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    张腾

    • 讲师(高校) 硕士生导师
    • 性别:男
    • 所在单位:人工智能学院(未来技术学院、人工智能产业学院)
    • 办公地点:临江楼A1909
    • 联系方式:zhangteng@nuist.edu.cn

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    Group comparison of cortical fiber connectivity map: An application between post-stroke patients and healthy subjects

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    影响因子:3.4

    发表刊物:Neuroscience

    关键字:Cortex; Connectome; Fiber connectivity map; Vertex-wise statistical analysis

    摘要:Structural connectome measurement combined with diffusion magnetic resonance imaging (MRI) and tractography allows generation of a whole-brain connectome. However, current cortical structural connectivity (SC) measurements have not been well combined with the vertex-wise multi-subjects statistical analysis. The aim of this study was to examine the feasibility of using group comparison vertex-wise analysis for cortical SC measurement. A fiber connectivity density (FiCD) method based on a combination of a diffusion fiber tracking technique and cortical surface-based analysis was used to measure the whole-brain cortical SC map (FiCD map). A public MRI dataset (GigaDB) was employed to evaluate the reproducibility of the FiCD method. For group comparison, 14 post-stroke patients (mean age, 68.36 ± 7.33 y) and 19 healthy participants (mean age, 66.84 ± 8.58 y) had FiCD measurement. The intergroup comparison of the FiCD map was performed using vertex-wise multi-subject statistical analysis. Reliability testing showed the mean intra- and inter-subject FiCD variability was 3.51 ± 2.12% and 19.44 ± 4.79%, respectively. The group comparison of the whole-brain FiCD identified cortical regions with altered FiCD values, and there was a spatial consistency between the cortical clusters with low FiCD values and the subcortical lesions of patients. This study demonstrated the feasibility of vertex-wise group comparison for evaluating cortical fiber connectivity density. The FiCD method has good intra- and inter-individual reproducibility, and accurately reflects the affected cortical regions in post-stroke patients. This method may be helpful for neuroscience research.

    论文类型:期刊论文

    学科门类:医学

    文献类型:J

    卷号:344

    页面范围:15-24

    是否译文:

    发表时间:2017-03-06

    收录刊物:SCI