Multimodal MRI-based imputation of the Aβ+ in early mild cognitive impairment

Objective: The primary goal of this study was to identify brain atrophy from structural MRI (magnetic resonance imaging) and cerebral blood flow (CBF) patterns from arterial spin labeling perfusion MRI that are best predictors of the A beta-burden, measured as composite F-18-AV45-PET (positron emission tomography) uptake, in individuals with early mild cognitive impairment (MCI). Furthermore, another objective was to assess the relative importance of imaging modalities in classification of A beta+/A beta- early MCI. Methods: Sixty-seven Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 participants with early MCI were included. Voxel-wise anatomical shape variation measures were computed by estimating the initial diffeomorphic mapping momenta from an unbiased control template. CBF measures normalized to average motor cortex CBF were mapped onto the template space. Using partial least squares regression, we identified the structural and CBF signatures of A beta after accounting for normal cofounding effects of age, gender, and education. Results: F-18-AV45-positive early MCIs could be identified with 83% classification accuracy, 87% positive predictive value, and 84% negative predictive value by multidisciplinary classifiers combining demographics data, ApoE epsilon 4-genotype, and a multimodal MRI-based A beta score. Interpretation: Multimodal MRI can be used to predict the amyloid status of early-MCI individuals. MRI is a very attractive candidate for the identification of inexpensive and noninvasive surrogate biomarkers of A beta deposition. Our approach is expected to have value for the identification of individuals likely to be A beta+ in circumstances where cost or logistical problems prevent A beta detection using cerebrospinal fluid analysis or A beta-PET. This can also be used in clinical settings and clinical trials, aiding subject recruitment and evaluation of treatment efficacy. Imputation of the A beta-positivity status could also complement A beta-PET by identifying individuals who would benefit the most from this assessment.