Supervoxel-based statistical analysis of diffusion tensor imaging in schizotypal personality disorder
- 点击次数：
- 影响因子：5.46
- DOI码：10.1016/j.neuroimage.2017.07.026
- 发表刊物：Neuroimage
- 关键字：Diffusion tensor imaging; Schizotypal personality disorder; Supervoxel; Statistical analysis
- 摘要：To study white matter changes in schizotypal personality disorder (SPD), we developed a new statistical analysis method based on supervoxels for diffusion tensor imaging. Twenty patients with SPD and eighteen healthy controls were recruited from a pool of 3000 first-year university undergraduates, and underwent MRI using a 3T scanner. Diffusion tensors were first normalized into ICBM-152 space followed by a supervoxel segmentation based on graph clustering to segment white matter tensors into diffusion homogeneous supervoxels. Fractional anisotropy (FA) values in supervoxels were compared between SPD and healthy controls using permutation test. Suprathreshold cluster size test was used to correct multiple comparison. At last, fibers with significant differences were extracted from supervoxel clusters with significance level P < 0.05. Results showed that FA values in genu of corpus callosum were significantly reduced (P = 0.012) in patients with SPD (FA = 0.565) compared with healthy controls (FA = 0.593). In summary, this study proposed a novel supervoxel segmentation method for diffusion tensor imaging using graph-based clustering, and extended permutation test and suprathreshold cluster size test to supervoxels for detection of white matter changes.
- 论文类型：期刊论文
- 学科门类：医学
- 文献类型：J
- 卷号：163
- 页面范围：368-378
- 是否译文：否
- 发表时间：2017-07-13
- 收录刊物：SCI
- 发布刊物链接：https://www.sciencedirect.com/science/article/pii/S1053811917305943?via%3Dihub
