Kang Min Park1, Keun Tae Kim2, Dong Ah Lee1, Yong Won Cho2. 1. Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, South Korea. 2. Department of Neurology, Keimyung University School of Medicine, Daegu, South Korea.
Abstract
STUDY OBJECTIVES: To evaluate alterations of global and local structural brain connectivity in patients with restless legs syndrome (RLS). METHODS: Patients with primary RLS and healthy controls were recruited at a sleep center where they underwent diffusion tensor imaging (DTI) of the brain. We calculated the network measures of global and local structural brain connectivity based on the DTI in both groups using DSI studio program and a graph theory. RESULTS: A total of 69 patients with primary RLS and 51 healthy controls were included in the study. We found a significant difference in the global structural connectivity between the groups. The transitivity in the patients with RLS was lower than that in healthy controls (0.031 vs. 0.033, p = 0.035). Additionally, there were significant differences in the local structural connectivity between the groups. The characteristic path length (r = 0.283, p = 0.018), radius of graph (r = 0.260, p = 0.030), and diameter of graph (r = 0.280, p = 0.019) were all positively correlated with RLS severity, whereas the mean clustering coefficient (r = -0.327, p = 0.006), global efficiency (r = -0.272, p = 0.023), small-worldness index (r = -0.325, p = 0.006), and transitivity (r = -0.351, p = 0.003) were negatively correlated with RLS severity. CONCLUSION: We identified changes in the global structural connectivity of patients with RLS using graph theory based on DTI, which showed decreased segregation in the brain network compared to healthy controls. These changes are well correlated with RLS severity. We also found changes in local structural connectivity, especially in regions involved in sensorimotor function, which suggests that these areas play a pivotal role in RLS. These findings contribute to a better understanding of the pathophysiology of RLS symptoms.
STUDY OBJECTIVES: To evaluate alterations of global and local structural brain connectivity in patients with restless legs syndrome (RLS). METHODS: Patients with primary RLS and healthy controls were recruited at a sleep center where they underwent diffusion tensor imaging (DTI) of the brain. We calculated the network measures of global and local structural brain connectivity based on the DTI in both groups using DSI studio program and a graph theory. RESULTS: A total of 69 patients with primary RLS and 51 healthy controls were included in the study. We found a significant difference in the global structural connectivity between the groups. The transitivity in the patients with RLS was lower than that in healthy controls (0.031 vs. 0.033, p = 0.035). Additionally, there were significant differences in the local structural connectivity between the groups. The characteristic path length (r = 0.283, p = 0.018), radius of graph (r = 0.260, p = 0.030), and diameter of graph (r = 0.280, p = 0.019) were all positively correlated with RLS severity, whereas the mean clustering coefficient (r = -0.327, p = 0.006), global efficiency (r = -0.272, p = 0.023), small-worldness index (r = -0.325, p = 0.006), and transitivity (r = -0.351, p = 0.003) were negatively correlated with RLS severity. CONCLUSION: We identified changes in the global structural connectivity of patients with RLS using graph theory based on DTI, which showed decreased segregation in the brain network compared to healthy controls. These changes are well correlated with RLS severity. We also found changes in local structural connectivity, especially in regions involved in sensorimotor function, which suggests that these areas play a pivotal role in RLS. These findings contribute to a better understanding of the pathophysiology of RLS symptoms.