort brain region’s relative proximity as marker for alzheimer’s disease based on structural mri
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4048460/
https://www.ncbi.nlm.nih.gov/pubmed/24889999
http://dx.doi.org/10.1186/1471-2342-14-21
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