Elucidating the complementarity of resting-state networks derived from dynamic [18F]FDG and hemodynamic fluctuations using simultaneous small-animal PET/MRI

Abstract

Functional connectivity (FC) and resting-state network (RSN) analyses using functional magnetic resonance imaging (fMRI) have evolved into a growing field of research and have provided useful biomarkers for the assessment of brain function in neurological disorders. However, the underlying mechanisms of the blood oxygen level-dependant (BOLD) signal are not fully resolved due to its inherent complexity. In contrast, [ 18 F]fluorodeoxyglucose positron emission tomography ([ 18 F]FDG-PET) has been shown to provide a more direct measure of local synaptic activity and may have additional value for the readout and interpretation of brain connectivity. We performed an RSN analysis from simultaneously acquired PET/fMRI data on a single-subject level to directly compare fMRI and [ 18 F]FDG-PET-derived networks during the resting state. Simultaneous [ 18 F]FDG-PET/fMRI scans were performed in 30 rats. Pairwise correlation analysis, as well as independent component analysis (ICA), were used to compare the readouts of both methods. We identified three RSNs with a high degree of similarity between PET and fMRI-derived readouts: the default-mode-like network (DMN), the basal ganglia network and the cerebellar-midbrain network. Overall, [ 18 F]FDG connectivity indicated increased integration between different, often distant, brain areas compared to the results indicated by the more segregated fMRI-derived FC. Additionally, several networks exclusive to either modality were observed using ICA. These networks included mainly bilateral cortical networks of a limited spatial extent for fMRI and more spatially widespread networks for [ 18 F]FDG-PET, often involving several subcortical areas. This is the first study using simultaneous PET/fMRI to report RSNs subject-wise from dynamic [ 18 F]FDG tracer delivery and BOLD fluctuations with both independent component analysis (ICA) and pairwise correlation analysis in small animals. Our findings support previous studies, which show a close link between local synaptic glucose consumption and BOLD-fMRI-derived FC. However, several brain regions were exclusively attributed to either [ 18 F]FDG or BOLD-derived networks underlining the complementarity of this hybrid imaging approach, which may contribute to the understanding of brain functional organization and could be of interest for future clinical applications.

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