Abstract
The objective of this study was to validate disease-related metabolic brain patterns for Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy. The study included 20 patients with Parkinson's disease, 21 with multiple system atrophy, and 17 with progressive supranuclear palsy, all of whom had undergone a clinically motivated [18F]-fluoro-deoxyglucose positron emission tomography scan at an early stage of their disease. At a follow-up time after the scan of 2-4 years, a clinical diagnosis was made according to established clinical research criteria. Patient groups were compared with 18 healthy controls using a multivariate covariance image analysis technique called scaled subprofile model/principal component analysis. Disease-related metabolic brain patterns for these parkinsonian disorders were identified. Validation showed that these patterns were highly discriminative of the 3 disorders. Early diagnosis of parkinsonian disorders is feasible when the expression of disease-related metabolic brain patterns is quantified at a single-subject level.
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