Multiscale entropy and small-world network analysis in rs-fMRI — new tools to evaluate early basal ganglia dysfunction in diabetic peripheral neuropathy

Abstract

Objective: The risk of falling increases in diabetic peripheral neuropathy (DPN) patients. As a central part, Basal ganglia play an important role in motor and balance control, but whether its involvement in DPN is unclear. Methods: Ten patients with confirmed DPN, ten diabetes patients without DPN, and ten healthy age-matched controls(HC) were recruited to undergo magnetic resonance imaging(MRI) to assess brain structure and zone adaptability. Multiscale entropy and small-world network analysis were then used to assess the complexity of the hemodynamic response signal, reflecting the adaptability of the basal ganglia. Results: There was no significant difference in brain structure among the three groups, except the duration of diabetes in DPN patients was longer (p < 0.05). The complexity of basal ganglia was significantly decreased in the DPN group compared with the non-DPN and HC group (p < 0.05), which suggested their poor adaptability. Conclusion: In the sensorimotor loop, peripheral and early central nervous lesions exist simultaneously in DPN patients. Multiscale Entropy and Small-world Network Analysis could detect basal ganglia dysfunction prior to structural changes in MRI, potentially valuable tools for early non-invasive screening and follow-up.