Aberrant brain structural network and altered topological organization in minimal hepatic encephalopathy.

PURPOSE: We aimed to investigate the multilevel impairments of brain structural network in patients with minimal hepatic encephalopathy (MHE). METHODS: Twenty-two patients with MHE and 22 well-matched healthy controls (HC) underwent structural magnetic resonance imaging (MRI) brain scans and neuropsychological evaluations. Individual brain structural networks were constructed using diffusion tensor imaging. Comparing with HC, we investigated the possible impairments of brain structural network in MHE, by applying graph-theory approaches to analyze the topological organization at global, modular, and local levels. The correlations between altered brain structural network and neuropsychological tests scores and venous ammonia levels were also examined in MHE patients. RESULTS: In the MHE group, small-worldness showed significant decrease and normalized characteristic path length showed increase at the global level. In the modular section, six modules were identified. The inter-modular connective strengths showed significant increase between modules 2 and 4 and between modules 4 and 5. The results of node analysis showed similar hub distributions in the MHE and HC groups except for the right postcentral gyrus, which was only found in the MHE group. No significant differences were found in connective strength of edges between MHE and HC groups using network-based statistics. CONCLUSION: The altered brain structural networks with reduced network integration and module segregation were demonstrated in patients with MHE. The dysconnectivity of brain structural network could provide an explanation for the brain dysfunctions of MHE.

Structural Brain Network Alteration and its Correlation With Structural Impairments in Patients With Depression in de novo and Drug-Naïve Parkinson's Disease.

Purpose: Depression is common in Parkinson's disease (PD) and is correlated with the severity of motor deficits and quality of life. The present study aimed to investigate alterations in the structural brain network related to depression in Parkinson's disease (d-PD) and their correlations with structural impairments of white matter (WM). Materials and Methods: Data were acquired from the Parkinson Progression Markers Initiative (PPMI) database. A total of 84 de novo and drug-naïve PD patients were screened and classified into two groups according to the 15-item Geriatric Depression Scale (GDS-15): d-PD (n = 28) and nondepression in PD (nd-PD, n = 56). Additionally, 37 healthy controls (HC) were screened. All subjects underwent DTI and 3D-T1WI on a 3.0 T MR scanner. Individual structural brain networks were constructed and analyses were performed using graph theory and network-based statistics (NBS) at both global and local levels. Differences in global topological properties were explored among the three groups. The association models between node and edge changes and the GDS-15 were constructed to detect regions that were specifically correlated with d-PD. Tract-based spatial statistics (TBSS) was used to detect structural impairments of WM between the d-PD and nd-PD groups. The correlations between altered global topological properties and structural impairments were analyzed in the d-PD group. Results: The global efficiency and characteristic path length of the structural brain network were impaired in the d-PD group compared with those in the nd-PD and HC groups. Thirteen nodes and 1 subnetwork with 10 nodes and 12 edges specifically correlated with d-PD were detected. The left hippocampus, left parahippocampal, left lingual, left middle occipital, left inferior occipital, left fusiform, left middle temporal, and left inferior temporal regions were all involved in the results of node and edge analysis. No WM microstructural impairments were identified in the d-PD group. Conclusion: Our study suggests that the integration of the structural brain network is impaired with disrupted connectivity of limbic system and visual system in the de novo and drug-naïve d-PD patients.The topological properties assessing integration of the structural brain network can serve as a potential objective neuroimaging marker for early diagnosis of d-PD.