More insights into disruption and decoupling of individually metabolic connectomes in Parkinson’s disease

Motivation: Metabolic disturbances are key features of Parkinson's disease (PD), captured noninvasively by arterial spin labeling (ASL). Specific patterns of metabolic disconnections remain scarcely documented. Goal(s): Validate the feasibility of constructing metabolic similarity networks (MSNs) using ASL and Jensen-Shannon divergence similarity estimation (JSSE), and characterize MSN impairments in PD. Approach: 48 PD patients and 50 healthy controls underwent multi-delay ASL (m-ASL) imaging. Perfusion metrics were used to construct MSNs via JSSE, followed by topological analysis and SVM classification. Results: MSNs showed complex connectomes with small-world properties in PD, with impaired network topology and modularity. m-ASL improved CBF diagnostic efficiency via ATT correction. Impact: Our study revealed complex metabolic disconnections underlying the neurodegenerative process in PD, highlighting the clinical implications of multi-delay ASL for comprehensive investigations of metabolic patterns of disconnection syndromes.