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Wang M, Cheng X, Shi Q, Xu B, Hou X, Zhao H, Gui Q, Wu G, Dong X, Xu Q, Shen M, Cheng Q, Xue S, Feng H, Ding Z. Brain diffusion tensor imaging reveals altered connections and networks in epilepsy patients. Front Hum Neurosci 2023; 17:1142408. [PMID: 37033907 PMCID: PMC10073437 DOI: 10.3389/fnhum.2023.1142408] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 02/28/2023] [Indexed: 04/11/2023] Open
Abstract
Introduction Accumulating evidence shows that epilepsy is a disease caused by brain network dysfunction. This study explored changes in brain network structure in epilepsy patients based on graph analysis of diffusion tensor imaging data. Methods The brain structure networks of 42 healthy control individuals and 26 epilepsy patients were constructed. Using graph theory analysis, global and local network topology parameters of the brain structure network were calculated, and changes in global and local characteristics of the brain network in epilepsy patients were quantitatively analyzed. Results Compared with the healthy control group, the epilepsy patient group showed lower global efficiency, local efficiency, clustering coefficient, and a longer shortest path length. Both healthy control individuals and epilepsy patients showed small-world attributes, with no significant difference between groups. The epilepsy patient group showed lower nodal local efficiency and nodal clustering coefficient in the right olfactory cortex and right rectus and lower nodal degree centrality in the right olfactory cortex and the left paracentral lobular compared with the healthy control group. In addition, the epilepsy patient group showed a smaller fiber number of edges in specific regions of the frontal lobe, temporal lobe, and default mode network, indicating reduced connection strength. Discussion Epilepsy patients exhibited lower global and local brain network properties as well as reduced white matter fiber connectivity in key brain regions. These findings further support the idea that epilepsy is a brain network disorder.
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Affiliation(s)
- Meixia Wang
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaoyu Cheng
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Qianru Shi
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Bo Xu
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaoxia Hou
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Huimin Zhao
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Qian Gui
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Guanhui Wu
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaofeng Dong
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Qinrong Xu
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Mingqiang Shen
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Qingzhang Cheng
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Shouru Xue
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Hongxuan Feng
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
- *Correspondence: Hongxuan Feng,
| | - Zhiliang Ding
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
- Zhiliang Ding,
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Yan R, Zhang H, Wang J, Zheng Y, Luo Z, Zhang X, Xu Z. Application value of molecular imaging technology in epilepsy. IBRAIN 2021; 7:200-210. [PMID: 37786793 PMCID: PMC10528966 DOI: 10.1002/j.2769-2795.2021.tb00084.x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/16/2021] [Accepted: 09/02/2021] [Indexed: 10/04/2023]
Abstract
Epilepsy is a common neurological disease with various seizure types, complicated etiologies, and unclear mechanisms. Its diagnosis mainly relies on clinical history, but an electroencephalogram is also a crucial auxiliary examination. Recently, brain imaging technology has gained increasing attention in the diagnosis of epilepsy, and conventional magnetic resonance imaging can detect epileptic foci in some patients with epilepsy. However, the results of brain magnetic resonance imaging are normal in some patients. New molecular imaging has gradually developed in recent years and has been applied in the diagnosis of epilepsy, leading to enhanced lesion detection rates. However, the application of these technologies in epilepsy patients with negative brain magnetic resonance must be clarified. Thus, we reviewed the relevant literature and summarized the information to improve the understanding of the molecular imaging application value of epilepsy.
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Affiliation(s)
- Rong Yan
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Hai‐Qing Zhang
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Jing Wang
- Prevention and Health Care, The Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Yong‐Su Zheng
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Zhong Luo
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Xia Zhang
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Zu‐Cai Xu
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
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Abstract
Epilepsy in infants and children is one of the most common and devastating neurological disorders. In the past, we had a limited understanding of the causes of epilepsy in pediatric patients, so we treated pediatric epilepsy according to seizure type. Now with new tools and tests, we are entering the age of precision medicine in pediatric epilepsy. In this review, we use the new etiological classification system proposed by the International League Against Epilepsy to review the advances in the diagnosis of pediatric epilepsy, describe new tools to identify seizure foci for epilepsy surgery, and define treatable epilepsy syndromes.
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Affiliation(s)
- Priya Sharma
- Department of Neurology, University of North Carolina School of Medicine, Physicians Office Building, Chapel Hill, NC, 27599-7025, USA
| | - Ammar Hussain
- Department of Neurology, University of North Carolina School of Medicine, Physicians Office Building, Chapel Hill, NC, 27599-7025, USA
| | - Robert Greenwood
- Department of Neurology & Pediatrics, University of North Carolina School of Medicine, 2141 Physicians Office Building, Chapel Hill, NC, 27599-7025, USA
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