18FDG PET in vascular dementia: differentiation from Alzheimer's disease using voxel-based multivariate analysis

Journal of Cerebral Blood Flow and Metabolism : Official Journal of the International Society of Cerebral Blood Flow and Metabolism
Nacer KerroucheJean-Claude Baron

Abstract

The brain metabolic pattern of vascular dementia (VaD) remains poorly characterized. Univariate voxel-based analysis ignores the functional correlations among structures and may lack sensitivity and specificity. Here, we applied a novel voxel-based multivariate technique to a large ((18)F)2-fluoro-2-deoxy-D-glucose positron emission tomography data set. The sample consisted of 153 subjects, one-third each being probable subcortical VaD, probable Alzheimer disease (AD) (matched for Mini-Mental-State examination (MMSE) and age), and normal controls (NCs). We first applied principal component (PC) analysis and removed PCs significantly correlated to age. The remainders were used as feature vectors in a canonical variate analysis to generate canonical variates (CVs), that is, linear combinations of PC-scores. The first two CVs efficiently separated the groups. CV(1) separated VaD from AD with 100% accuracy, whereas CV(2) separated NC from demented subjects with 72% sensitivity and 96% specificity. Images depicting CV(1) and CV(2) showed that lower metabolism differentiating VaD from AD mainly concerned the deep gray nuclei, cerebellum, primary cortices, middle temporal gyrus, and anterior cingulate gyrus, whereas lower metabolism i...Continue Reading

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Citations

Mar 6, 2007·Molecular Imaging and Biology : MIB : the Official Publication of the Academy of Molecular Imaging·Yilong Ma, David Eidelberg
Apr 27, 2011·Neurology·M J FirbankJ T O'Brien
Jul 31, 2013·PloS One·Gretel Sanabria-DiazUNKNOWN Alzheimer’s Disease Neuroimaging Initiative
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