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The data obtained from measurements of regional rCMR glu using 18 Ffluorodeoxyglucose (FDG)/positron emission tomographic (PET) data contain more structure than can be identified with group mean rCMR glu profiles or regional correlation coefficients. This additional structure is revealed by a novel mathematical-statistical model of regional metabolic interactions that explicitly represents rCMR glu profiles as a combination of region-independent global effects, a group mean pattern and a mosaic of interacting networks. In its application to FDG/PET data, this model removes global subject effects global scaling factors (GSFs) and a group mean pattern (profile) so as to maximize statistical power for the detection and simultaneous discovery of all networks of two or more regions that form a significant and consistent linearly covarying pattern. The model approach presented here was applied to the combined rCMR glu data from 12 demented AIDS patients and 18 normal controls: Two significant metabolic covariance pattern descriptors that together accounted for 71 to 96% of the rCMR glu /GSF variation across subjects for 22/28 regions in the AIDS group were extracted. Each descriptor was found to be highly correlated with performance on several neuropsychological tests, providing independent validation of the analysis technique as a means of discovering and describing behaviorally related components of group rCMR glu profiles.
Moeller et al. (Thu,) studied this question.