The Characteristics of Brain Structural Network in Patients with Low Grade Glioma Revealed by Diffusion Tensor Imaging

Ling Tao (Login required)
Nanjing University of Aeronautics and Astronautics, China

Zhiyu Qian
Nanjing University of Aeronautics and Astronautics, China

Yamin Yang
Nanjing University of Aeronautics and Astronautics, China

Hongyi Liu
Nanjing Brain Hospital Affiliated to Nanjing Medical University, China

Li Xue
Nanjing University of Aeronautics and Astronautics, China


Paper #3154 received 24 Jan 2017; revised manuscript received 5 May 2017; accepted for publication 10 May 2017; published online 15 Jun 2017.

DOI: 10.18287/JBPE17.03.030301

Abstract

Purpose: At present, few studies have investigated the functional performance in patients with low grade glioma (LGG) from the perspective of brain structural characteristics. This study aimed to analyze the topological properties of brain structural networks in LGG patients and investigate the influence of operation and lesion location on whole-brain and hemisphere networks. On this basis, the structural plasticity and function compensatory mechanism of LGG patient were discussed. Method: We constructed whole-brain and hemisphere anatomical networks for 20 LGG patients and 20 normal controls (NC). The structural connections were established by selecting an appropriate connectivity threshold.  Brain hub nodes and random nodes between LGG and NC were compared. Statistical analyses were performed to reveal the significant differences of various network characteristics between LGG patients and NC as well as between LGG patients before and after operation. The two-factor variance analysis was used to investigate the influence of operation and lesion location on whole-brain and hemisphere networks. Results: From the graph-based topological metrics of the constructed network, various global parameters changed significantly in LGG patients. Meanwhile, altered regions in the LGG patients was obtained and various nodal parameters were further calculated in each region. Most of hub nodes were identical between LGG and NC groups, while the betweenness centrality values of those hub nodes and some random nodes were higher in the LGG patients. By comparing LGG patients pre- and post- operation, more significantly altered network metrics were obtained from hemisphere network analysis than that from whole-brain network analysis, and network features of dominant hemisphere changed more drastically when the lesion is located in the same hemisphere. Conclusion: To conclude, the present study indicates the existence of compensatory mechanism in LGG patients to adapt to cognitive requirements. Function reorganization and the rewiring of neuronal circuits allow signal transmission bypassing the lesion area or surgical trauma. It also suggests that graph-based topological metrics analysis could become a useful method to provide valuable indices of brain function in the evaluation of the LGG.

Keywords

Structural network; Topological properties; Brain plasticity; Compensatory mechanism; Functional lateralization

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