The Preliminary Research Of PHN Brain’s Structural Networks Based On The Graph Theoretical Approach

Objective:This study used in cross interdisciplinary research topics of brain network analysis method,the diffusion tensor imaging technology combining with the graph theory,we employed the Automated Anatomical Labeling template to parcellate the cerebral cortex into 90 cortical and subcortical regions(45 for each hemisphere),each representing a node of the cortical network,Edge weight(wij)was computed as the multiplication of fiber number(FN)by the mean FA along the fiber bundles between a pair of cortical regions,Wij = FNij×FAij.As a result,we constructed the weighted structural brain network(90×90)for each participant.To detect and quantitatively analyze any difference in topological organization of structural brain network between PHN and healthy comparison controls,and to understand and explore the PHN central micro change from a new perspective.Methods:15 cases of PHN patients and the gender,age and education matched healthy volunteers with magnetic resonance image data were collected,including whole brain DTI and 3D T1WI data(the same day all the subjects of general clinical data and PHN patients with VAS,the duration,location related information were collected).Beijing Normal University State Key Laboratory of brain and cognitive learning designed by DTI automatic processing software PANDA and based on Matlab software development point at magnetic resonance imaging data of complex brain network analysis software Gretna,NBS(Network-Based Statistic)for data processing,we employed the Automated Anatomical Labeling template to parcellate the cerebral cortex into 90 cortical and subcortical regions(45 for each hemisphere),each representing a node of the cortical network,Edge weight(Wij)was computed as the multiplication of fiber number(FN)by the mean FA along the fiber bundles between a pair of cortical regions,Wij FNij x FAij,constructed the weighted structural brain network(90x90)for each participant.By age,gender and education level as a covariate,using two independent sample t test on the two groups of subjects brain structural network model the topology characteristics and differences in statistical analysis,including small world properties,global efficiency and local efficiency,node efficiency.The correlation between two groups of network attributes and clinical variables(VAS score,the duration of disease)was analyzed,to observe whether there is a significant correlation between the abnormal change of network attributes and clinical variables in PHN patients.Results:1.The brain structural network of PHN group and normal control group had obvious"small world" characteristics(σ>1),small world properties of PHN group compared with the normal control group decreased slightly,but the difference was not statistically significant(using two sample t test was used for statistical analysis,adjusted by FDR,P<0.05,there was significant difference between the two groups).2.There was no significant difference between the PHN group and the HC group in the global efficiency and local efficiency of the brain structural network(P>0.05).3.PHN group brain structural network efficiency of each node compared with the HC group,the PHN group node efficiency significantly reduced,these brain regions including the left insula,the left parahippocampal gyrus,the left putamen,the right orbital middle frontal gyrus,the right orbital inferior frontal gyrus,the bilateral gyrus rectus,the right Inferior occipital gyrus(P<0.05).4.Compared with the HC group,the connection strength of edge in some brain regions of PHN group decreased significantly,these brain regions including the PHG.L—the LING.L,the LING.L—the REC.L,the REC.L—the ACG.R,the REC.L—the ORBsupmed.L,the ORBsupmed.L—the CAU.L,the ORBsupmed.L-the PUT.L,the CAU.R—the THA.L,the CAU.R—the SFGdor.L(P<0.05).5.Regression adjusted for age,gender and education degree,the correlation analysis showed that PHN node efficiency change and connection edge reduction withVAS,disease duration had no significant statistical correlation(P>0.05).Conclusion(s):1.The brain structural network of PHN patients and normal controls had obvious"small world" characteristics(σ>1),which confirmed that the human brain has a"small world" information processing model of economic and low energy,it reflects the optimal balance between the differentiation and integration of human brain structural network.2.There was no significant difference between PHN patients and normal controls in the global efficiency and local efficiency of the brain structural network(P<0.05),which indicated that the PHN brain structural network connection pattern did not change in nature.3.PHN structural brain networks in the left insula,the left parahippocampal gyrus,the left putamen,the right orbital middle frontal gyrus,the right orbital inferior frontal gyrus,the bilateral gyrus rectus and the right Inferior occipital gyrus node efficiency decreased significantly(P<0.05,adjusted by FDR),and the connection strength of edge in some brain regions of PHN group decreased significantly.These brain regions are involved in sensory,memory,emotion and emotional process,suggesting that PHN produces pain may originate from different brain regions connected structure imbalance,indirectly reflects the PHN patients with widespread white matter damage.4.Based on graph theory of brain structural network research method can be comprehensive,three-dimensional detect and quantitative analysis of brain network topology property,can provide a new direction for explore the central mechanism of PHN,to observe the brain structural network change and explain the corresponding clinical manifestations.