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Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients
Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer’s disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of A...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5363868/ https://www.ncbi.nlm.nih.gov/pubmed/28333946 http://dx.doi.org/10.1371/journal.pone.0173426 |
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author | Son, Seong-Jin Kim, Jonghoon Park, Hyunjin |
author_facet | Son, Seong-Jin Kim, Jonghoon Park, Hyunjin |
author_sort | Son, Seong-Jin |
collection | PubMed |
description | Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer’s disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint. |
format | Online Article Text |
id | pubmed-5363868 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-53638682017-04-06 Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients Son, Seong-Jin Kim, Jonghoon Park, Hyunjin PLoS One Research Article Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer’s disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint. Public Library of Science 2017-03-23 /pmc/articles/PMC5363868/ /pubmed/28333946 http://dx.doi.org/10.1371/journal.pone.0173426 Text en © 2017 Son et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Son, Seong-Jin Kim, Jonghoon Park, Hyunjin Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients |
title | Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients |
title_full | Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients |
title_fullStr | Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients |
title_full_unstemmed | Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients |
title_short | Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients |
title_sort | structural and functional connectional fingerprints in mild cognitive impairment and alzheimer’s disease patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5363868/ https://www.ncbi.nlm.nih.gov/pubmed/28333946 http://dx.doi.org/10.1371/journal.pone.0173426 |
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