title: Altered brain anatomical networks and disturbed connection density in brain tumor patients revealed by diffusion tensor tractography.
abstract: OBJECTIVE
  Brain tumor patients are usually accompanied by impairments in cognitive functions, and these dysfunctions arise from the altered diffusion tensor of water molecules and disrupted neuronal conduction in white matter. Diffusion tensor imaging (DTI) is a powerful noninvasive imaging technique that can reflect diffusion anisotropy of water and brain white matter neural connectivity in vivo. This study was aimed to analyze the topological properties and connection densities of the brain anatomical networks in brain tumor patients based on DTI and provide new insights into the investigation of the structural plasticity and compensatory mechanism of tumor patient's brain.
  
  
  METHODS
  In this study, the brain anatomical networks of tumor patients and healthy controls were constructed using the tracking of white matter fiber bundles based on DTI and the topological properties of these networks were described quantitatively. The statistical comparisons were performed between two groups with six DTI parameters: degree, regional efficiency, local efficiency, clustering coefficient, vulnerability, and betweenness centrality. In order to localize changes in structural connectivity to specific brain regions, a network-based statistic approach was utilized. By comparing the edge connection density of brain network between two groups, the edges with greater difference in connection density were associated with three functional systems.
  
  
  RESULTS
  Compared with controls, tumor patients show a significant increase in small-world feature of cerebral structural network. Two-sample two-tailed t test indicates that the regional properties are altered in 17 regions ([Formula: see text]). Study reveals that the positive and negative changes in vulnerability take place in the 14 brain areas. In addition, tumor patients lose 3 hub regions and add 2 new hubs when compared to normal controls. Eleven edges show much significantly greater connection density in the patients than in the controls. Most of the edges with greater connection density are linked to regions located in the limbic/subcortical and other systems. Besides, most of the edges connect the two hemispheres of the brains.
  
  
  CONCLUSIONS
  The stronger small-world property in the tumor patients proves the existence of compensatory mechanism. The changes in the regional properties, especially the betweenness centrality and vulnerability, aid in understanding the brain structural plasticity. The increased connection density in the tumor group suggests that tumors may induce reorganization in the structural network.
authors.affiliation: Department of Biomedical Engineering, College of Automation, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao Street, Qinhuai District, Nanjing, 210016, Jiangsu Province, China.
authors.forename: Zhou
authors.initials: Z
authors.lastname: Yu
authors.affiliation: Department of Biomedical Engineering, College of Automation, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao Street, Qinhuai District, Nanjing, 210016, Jiangsu Province, China. taoling@nuaa.edu.cn.
authors.forename: Ling
authors.initials: L
authors.lastname: Tao
authors.affiliation: Department of Biomedical Engineering, College of Automation, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao Street, Qinhuai District, Nanjing, 210016, Jiangsu Province, China.
authors.forename: Zhiyu
authors.initials: Z
authors.lastname: Qian
authors.affiliation: Department of Biomedical Engineering, College of Automation, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao Street, Qinhuai District, Nanjing, 210016, Jiangsu Province, China.
authors.forename: Jiangfen
authors.initials: J
authors.lastname: Wu
authors.affiliation: Department of Neurosurgery, Nanjing Brain Hospital Affiliated to Nanjing Medical University, No. 264, Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu Province, China.
authors.forename: Hongyi
authors.initials: H
authors.lastname: Liu
authors.affiliation: Department of Biomedical Engineering, College of Automation, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao Street, Qinhuai District, Nanjing, 210016, Jiangsu Province, China.
authors.forename: Yun
authors.initials: Y
authors.lastname: Yu
authors.affiliation: Department of Biomedical Engineering, College of Automation, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao Street, Qinhuai District, Nanjing, 210016, Jiangsu Province, China.
authors.forename: Jiantai
authors.initials: J
authors.lastname: Song
authors.affiliation: Department of Biomedical Engineering, College of Automation, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao Street, Qinhuai District, Nanjing, 210016, Jiangsu Province, China.
authors.forename: Shaobo
authors.initials: S
authors.lastname: Wang
authors.affiliation: Department of Biomedical Engineering, College of Automation, Nanjing University of Aeronautics and Astronautics, No. 29, Yudao Street, Qinhuai District, Nanjing, 210016, Jiangsu Province, China.
authors.forename: Jinyang
authors.initials: J
authors.lastname: Sun
mesh_terms: D000328:Adult; D001921:Brain / Q000033:anatomy & histology / Q000000981:diagnostic imaging* / Q000502:physiology; D001931:Brain Mapping / Q000379:methods*; D001932:Brain Neoplasms / Q000000981:diagnostic imaging*; D016022:Case-Control Studies; D003071:Cognition; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009434:Neural Pathways / Q000000981:diagnostic imaging*; D055815:Young Adult
keywords: Anatomical network; Compensatory mechanism; Hub regions; Structural plasticity; Topological properties