Regional brain metabolism and metabolic connectivity alterations in corticobasal syndrome assessed with [18F]FDG-PET

PURPOSE: F]FDG-PET) studies have described regional metabolic abnormalities but detailed subcortical and cerebellar structures involvement is less known and metabolic connectivity remains unexplored. This study combined voxel-based, region-of-interest (ROI) analyses and connectivity approaches to further characterize metabolic alterations and to provide a network-level framework in CBS. METHODS: F]FDG-PET at two sites, with images flipped to align the most affected hemisphere; 99 controls were drawn from a national normative database. Voxel-based SPM method and ROIs analysis were performed. Thirty-six bilateral cortical and subcortical regions of interest were processed to perform interregional correlation and network-based analyses within five functional networks. Pairwise Spearman correlations were computed from normalized regional signals. Group differences were assessed at regional and network levels using Fisher-transformed correlations, Cohen's q, permutation testing (10,000 iterations), and graph-theoretical metrics (node strength, clustering coefficient; threshold ρ > 0.25). RESULTS: CBS patients showed asymmetric hypometabolism predominantly in frontal, parietal, and temporal cortices, caudate and thalamus of the predominantly affected hemisphere, with additional contralateral involvement, notably in the cerebellum and caudate. Metabolic connectivity analyses revealed widespread intra- and inter-network disconnection, particularly involving frontal, parietal, and sensorimotor cortices, and thalamo-cortical pathways, with significant lateralization toward the affected hemisphere. Graph analysis showed decreased cortical node strength with relative increases in subcortical hubs and mixed changes in clustering coefficients, suggesting network reorganization. CONCLUSION: F]FDG-PET metabolic connectivity study in CBS demonstrates asymmetric and bilateral regional hypometabolism, widespread and lateralized network disconnection, and subcortical reorganization. These findings reflect both degenerative, functional and compensatory mechanisms and highlight metabolic connectivity as a sensitive marker of network-level alterations in neurodegenerative disease.