Disrupted Structural and Metabolic Brain Networks with Structural - Metabolic Decoupling in Parkinson's Disease: An Integrated PET/MRI Study.
Using integrated 18F-FDG PET and DTI in 43 Parkinson's patients versus 25 controls, the study found preserved small-world topology but reduced metabolic network integration and significant regional decoupling between structural and metabolic connectivity—most prominently in orbitofrontal-basal…
What the AI sees
Using integrated 18F-FDG PET and DTI in 43 Parkinson's patients versus 25 controls, the study found preserved small-world topology but reduced metabolic network integration and significant regional decoupling between structural and metabolic connectivity—most prominently in orbitofrontal-basal…
Research significance
By revealing network-level structural–metabolic decoupling, especially in orbitofrontal–basal ganglia circuits, the work suggests multimodal imaging biomarkers for patient stratification and for tracking or targeting circuit- and metabolism-focused interventions, though it stops short of…
Source abstract
RATIONALE AND OBJECTIVES: Recent brain network studies have been broadly applied in Parkinson's disease (PD), but the relationship between structural and metabolic networks remains unclear. This study aimed to use integrated PET/MRI to investigate whether decoupling exists between structural and metabolic networks in the brains of PD patients, providing imaging evidence to elucidate the mechanisms of network disruption in PD. MATERIALS AND METHODS: We collected diffusion tensor imaging (DTI) data and 18F-FDG PET imaging data and from 43 patients with PD and 25 healthy controls (HC), generated structural connectivity (SC) and metabolic connectivity (MC) networks. Graph-theoretical methods were used to characterize the topological properties of networks. Based on Yeo 7-network parcellation, whole brain was divided into 7 functional modules, and the structural-metabolic connectivity (SC-MC) coupling was compared at both regional and module level. RESULTS: Both SC and MC networks of PD patients retained small-world properties. For global topological properties, MC network showed longer characteristic path length (Lp) and lower global efficiency (Eg), whereas SC network did not differ from controls. At whole-brain level, compared with HC, significant SC-MC decoupling in bilateral orbital inferior frontal gyrus (IFGorb), bilateral orbital middle frontal gyrus (MFGorb) and right pallidum (PG) (all with pFDR < 0.001) was showed in PD patients. At module level, stronger SC-MC coupling of somatomotor network (SMN) (pFDR = 0.04) was found in PD patients. However, visual network (VIS) (pFDR < 0.001), ventral attention network (VAN) (pFDR = 0.019) and frontoparietal control network (FPCN) (pFDR = 0.027) showed significant SC-MC decoupling in PD patients. CONCLUSION: Our results showed that PD is associated with reduced metabolic network integration and regional SC-MC decoupling, with the most prominent effects located in orbitofrontal-basal ganglia circuits. SC-MC may provide information complementary to SC-functional connectivity (FC) and shows promise as a multimodal, network-level biomarker.