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Lv K, Zhang C, Liu B, Yang A, Luan J, Hu P, Yao Z, Liu J, Ma G. White matter structural changes before and after microvascular decompression for hemifacial spasm. Brain Struct Funct 2024; 229:959-970. [PMID: 38502329 DOI: 10.1007/s00429-023-02741-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 11/22/2023] [Indexed: 03/21/2024]
Abstract
Hemifacial spasm (HFS) is a syndrome characterized by involuntary contractions of the facial muscles innervated by the ipsilateral facial nerve. Currently, microvascular decompression (MVD) is an effective treatment for HFS. Diffusion weighted imaging (DWI) is a non-invasive advanced magnetic resonance technique that allows us to reconstruct white matter (WM) virtually based on water diffusion direction. This enables us to model the human brain as a complex network using graph theory. In our study, we recruited 32 patients with HFS and 32 healthy controls to analyze and compare the topological organization of whole-brain white matter networks between the groups. We also explored the potential relationships between altered topological properties and clinical outcomes. Compared to the HC group, the white matter network was disrupted in both preoperative and postoperative groups of HFS patients, mainly located in the somatomotor network, limbic network, and default network (All P < 0.05, FDR corrected). There was no significant difference between the preoperative and postoperative groups (P > 0.05, FDR corrected). There was a correlation between the altered topological properties and clinical outcomes in the postoperative group of patients (All P < 0.05, FDR corrected). Our findings indicate that in HFS, the white matter structural network was disrupted before and after MVD, and that these alterations in the postoperative group were correlated with the clinical outcomes. White matter alteration here described may subserve as potential biomarkers for HFS and may help us identify patients with HFS who can benefit from MVD and thus can help us make a proper surgical patient selection.
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Affiliation(s)
- Kuan Lv
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang District, Beijing, 100029, China
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
| | - Chuanpeng Zhang
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
- Department of Neurosurgery, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang District, Beijing, 100029, China
| | - Bing Liu
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang District, Beijing, 100029, China
- Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Aocai Yang
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang District, Beijing, 100029, China
- Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jixin Luan
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang District, Beijing, 100029, China
- Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Pianpian Hu
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang District, Beijing, 100029, China
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
| | - Zeshan Yao
- Jingjinji National Center of Technology Innovation, Beijing, China
| | - Jiang Liu
- Department of Neurosurgery, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang District, Beijing, 100029, China.
| | - Guolin Ma
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang District, Beijing, 100029, China.
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China.
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Li J, Liu X, Wang X, Liu H, Lin Z, Xiong N. Diffusion Tensor Imaging Radiomics for Diagnosis of Parkinson’s Disease. Brain Sci 2022; 12:brainsci12070851. [PMID: 35884658 PMCID: PMC9313106 DOI: 10.3390/brainsci12070851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 06/13/2022] [Accepted: 06/14/2022] [Indexed: 11/25/2022] Open
Abstract
Background: Diagnosis of Parkinson’s Disease (PD) based on clinical symptoms and scale scores is mostly objective, and the accuracy of neuroimaging for PD diagnosis remains controversial. This study aims to introduce a radiomic tool to improve the sensitivity and specificity of diagnosis based on Diffusion Tensor Imaging (DTI) metrics. Methods: In this machine learning-based retrospective study, we collected basic clinical information and DTI images from 54 healthy controls (HCs) and 56 PD patients. Among them, 60 subjects (30 PD patients and 30 HCs) were assigned to the training group, whereas the test cohort was 26 PD patients and 24 HCs. After the feature extraction and selection using newly developed image processing software Ray-plus, LASSO regression was used to finalize radiomic features. Results: A total of 4600 radiomic features were extracted, of which 12 were finally selected. The values of the AUC (area under the subject operating curve) in the training group, the validation group, and overall were 0.911, 0.931, and 0.919, respectively. Conclusion: This study introduced a novel radiometric and computer algorithm based on DTI images, which can help increase the sensitivity and specificity of PD screening.
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Affiliation(s)
- Jingwen Li
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (J.L.); (X.W.); (H.L.)
| | - Xiaoming Liu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China;
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, China
| | - Xinyi Wang
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (J.L.); (X.W.); (H.L.)
| | - Hanshu Liu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (J.L.); (X.W.); (H.L.)
| | - Zhicheng Lin
- Laboratory of Psychiatric Neurogenomics, McLean Hospital, Harvard Medical School, Belmont, MA 02478, USA;
| | - Nian Xiong
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; (J.L.); (X.W.); (H.L.)
- Wuhan Red Cross Hospital, Wuhan 430022, China
- Correspondence:
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