Journal
NEUROBIOLOGY OF AGING
Volume 31, Issue 8, Pages 1364-1374Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.neurobiolaging.2010.04.023
Keywords
Computational MRI; AD; Mild cognitive impairment; Clinical biomarker
Categories
Funding
- National Center for Research Resources [P41-RR14075, R01 RR 16594-01A1, BIRN002, U24 RR021382]
- National Institute for Biomedical Imaging and Bioengineering [R01 EB001550]
- Mental Illness and Neuroscience Discovery (MIND) Institute
- National Institute on Aging [P50 AG05681, P01 AG03991, AG021910]
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The prediction of individuals with mild cognitive impairment (MCI) destined to develop Alzheimer's disease (AD) is of increasing clinical importance. In this study, using baseline T1-weighted MRI scans of 324 MCI individuals from two cohorts and automated software tools, we employed factor analyses and Cox proportional hazards models to identify a set of neuroanatomic measures that best predicted the time to progress from MCI to AD. For comparison, cerebrospinal fluid (CSF) assessments of cellular pathology and positron emission tomography (PET) measures of metabolic activity were additionally examined. By 3 years follow-up, 60 MCI individuals from the first cohort and 58 MCI individuals from the second cohort had progressed to a diagnosis of AD. Cox models on the first cohort demonstrated significant effects for the medial temporal factor [Hazards Ratio (HR) = 0.43(95% confidence interval (CI), 0.32-0.55), p<0.0001], the fronto-parietoccipital factor [HR = 0.59[95% CI, 0.48-0.80), p<0.001], and the lateral temporal factor [HR = 0.67 (95% CI, 0.52-0.871, p<0.011. When applied to the second cohort, these Cox models showed significant effects for the medial temporal factor [HR = 0.44 (0.32-0.61), p<0.0011 and lateral temporal factor [HR = 0.49 (0.38-0.62), p<0.001]. In a combined Cox model, consisting of individual CSF, PET, and MRI measures that best predicted disease progression, only the medial temporal factor [HR = 0.53 195% CI, 0.34-0.811, p<0.001] demonstrated a significant effect. These findings illustrate that automated MRI measures of the medial temporal cortex accurately and reliably predict time to disease progression, outperform cellular and metabolic measures as predictors of clinical decline, and can potentially serve as a predictive marker for AD. (C) 2010 Elsevier Inc. All rights reserved.
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