Combining structural brain changes improves the prediction of Alzheimer's disease and mild cognitive impairment

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Journal titleDementia and Geriatric Cognitive Disorders
Pages318326; # of pages: 9
Subjectaccuracy; aged; aging; Alzheimer disease; article; brain atrophy; controlled study; correlation analysis; disease predisposition; female; follow up; human; major clinical study; male; medial temporal lobe atrophy; mild cognitive impairment; nuclear magnetic resonance imaging; predictive value; priority journal; prognosis; Aged; Aged, 80 and over; Aging; Alzheimer Disease; Atrophy; Brain; Case-Control Studies; Disease Progression; Female; Humans; Magnetic Resonance Imaging; Male; Middle Aged; Mild Cognitive Impairment; Organ Size; Predictive Value of Tests; Prognosis; Sensitivity and Specificity; Temporal Lobe
AbstractBackground: Several structural brain changes have been associated with Alzheimer's disease (AD). This study investigated the prediction of AD by combining multiple brain changes with the hallmark medial temporal lobe atrophy (MTA). Methods: High-resolution magnetic resonance imaging (MRI) data of people with mild AD (n = 39), mild cognitive impairment (MCI; n = 82), and of healthy controls (HC; n = 58) were obtained at baseline. Among these people, 26 AD, 53 MCI, and 46 HC subjects had 24-month follow-up MRI scans. Bilateral MTA was evaluated using a medial temporal lobe atrophy scale (MTAS). Common changes in the aging brain were summarized using a brain atrophy and lesion index (BALI). The performance of the MTAS, BALI, and a score combining both, using a logistic regression model, were assessed. Results: The MTAS and BALI scores were closely correlated (r2 > 0.56); each differed between the diagnostic groups. Having an unfavorable MTAS score was associated with an increased risk of MCI-AD conversion (OR = 3.71, p = 0.039), adjusted for age, sex, and education; having an unfavorable BALI score marginally contributed to such risks (OR = 4.08, p = 0.080). Combining MTAS and BALI components resulted in a greater OR (8.99, p = 0.007) and an improved predictive accuracy (75.9%, p = 0.002). Conclusion: Multiple structural changes have an additive effect on AD. The data support potential future roles of combining multiple coexisting structural changes to benefit AD diagnosis, progression monitoring, and/or treatment effect evaluation. Copyright © 2012 S. Karger AG, Basel.
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AffiliationNational Research Council Canada (NRC-CNRC); NRC Institute for Biodiagnostics (IBD-IBD)
Peer reviewedYes
NPARC number21269313
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Record identifier8830aaa1-6987-4d05-aba0-3a285fdb45a0
Record created2013-12-12
Record modified2016-05-09
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