Multi-threshold White Matter Structural Networks Fusion for Accurate Diagnosis of Tourette Syndrome Children
Wen Hongwei1,2; Yue Liu4; Shengpei Wang1,2; Zuoyong Li5; Jishui Zhang6; Yun Peng4; Huiguang He1,2,3; He Huiguang
2017-03
会议名称SPIE Medical Imaging 2017: Computer-Aided Diagnosis
会议录名称Proceedings of SPIE
卷号10134
页码101341Q-101341Q-13
会议日期2017-02
会议地点Orlando, USA
摘要

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. To date, TS is still misdiagnosed due to its varied presentation and lacking of obvious clinical symptoms. Therefore, studies of objective imaging biomarkers are of great importance for early TS diagnosis. As tic generation has been linked to disturbed structural networks, and many efforts have been made recently to investigate brain functional or structural networks using machine learning methods, for the purpose of disease diagnosis. However, few studies were related to TS and some drawbacks still existed in them. Therefore, we propose a novel classification framework integrating a multi-threshold strategy and a network fusion scheme to address the preexisting drawbacks. Here we used diffusion MRI probabilistic tractography to construct the structural networks of 44 TS children and 48 healthy children. We ameliorated the similarity network fusion algorithm specially to fuse the multi-threshold structural networks. Graph theoretical analysis was then implemented, and nodal degree, nodal efficiency and nodal betweenness centrality were selected as features. Finally, support vector machine recursive feature extraction (SVM-RFE) algorithm was used for feature selection, and then optimal features are fed into SVM to automatically discriminate TS children from controls. We achieved a high accuracy of 89.13% evaluated by a nested cross validation, demonstrated the superior performance of our framework over other comparison methods. The involved discriminative regions for classification primarily located in the basal ganglia and frontal cortico-cortical networks, all highly related to the pathology of TS. Together, our study may provide potential neuroimaging biomarkers for early-stage TS diagnosis.

关键词Tourette Syndrome Diffusion Mri Probabilistic Tractography Structural Connectivity Graph Theoretical Analysis Similarity Network Fusion Support Vector Machine
学科领域Medical Imaging
收录类别EI
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/14662
专题复杂系统管理与控制国家重点实验室_影像分析与机器视觉
通讯作者He Huiguang
作者单位1.Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China
2.University of Chinese Academy of Sciences, Beijing, China
3.Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, China
4.Department of Radiology, Beijing Children’s Hospital, Capital Medical University, Beijing, China
5.Fujian Provincial Key Laboratory of Information Processing and Intelligent Control (Minjiang University), Fuzhou, 350121, China
6.Department of Neurology, Beijing Children’s Hospital, Capital Medical University, Beijing, China
推荐引用方式
GB/T 7714
Wen Hongwei,Yue Liu,Shengpei Wang,et al. Multi-threshold White Matter Structural Networks Fusion for Accurate Diagnosis of Tourette Syndrome Children[C],2017:101341Q-101341Q-13.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
发表的SPIE Medical Imag(2634KB)会议论文 开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Wen Hongwei]的文章
[Yue Liu]的文章
[Shengpei Wang]的文章
百度学术
百度学术中相似的文章
[Wen Hongwei]的文章
[Yue Liu]的文章
[Shengpei Wang]的文章
必应学术
必应学术中相似的文章
[Wen Hongwei]的文章
[Yue Liu]的文章
[Shengpei Wang]的文章
相关权益政策
暂无数据
收藏/分享
文件名: 发表的SPIE Medical Imaging论文(10134-59).pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。