Distinct laterality alterations distinguish mild cognitive impairment and Alzheimer's disease from healthy aging: Statistical parametric mapping with high resolution MRI
Laterality of human brain varies under healthy aging and diseased conditions. The alterations in hemispheric asymmetry may embed distinct biomarkers linked to the disease dynamics. Statistical parametric mapping based on high‐resolution magnetic resonance imaging (MRI) and image processing technique...
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Published in | Human brain mapping Vol. 34; no. 12; pp. 3400 - 3410 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York, NY
Blackwell Publishing Ltd
01.12.2013
Wiley-Liss John Wiley & Sons, Inc John Wiley and Sons Inc |
Subjects | |
Online Access | Get full text |
ISSN | 1065-9471 1097-0193 1097-0193 |
DOI | 10.1002/hbm.22157 |
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Summary: | Laterality of human brain varies under healthy aging and diseased conditions. The alterations in hemispheric asymmetry may embed distinct biomarkers linked to the disease dynamics. Statistical parametric mapping based on high‐resolution magnetic resonance imaging (MRI) and image processing techniques have allowed automated characterization of morphological features across the entire brain. In this study, 149 subjects grouped in healthy young, healthy elderly, mild cognitive impairment (MCI), and Alzheimer's disease (AD) were investigated using multivariate analysis for regional cerebral laterality indexed by surface area, curvature index, cortical thickness, and subjacent white matter volume measured on high‐resolution MR images. Asymmetry alteration of MCI and AD were characterized by marked region‐specific reduction, while healthy elderly featured a distinct laterality shift in the limbic system in addition to regional asymmetry loss. Lack of the laterality shift in limbic system and early loss of asymmetry in entorhinal cortex may be biomarkers to identify preclinical AD among other dementia. Multivariate analysis of hemispheric asymmetry may provide information helpful for monitoring the disease progress and improving the management of MCI and AD. Hum Brain Mapp 34:3400–3410, 2013. © 2012 Wiley Periodicals, Inc. |
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Bibliography: | ark:/67375/WNG-LWLQ0NC6-C ArticleID:HBM22157 istex:328A7B9EBE645B13590B42568612EDE46D8B2CCC Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.ucla.edu). As such, the investigators within the 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 complete listing of ADNI investigators can be found at http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. National Institutes of Health - No. U01 AG024904 http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf adni.loni.ucla.edu As such, the investigators within the 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 complete listing of ADNI investigators can be found at Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database . ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.ucla.edu). As such, the investigators within the 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 complete listing of ADNI investigators can be found at http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. |
ISSN: | 1065-9471 1097-0193 1097-0193 |
DOI: | 10.1002/hbm.22157 |