Evaluate How WMH Affects Constructing of Cerebral Neural Network Using Graph Theory

• Main Authors: Wan-Chu Teng, 鄧婉竹
• Other Authors: Ching-Po Lin
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/43216532477872177806

碩士 === 國立陽明大學 === 腦科學研究所 === 104 === White matter hyperintensities (WMH) refers in high signal areas that appears in T2-weighted MRI images. According to previous studies, the incidence of this high-signal areas increase with age and vascular disease risk factors. This high signal area may be couse by edema, gliosis, or nerve sheath cells with damage, causing water molecules within nerve can not be completely covered in myelin sheath. So this areas of high signal can be regarded as white matter lesions or mutate position. In diffusion imaging studys ,WMH region were showing the average amount of diffusion has significantly increased, anisotropic diffusion characteristics are significant decline, indicating that integrity nerve fiber are damage in the area. WMH in addition to reducing the integrity of nerve fibers, are more likely to cause low efficiency communication between the cerebral cortex, directly affect the overall network architecture of the brain, which causes the degradation of cognitive function. In order to compare the diffusion tensor network estimated by diffusion tensor imaging (DTI) using tractography algorithm, coupled with known template for brain partition, by graph theory we can build cerebral neural network. 90 subjects with varying degrees of white matter lesions acquired DWI, T1 and T2 FLAIR weight images on 3T MRI. FLAIR lesion segmentation toolbox (FLEX) was then used to segment WMH volume. The graph theory will be used to establish cerebral neural network with 90 regions segmentation by AAL (Automated Anatomical Labeling) template, and network topological parameters can be compared. White matter directions can be under the precondition that WMH may couse white matter lesions, expected the overall network transmission efficiency of the brain will accordingly decrease. This paper aims to investigate how white matter lesions in MR imaging of the brain affects brain DTI-based network. Previously known white matter injury can affect the structure of myelin causing directivity strength educe of water molecules diffusion. We anticipated that network structure and transmission efficiency of the brain will be diminished. The study found that WMH affected part of the transmission of brain network, that it’s not powerful enough to break the transmission but to reduce the transmission efficiency. We also noted that WMH reduce the transmission of the effects brain network more when the brain perform certain cognitive performance, is obvious when compared to other cognitive functions brain processing.