Automated MRI Measures Identify Individuals with Mild Cognitive Impairment and Alzheimer's Disease*

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dc.contributor.author Desikan, Rahul S. en_US
dc.contributor.author Cabral, Howard J. en_US
dc.contributor.author Hess, Christopher P. en_US
dc.contributor.author Dillon, William P. en_US
dc.contributor.author Glastonbury, Christine M. en_US
dc.contributor.author Weiner, Michael W. en_US
dc.contributor.author Schmansky, Nicholas J. en_US
dc.contributor.author Greve, Douglas N. en_US
dc.contributor.author Salat, David H. en_US
dc.contributor.author Buckner, Randy L. en_US
dc.contributor.author Fischl, Bruce en_US
dc.date.accessioned 2012-01-11T15:51:14Z
dc.date.available 2012-01-11T15:51:14Z
dc.date.copyright 2009 en_US
dc.date.issued 2009-5-21 en_US
dc.identifier.citation Desikan, Rahul S., Howard J. Cabral, Christopher P. Hess, William P. Dillon, Christine M. Glastonbury, Michael W. Weiner, Nicholas J. Schmansky, Douglas N. Greve, David H. Salat, Randy L. Buckner, Bruce Fischl. "Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease*" Brain 132(8): 2048-2057. (2009) en_US
dc.identifier.issn 1460-2156 en_US
dc.identifier.uri http://hdl.handle.net/2144/3085
dc.description.abstract Mild cognitive impairment can represent a transitional state between normal ageing and Alzheimer's disease. Non-invasive diagnostic methods are needed to identify mild cognitive impairment individuals for early therapeutic interventions. Our objective was to determine whether automated magnetic resonance imaging-based measures could identify mild cognitive impairment individuals with a high degree of accuracy. Baseline volumetric T1-weighted magnetic resonance imaging scans of 313 individuals from two independent cohorts were examined using automated software tools to identify the volume and mean thickness of 34 neuroanatomic regions. The first cohort included 49 older controls and 48 individuals with mild cognitive impairment, while the second cohort included 94 older controls and 57 mild cognitive impairment individuals. Sixty-five patients with probable Alzheimer's disease were also included for comparison. For the discrimination of mild cognitive impairment, entorhinal cortex thickness, hippocampal volume and supramarginal gyrus thickness demonstrated an area under the curve of 0.91 (specificity 94%, sensitivity 74%, positive likelihood ratio 12.12, negative likelihood ratio 0.29) for the first cohort and an area under the curve of 0.95 (specificity 91%, sensitivity 90%, positive likelihood ratio 10.0, negative likelihood ratio 0.11) for the second cohort. For the discrimination of Alzheimer's disease, these three measures demonstrated an area under the curve of 1.0. The three magnetic resonance imaging measures demonstrated significant correlations with clinical and neuropsychological assessments as well as with cerebrospinal fluid levels of tau, hyperphosphorylated tau and abeta 42 proteins. These results demonstrate that automated magnetic resonance imaging measures can serve as an in vivo surrogate for disease severity, underlying neuropathology and as a non-invasive diagnostic method for mild cognitive impairment and Alzheimer's disease. en_US
dc.description.sponsorship American Federation for Aging Research (Medical Student Training in Aging Research Program); National Center for Research Resources (P41-RR14075, R01 RR 16594-01A1, NCRR BIRN Morphometric Project BIRN002, U24 RR021382); National Institute for Biomedical Imaging and Bioengineering (RO1 EB001550); Mental Illness and Neuroscience Discovery Institute; National Institute on Aging (P50 AG05681, P01 AG03991, AG021910); Alzheimer's Disease Neuroimaging Initiative (NIH U01 AG024904); Howard Hughes Medical Institute (OASIS project); Pfizer, Inc.; Wyeth Research; Bristol-Meyers Squibb; Eli Lilly and Company; GlaxoSmithKline; Merck & Co. Inc.; AstraZenica AB; Novartis Pharmaceuticals Corporation; Alzheimer's Association; Eisai Global Clinical Development; Elan Corporation plc; Forest Laboratories; Institute for the Study of Aging en_US
dc.language.iso en en_US
dc.publisher Oxford University Press en_US
dc.rights Copyright 2009 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. en_US
dc.rights.uri http://creativecommons.org/licenses/by-nc/2.0/uk/ en_US
dc.subject MRI en_US
dc.subject Mild cognitive impairment en_US
dc.subject Alzheimer's disease en_US
dc.subject Diagnostic marker en_US
dc.title Automated MRI Measures Identify Individuals with Mild Cognitive Impairment and Alzheimer's Disease* en_US
dc.type article en_US
dc.identifier.doi 10.1093/brain/awp123 en_US
dc.identifier.pubmedid 19460794 en_US
dc.identifier.pmcid 2714061 en_US

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