Combining Disrupted and Discriminative Topological Properties of Functional Connectivity Networks as Neuroimaging Biomarkers for Accurate Diagnosis of Early Tourette Syndrome Children
Wen, Hongwei1,2,3; Liu, Yue4; Rekik, Islem5; Wang, Shengpei1,2,3; Chen, Zhiqiang1,2,3; Zhang, Jishui6; Zhang, Yue4; Peng, Yun4; He, Huiguang1,2,3,7; He HG(何晖光)
Source PublicationMOLECULAR NEUROBIOLOGY
2018-04-01
Volume55Issue:4Pages:3251-3269
SubtypeArticle
AbstractTourette syndrome (TS) is a childhood-onset neurological disorder. To date, accurate TS diagnosis remains challenging due to its varied clinical expressions and dependency on qualitative description of symptoms. Therefore, identifying accurate and objective neuroimaging biomarkers may help improve early TS diagnosis. As resting-state functional MRI (rs-fMRI) has been demonstrated as a promising neuroimaging tool for TS diagnosis, previous rs-fMRI studies on TS revealed functional connectivity (FC) changes in a few local brain networks or circuits. However, no study explored the disrupted topological organization of whole-brain FC networks in TS children. Meanwhile, very few studies have examined brain functional networks using machine-learning methods for diagnostics. In this study, we construct individual whole-brain, ROI-level FC networks for 29 drug-naive TS children and 37 healthy children. Then, we use graph theory analysis to investigate the topological disruptions between groups. The identified disrupted regions in FC networks not only involved the sensorimotor association regions but also the visual, default-mode and language areas, all highly related to TS. Furthermore, we propose a novel classification framework based on similarity network fusion (SNF) algorithm, to both diagnose an individual subject and explore the discriminative power of FC network topological properties in distinguishing between TS children and controls. We achieved a high accuracy of 88.79%, and the involved discriminative regions for classification were also highly related to TS. Together, both the disrupted topological properties between groups and the discriminative topological features for classification may be considered as comprehensive and helpful neuroimaging biomarkers for assisting the clinical TS diagnosis.
KeywordTourette Syndrome Children Functional Connectivity Graph Theory Topological Organization Similarity Network Fusion
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
Subject Area模式识别与智能系统
DOI10.1007/s12035-017-0519-1
WOS KeywordATTENTION-DEFICIT/HYPERACTIVITY DISORDER ; HUMAN BRAIN ; STRUCTURAL CONNECTIVITY ; CORTICAL THICKNESS ; GRAPH-THEORY ; DRUG-NAIVE ; MRI ; SCALE ; CLASSIFICATION ; CORTEX
Indexed BySCI ; SSCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(91520202 ; Youth Innovation Promotion Association CAS ; Beijing Municipal Administration of Hospitals Incubating Program(PX2016035) ; Beijing Health System Top level Health Technical Personnel Training Plan(2015-3-082) ; 61271151 ; 31271161 ; 81671651)
WOS Research AreaNeurosciences & Neurology
WOS SubjectNeurosciences
WOS IDWOS:000427097500042
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14657
Collection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
Corresponding AuthorHe HG(何晖光)
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Capital Med Univ, Beijing Childrens Hosp, Dept Radiol, 56 Nanlishi Rd, Beijing 100045, Peoples R China
5.Univ Dundee, Sch Sci & Engn, Comp, CVIP, Dundee, Scotland
6.Capital Med Univ, Beijing Childrens Hosp, Dept Neurol, Beijing, Peoples R China
7.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China;  Institute of Automation, Chinese Academy of Sciences
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GB/T 7714
Wen, Hongwei,Liu, Yue,Rekik, Islem,et al. Combining Disrupted and Discriminative Topological Properties of Functional Connectivity Networks as Neuroimaging Biomarkers for Accurate Diagnosis of Early Tourette Syndrome Children[J]. MOLECULAR NEUROBIOLOGY,2018,55(4):3251-3269.
APA Wen, Hongwei.,Liu, Yue.,Rekik, Islem.,Wang, Shengpei.,Chen, Zhiqiang.,...&何晖光.(2018).Combining Disrupted and Discriminative Topological Properties of Functional Connectivity Networks as Neuroimaging Biomarkers for Accurate Diagnosis of Early Tourette Syndrome Children.MOLECULAR NEUROBIOLOGY,55(4),3251-3269.
MLA Wen, Hongwei,et al."Combining Disrupted and Discriminative Topological Properties of Functional Connectivity Networks as Neuroimaging Biomarkers for Accurate Diagnosis of Early Tourette Syndrome Children".MOLECULAR NEUROBIOLOGY 55.4(2018):3251-3269.
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