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Background: Freezing of gait (FOG) is a common disabling gait disturbance in Parkinson's disease (PD). The objectives of this study were to explore alterations in the topological organization of whole-brain functional networks in patients with PD who will develop FOG. Methods: We recruited 20 patients with PD who developed FOG (PD-FOGt) during a 5-year follow-up period, 20 patients with PD who did not developed FOG (PD-FOGn) within the follow-up period, and 20 healthy control subjects. Using graph theory approaches, we performed a comparative analysis of the topological organization of whole-brain functional networks among the groups, and further explored their potential relationships with latency to develop FOG. Results: At baseline, the global topological properties of functional brain networks in PD-FOGt and PD-FOGn showed no abnormalities. Additionally, regarding regional topological properties, compared with PD-FOGn patients, PD-FOGt patients exhibited decreased nodal centrality in the left middle frontal gyrus (MFG). Although there were no significant differences compared with PD-FOGn patients, the PD-FOGt group exhibited the lowest nodal centrality values in the frontal cortex (left gyrus rectus), and visual cortex (bilateral inferior occipital gyrus and left fusiform gyrus), and the highest nodal centrality values in the cerebellum (vermis_6) among the three groups. However, no relationship was found between the nodal centrality in above brain regions and latency to develop FOG. Conclusion: This study demonstrates the disrupted regional topological organization might contribute to the future development of FOG in PD patients, especially associated with damage to the left MFG. [ABSTRACT FROM AUTHOR]

Purpose: To use structural magnetic resonance imaging and graph theory approaches to investigate the topological organization of the brain morphological network based on gray matter in essential tremor, and its potential relation to disease severity. Methods: In this prospective study conducted from November 2018 to November 2019, 36 participants with essential tremor and 37 matched healthy controls underwent magnetic resonance imaging. Brain networks based on the morphological similarity of gray matter across regions were analyzed using graph theory. Nonparametric permutation testing was used to assess group differences in topological metrics. Support vector machine was applied to the gray matter morphological matrices to classify participants with essential tremor vs. healthy controls. Results: Compared with healthy controls, participants with essential tremor showed increased global efficiency (p < 0.01) and decreased path length (p < 0.01); abnormal nodal properties in frontal, parietal, and cerebellar lobes; and disconnectivity in cerebello-thalamo-cortical network. The abnormal brain nodal centralities (left superior cerebellum gyrus; right caudate nucleus) correlated with clinical measures, both motor (Fahn–Tolosa–Marìn tremor rating, p = 0.017, r = − 0.41) and nonmotor (Hamilton depression scale, p = 0.040, r = − 0.36; Hamilton anxiety scale, p = 0.008, r = − 0.436). Gray matter morphological matrices classified individuals with high accuracy of 80.0%. Conclusion: Participants with essential tremor showed randomization in global properties and dysconnectivity in the cerebello-thalamo-cortical network. Participants with essential tremor could be distinguished from healthy controls by gray matter morphological matrices. [ABSTRACT FROM AUTHOR]