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Tractography-based classification in distinguishing patients with first-episode schizophrenia from healthy individuals | |
Deng, Yi1,2,3; Hung, Karen S. Y.1; Lui, Simon S. Y.1,2; Chui, William W. H.2; Lee, Joe C. W.1; Wang, Yi2,4![]() ![]() | |
First Author | Deng, Yi |
Correspondent Email | cheungfc@ha.org.hk (e.f.c. cheung). |
Contribution Rank | 2 |
Abstract | Background: Schizophrenia has been characterized as a neurodevelopmental disorder of brain disconnectivity. However, whether disrupted integrity of white matter tracts in schizophrenia can potentially serve as individual discriminative biomarkers remains unclear. Methods: A random forest algorithm was applied to tractography-based diffusion properties obtained from a cohort of 65 patients with first-episode schizophrenia (FES) and 60 healthy individuals to investigate the machine-learning discriminative power of white matter disconnectivity. Recursive feature elimination was used to select the ultimate white matter features in the classification. Relationships between algorithm-predicted probabilities and clinical characteristics were also examined in the FES group. Results: The classifier was trained by 80% of the sample. Patients were distinguished from healthy individuals with an overall accuracy of 71.0% (95% confident interval: 61.1%, 79.6%), a sensitivity of 67.3%, a specificity of 75.0%, and the area under receiver operating characteristic curve (AUC) was 79.3% (chi(2) p < 0.001). In validation using the held-up 20% of the sample, patients were distinguished from healthy individuals with an overall accuracy of 76.0% (95% confident interval: 54.9%, 90.6%), a sensitivity of 76.9%, a specificity of 75.0%, and an AUC of 73.1% (chi(2) p = 0.012). Diffusion properties of inter-hemispheric fibres, the cerebello-thalamo-cortical circuits and the long association fibres were identified to be the most discriminative in the classification. Higher predicted probability scores were found in younger patients. Conclusions: Our findings suggest that the widespread connectivity disruption observed in FES patients, especially in younger patients, might be considered potential individual discriminating biomarkers. |
Keyword | Corpus Callosum Diffusion Tensor Imaging Discriminant Analysis Psychosis Machine Learning Random Forest |
2019-01-10 | |
Language | 英语 |
DOI | 10.1016/j.pnpbp.2018.06.010 |
Source Publication | PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY
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ISSN | 0278-5846 |
Volume | 88Pages:66-73 |
Subtype | article |
Funding Project | Philip KH Wong Foundation ; Beijing Training Project for Leading Talents in ST[Z151100000315020] ; Beijing Municipal Science & Technology Commission Grant[Z161100000216138] |
Publisher | PERGAMON-ELSEVIER SCIENCE LTD |
WOS Keyword | Brain ; Abnormalities ; Disease ; Antipsychotics ; Challenges ; Biomarkers ; Fasciculus ; Accuracy ; Images |
WOS Research Area | Neurosciences & Neurology ; Pharmacology & Pharmacy ; Psychiatry |
WOS Subject | Clinical Neurology ; Neurosciences ; Pharmacology & Pharmacy ; Psychiatry |
WOS ID | WOS:000445634300007 |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.psych.ac.cn/handle/311026/27121 |
Collection | 中国科学院心理健康重点实验室 |
Corresponding Author | Cheung, Eric F. C. |
Affiliation | 1.Castle Peak Hosp, Tuen Mun, Hong Kong, Peoples R China 2.Chinese Acad Sci, Inst Psychol, Neuropsychol & Appl Cognit Neurosci Lab, CAS Key Lab Mental Hlth, Beijing, Peoples R China 3.Univ Calif Davis, MIND Inst, Cognit Anal & Brain Imaging Lab, Davis, CA 95616 USA 4.Univ Chinese Acad Sci, Dept Psychol, Beijing, Peoples R China 5.Univ Hong Kong, Dept Radiol, Hong Kong, Hong Kong, Peoples R China 6.Univ Hong Kong, Ctr Genom Sci, Hong Kong, Hong Kong, Peoples R China |
First Author Affilication | 认知与发展心理学研究室 |
Corresponding Author Affilication | 认知与发展心理学研究室 |
Recommended Citation GB/T 7714 | Deng, Yi,Hung, Karen S. Y.,Lui, Simon S. Y.,et al. Tractography-based classification in distinguishing patients with first-episode schizophrenia from healthy individuals[J]. PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY,2019,88:66-73. |
APA | Deng, Yi.,Hung, Karen S. Y..,Lui, Simon S. Y..,Chui, William W. H..,Lee, Joe C. W..,...&Cheung, Eric F. C..(2019).Tractography-based classification in distinguishing patients with first-episode schizophrenia from healthy individuals.PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY,88,66-73. |
MLA | Deng, Yi,et al."Tractography-based classification in distinguishing patients with first-episode schizophrenia from healthy individuals".PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY 88(2019):66-73. |
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Tractography-based c(1249KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | Application Full Text |
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