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Hu L, Liu Y, Yuan Z, Guo H, Duan R, Ke P, Meng Y, Tian X, Xiao F. Glucose-6-phosphate dehydrogenase alleviates epileptic seizures by repressing reactive oxygen species production to promote signal transducer and activator of transcription 1-mediated N-methyl-d-aspartic acid receptors inhibition. Redox Biol 2024; 74:103236. [PMID: 38875958 PMCID: PMC11225908 DOI: 10.1016/j.redox.2024.103236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 06/07/2024] [Accepted: 06/07/2024] [Indexed: 06/16/2024] Open
Abstract
The pathogenesis of epilepsy remains unclear; however, a prevailing hypothesis suggests that the primary underlying cause is an imbalance between neuronal excitability and inhibition. Glucose-6-phosphate dehydrogenase (G6PD) is a key enzyme in the pentose phosphate pathway, which is primarily involved in deoxynucleic acid synthesis and antioxidant defense mechanisms and exhibits increased expression during the chronic phase of epilepsy, predominantly colocalizing with neurons. G6PD overexpression significantly reduces the frequency and duration of spontaneous recurrent seizures. Furthermore, G6PD overexpression enhances signal transducer and activator of transcription 1 (STAT1) expression, thus influencing N-methyl-d-aspartic acid receptors expression, and subsequently affecting seizure activity. Importantly, the regulation of STAT1 by G6PD appears to be mediated primarily through reactive oxygen species signaling pathways. Collectively, our findings highlight the pivotal role of G6PD in modulating epileptogenesis, and suggest its potential as a therapeutic target for epilepsy.
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Affiliation(s)
- Liqin Hu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Major Neurological and Mental Disorders, Chongqing Medical University, 1 Youyi Road, Chongqing, 400016, China
| | - Yan Liu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Major Neurological and Mental Disorders, Chongqing Medical University, 1 Youyi Road, Chongqing, 400016, China
| | - Ziwei Yuan
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Major Neurological and Mental Disorders, Chongqing Medical University, 1 Youyi Road, Chongqing, 400016, China
| | - Haokun Guo
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Major Neurological and Mental Disorders, Chongqing Medical University, 1 Youyi Road, Chongqing, 400016, China
| | - Ran Duan
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Major Neurological and Mental Disorders, Chongqing Medical University, 1 Youyi Road, Chongqing, 400016, China
| | - Pingyang Ke
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Major Neurological and Mental Disorders, Chongqing Medical University, 1 Youyi Road, Chongqing, 400016, China
| | - Yuan Meng
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Major Neurological and Mental Disorders, Chongqing Medical University, 1 Youyi Road, Chongqing, 400016, China
| | - Xin Tian
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Major Neurological and Mental Disorders, Chongqing Medical University, 1 Youyi Road, Chongqing, 400016, China; Key Laboratory of Major Brain Disease and Aging Research (Ministry of Education), Chongqing Medical University, Chongqing, 400016, China.
| | - Fei Xiao
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Major Neurological and Mental Disorders, Chongqing Medical University, 1 Youyi Road, Chongqing, 400016, China; Key Laboratory of Major Brain Disease and Aging Research (Ministry of Education), Chongqing Medical University, Chongqing, 400016, China.
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Wan X, Zeng Y, Wang J, Tian M, Yin X, Zhang J. Structural and functional abnormalities and cognitive profiles in older adults with early-onset and late-onset focal epilepsy. Cereb Cortex 2024; 34:bhae300. [PMID: 39052362 DOI: 10.1093/cercor/bhae300] [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: 03/10/2024] [Revised: 06/26/2024] [Accepted: 07/09/2024] [Indexed: 07/27/2024] Open
Abstract
This study aimed to determine the patterns of changes in structure, function, and cognitive ability in early-onset and late-onset older adults with focal epilepsy (OFE). This study first utilized the deformation-based morphometry analysis to identify structural abnormalities, which were used as the seed region to investigate the functional connectivity with the whole brain. Next, a correlation analysis was performed between the altered imaging findings and neuropsychiatry assessments. Finally, the potential role of structural-functional abnormalities in the diagnosis of epilepsy was further explored by using mediation analysis. Compared with healthy controls (n = 28), the area of reduced structural volume was concentrated in the bilateral cerebellum, right thalamus, and right middle cingulate cortex, with frontal, temporal, and occipital lobes also affected in early-onset focal epilepsy (n = 26), while late-onset patients (n = 31) displayed cerebellar, thalamic, and cingulate atrophy. Furthermore, correlation analyses suggest an association between structural abnormalities and cognitive assessments. Dysfunctional connectivity in the cerebellum, cingulate cortex, and frontal gyrus partially mediates the relationship between structural abnormalities and the diagnosis of early-onset focal epilepsy. This study identified structural and functional abnormalities in early-onset and late-onset focal epilepsy and explored characters in cognitive performance. Structural-functional coupling may play a potential role in the diagnosis of epilepsy.
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Affiliation(s)
- Xinyue Wan
- Department of Radiology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai 200040, China
- Human Phenome Institute, Fudan University, Shanghai 201203, China
| | - Yanwei Zeng
- Department of Radiology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai 200040, China
| | - Jianhong Wang
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai 201203, China
| | - Xuyang Yin
- Department of Radiology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai 200040, China
| | - Jun Zhang
- Department of Radiology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai 200040, China
- National Center for Neurological Disorders, Fudan University, Shanghai 200040, China
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Grayev A, Larson M. Advanced Imaging Techniques in Pediatric Seizure Disorders: White Matter Changes in Idiopathic Generalized Epilepsy. Acad Radiol 2024; 31:2942-2943. [PMID: 38777722 DOI: 10.1016/j.acra.2024.05.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 05/25/2024]
Affiliation(s)
- Allison Grayev
- University of Wisconsin School of Medicine and Public Health, Department of Radiology, Neuroradiology Section, 600 Highland Avenue, CSC E1/336, Madison, Wisconsin 53792, USA.
| | - Matthew Larson
- University of Wisconsin School of Medicine and Public Health, Department of Radiology, Neuroradiology Section, 600 Highland Avenue, CSC E1/336, Madison, Wisconsin 53792, USA
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Allendorfer JB, Nenert R, Goodman AM, Kakulamarri P, Correia S, Philip NS, LaFrance WC, Szaflarski JP. Brain network entropy, depression, and quality of life in people with traumatic brain injury and seizure disorders. Epilepsia Open 2024; 9:969-980. [PMID: 38507279 PMCID: PMC11145610 DOI: 10.1002/epi4.12926] [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: 05/26/2023] [Revised: 01/29/2024] [Accepted: 02/29/2024] [Indexed: 03/22/2024] Open
Abstract
OBJECTIVE Traumatic brain injury (TBI) often precedes the onset of epileptic (ES) or psychogenic nonepileptic seizures (PNES) with depression being a common comorbidity. The relationship between depression severity and quality of life (QOL) may be related to resting-state network complexity. We investigated these relationships in adults with TBI-only, TBI + ES, or TBI + PNES using Sample Entropy (SampEn), a measure of physiologic signals complexity. METHODS Adults with TBI-only (n = 60), TBI + ES (n = 21), or TBI + PNES (n = 56) completed the Beck Depression Inventory-II (BDI-II; depression symptom severity) and QOL in Epilepsy (QOLIE-31) assessments and underwent resting-state functional magnetic resonance imaging (rs-fMRI). SampEn values derived from six resting state functional networks were calculated per participant. Effects of group, network, and group-by-network-interactions for SampEn were investigated with a mixed-effects model. We examined relationships between BDI-II, QOL, and SampEn of each of the networks. RESULTS Groups did not differ in age, but there was a higher proportion of women with TBI + PNES (p = 0.040). TBI + ES and TBI-only groups did not differ in BDI-II or QOLIE-31 scores, while the TBI + PNES group scored worse on both measures. The fixed effects of the model revealed significant differences in SampEn values across networks (lower SampEn for the frontoparietal network compared to other networks). The likelihood ratio test for group-by-network-interactions was significant (p = 0.033). BDI-II was significantly negatively associated with Overall QOL scale scores in all groups, and significantly negatively associated with network SampEn values only in the TBI + PNES group. SIGNIFICANCE Only TBI + PNES had significant relationships between depression symptom severity and network SampEn values indicating that the resting state network complexity is related to depression severity in this group but not in TBI + ES or TBI-only. PLAIN LANGUAGE SUMMARY The brain has a complex network of internal connections. How well these connections work may be affected by TBI and seizures and may underlie mental health symptoms including depression; the worse the depression, the worse the quality of life. Our study compared brain organization in people with TBI, people with epilepsy after TBI, and people with nonepileptic seizures after TBI. Only people with nonepileptic seizures after TBI showed a relationship between how organized their brain connections were and how bad was their depression. We need to better understand these relationships to develop more impactful, effective treatments.
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Affiliation(s)
- Jane B. Allendorfer
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- Department of NeurobiologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- UAB Epilepsy CenterUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Rodolphe Nenert
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Adam M. Goodman
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- UAB Epilepsy CenterUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Pranav Kakulamarri
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Stephen Correia
- VA RR&D Center for Neurorestoration and NeurotechnologyVA Providence Healthcare SystemProvidenceRhode IslandUSA
| | - Noah S. Philip
- VA RR&D Center for Neurorestoration and NeurotechnologyVA Providence Healthcare SystemProvidenceRhode IslandUSA
- Department of Psychiatry and Human BehaviorBrown UniversityProvidenceRhode IslandUSA
| | - W. Curt LaFrance
- VA RR&D Center for Neurorestoration and NeurotechnologyVA Providence Healthcare SystemProvidenceRhode IslandUSA
- Department of Psychiatry and Human BehaviorBrown UniversityProvidenceRhode IslandUSA
- Department of NeurologyBrown UniversityProvidenceRhode IslandUSA
- Division of Neuropsychiatry and Behavioral NeurologyRhode Island HospitalProvidenceRhode IslandUSA
| | - Jerzy P. Szaflarski
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- Department of NeurobiologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- UAB Epilepsy CenterUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- Department of NeurosurgeryUniversity of Alabama at BirminghamBirminghamAlabamaUSA
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5
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Iqbal MS, Belal Bin Heyat M, Parveen S, Ammar Bin Hayat M, Roshanzamir M, Alizadehsani R, Akhtar F, Sayeed E, Hussain S, Hussein HS, Sawan M. Progress and trends in neurological disorders research based on deep learning. Comput Med Imaging Graph 2024; 116:102400. [PMID: 38851079 DOI: 10.1016/j.compmedimag.2024.102400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 05/07/2024] [Accepted: 05/13/2024] [Indexed: 06/10/2024]
Abstract
In recent years, deep learning (DL) has emerged as a powerful tool in clinical imaging, offering unprecedented opportunities for the diagnosis and treatment of neurological disorders (NDs). This comprehensive review explores the multifaceted role of DL techniques in leveraging vast datasets to advance our understanding of NDs and improve clinical outcomes. Beginning with a systematic literature review, we delve into the utilization of DL, particularly focusing on multimodal neuroimaging data analysis-a domain that has witnessed rapid progress and garnered significant scientific interest. Our study categorizes and critically analyses numerous DL models, including Convolutional Neural Networks (CNNs), LSTM-CNN, GAN, and VGG, to understand their performance across different types of Neurology Diseases. Through particular analysis, we identify key benchmarks and datasets utilized in training and testing DL models, shedding light on the challenges and opportunities in clinical neuroimaging research. Moreover, we discuss the effectiveness of DL in real-world clinical scenarios, emphasizing its potential to revolutionize ND diagnosis and therapy. By synthesizing existing literature and describing future directions, this review not only provides insights into the current state of DL applications in ND analysis but also covers the way for the development of more efficient and accessible DL techniques. Finally, our findings underscore the transformative impact of DL in reshaping the landscape of clinical neuroimaging, offering hope for enhanced patient care and groundbreaking discoveries in the field of neurology. This review paper is beneficial for neuropathologists and new researchers in this field.
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Affiliation(s)
- Muhammad Shahid Iqbal
- Department of Computer Science and Information Technology, Women University of Azad Jammu & Kashmir, Bagh, Pakistan.
| | - Md Belal Bin Heyat
- CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, Zhejiang, China.
| | - Saba Parveen
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen 518060, China.
| | | | - Mohamad Roshanzamir
- Department of Computer Engineering, Faculty of Engineering, Fasa University, Fasa, Iran.
| | - Roohallah Alizadehsani
- Institute for Intelligent Systems Research and Innovation, Deakin University, VIC 3216, Australia.
| | - Faijan Akhtar
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.
| | - Eram Sayeed
- Kisan Inter College, Dhaurahara, Kushinagar, India.
| | - Sadiq Hussain
- Department of Examination, Dibrugarh University, Assam 786004, India.
| | - Hany S Hussein
- Electrical Engineering Department, Faculty of Engineering, King Khalid University, Abha 61411, Saudi Arabia; Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan 81528, Egypt.
| | - Mohamad Sawan
- CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, Zhejiang, China.
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Desale P, Dhande R, Parihar P, Nimodia D, Bhangale PN, Shinde D. Navigating Neural Landscapes: A Comprehensive Review of Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) Applications in Epilepsy. Cureus 2024; 16:e56927. [PMID: 38665706 PMCID: PMC11043648 DOI: 10.7759/cureus.56927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/25/2024] [Indexed: 04/28/2024] Open
Abstract
This review comprehensively explores the evolving role of neuroimaging, specifically magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS), in epilepsy research and clinical practice. Beginning with a concise overview of epilepsy, the discussion emphasizes the crucial importance of neuroimaging in diagnosing and managing this complex neurological disorder. The review delves into the applications of advanced MRI techniques, including high-field MRI, resting-state fMRI, and connectomics, highlighting their impact on refining our understanding of epilepsy's structural and functional dimensions. Additionally, it examines the integration of machine learning in the analysis of intricate neuroimaging data. Moving to the clinical domain, the review outlines the utility of neuroimaging in pre-surgical evaluations and the monitoring of treatment responses and disease progression. Despite significant strides, challenges and limitations are discussed in the routine clinical incorporation of neuroimaging. The review explores promising developments in MRI and MRS technology, potential advancements in imaging biomarkers, and the implications for personalized medicine in epilepsy management. The conclusion underscores the transformative potential of neuroimaging and advocates for continued exploration, collaboration, and technological innovation to propel the field toward a future where tailored, effective interventions improve outcomes for individuals with epilepsy.
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Affiliation(s)
- Prasad Desale
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Rajasbala Dhande
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Pratapsingh Parihar
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Devyansh Nimodia
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Paritosh N Bhangale
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Dhanajay Shinde
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
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Li Y, Ran Y, Yao M, Chen Q. Altered static and dynamic functional connectivity of the default mode network across epilepsy subtypes in children: A resting-state fMRI study. Neurobiol Dis 2024; 192:106425. [PMID: 38296113 DOI: 10.1016/j.nbd.2024.106425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 01/08/2024] [Accepted: 01/27/2024] [Indexed: 02/04/2024] Open
Abstract
BACKGROUND Epilepsy is a chronic neurologic disorder characterized by abnormal functioning of brain networks, making it a complex research topic. Recent advancements in neuroimaging technology offer an effective approach to unraveling the intricacies of the human brain. Within different types of epilepsy, there is growing recognition regarding ongoing changes in the default mode network (DMN). However, little is known about the shared and distinct alterations of static functional connectivity (sFC) and dynamic functional connectivity (dFC) in DMN among epileptic subtypes, especially in children with epilepsy. METHODS Here, 110 children with epilepsy at a single center, including idiopathic generalized epilepsy (IGE), frontal lobe epilepsy (FLE), temporal lobe epilepsy (TLE), and parietal lobe epilepsy (PLE), as well as 84 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (fMRI) scan. We investigated both sFC and dFC between groups of the DMN. RESULTS Decreased static and dynamic connectivity within the DMN subsystem were shared by all subtypes. In each epilepsy subtype, children with epilepsy displayed significant and distinct patterns of DMN connectivity compared to the control group: the IGE group showed reduced interhemispheric connectivity, the FLE group consistently demonstrated disturbances in frontal region connectivity, the TLE group exhibited significant disruptions in hippocampal connectivity, and the PLE group displayed a notable decrease in parietal-temporal connectivity within the DMN. Some state-specific FC disruptions (decreased dFC) were observed in each epilepsy subtype that cannot detect by sFC. To determine their uniqueness within specific subtypes, bootstrapping methods were employed and found the significant results (IGE: between PCC and bilateral precuneus, FLE: between right middle frontal gyrus and bilateral middle temporal gyrus, TLE: between left Hippocampus and right fusiform, PLE: between left angular and cingulate cortex). Furthermore, only children with IGE exhibited dynamic features associated with clinical variables. CONCLUSIONS Our findings highlight both shared and distinct FC alterations within the DMN in children with different types of epilepsy. Furthermore, our work provides a novel perspective on the functional alterations in the DMN of pediatric patients, suggesting that combined sFC and dFC analysis can provide valuable insights for deepening our understanding of the neuronal mechanism underlying epilepsy in children.
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Affiliation(s)
- Yongxin Li
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
| | - Yun Ran
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
| | - Maohua Yao
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
| | - Qian Chen
- Department of Pediatric Neurosurgery, Shenzhen Children's Hospital, Shenzhen, China
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Karpychev V, Malyutina S, Zhuravleva A, Bronov O, Kuzin V, Marinets A, Dragoy O. Disruptions in modular structure and network integration of language-related network predict language performance in temporal lobe epilepsy: Evidence from graph-based analysis. Epilepsy Behav 2023; 147:109407. [PMID: 37688840 DOI: 10.1016/j.yebeh.2023.109407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/03/2023] [Accepted: 08/19/2023] [Indexed: 09/11/2023]
Abstract
OBJECTIVE Temporal lobe epilepsy (TLE) is a network disorder that alters the total organization of the language-related network. Task-based functional magnetic resonance imaging (fMRI) aimed at functional connectivity is a direct method to investigate how the network is reorganized. However, such studies are scarce and represented mostly by the resting-state analysis of the individual connections between regions. To fill this gap, we used a graph-based analysis, which allows us to cover the total language-related network changes, such as disruptions in an integration/segregation balance, during a language task in TLE. METHODS We collected task-based fMRI data with sentence completion from 19 healthy controls and 28 people with left TLE. Using graph-based analysis, we estimated how the language-related network segregated into modules and tested whether they differed between groups. We evaluated the total network integration and the integration within modules. To assess intermodular integration, we considered the number and location of connector hubs-regions with high connectivity. RESULTS The language-related network was differently segregated during language processing in the groups. While healthy controls showed a module consisting of left perisylvian regions, people with TLE exhibited a bilateral module formed by the anterior language-related areas and a module in the left temporal lobe, reflecting hyperconnectivity within the epileptic focus. As a consequence of this reorganization, there was a statistical tendency that the dominance of the intramodular integration over the total network integration was greater in TLE, which predicted language performance. The increase in the number of connector hubs in the right hemisphere, in turn, was compensatory in TLE. SIGNIFICANCE Our study provides insights into the reorganization of the language-related network in TLE, revealing specific network changes in segregation and integration. It confirms reduced global connectivity and compensation across the healthy hemisphere, commonly observed in epilepsy. These findings advance the understanding of the network-based reorganizational processes underlying language processing in TLE.
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Affiliation(s)
- Victor Karpychev
- Center for Language and Brain, HSE University, Moscow, Russian Federation.
| | - Svetlana Malyutina
- Center for Language and Brain, HSE University, Moscow, Russian Federation
| | - Anna Zhuravleva
- Center for Language and Brain, HSE University, Moscow, Russian Federation
| | - Oleg Bronov
- National Medical and Surgical Center named after N.I. Pirogov, Moscow, Russian Federation
| | - Vasiliy Kuzin
- National Medical and Surgical Center named after N.I. Pirogov, Moscow, Russian Federation
| | - Aleksei Marinets
- National Medical and Surgical Center named after N.I. Pirogov, Moscow, Russian Federation
| | - Olga Dragoy
- Center for Language and Brain, HSE University, Moscow, Russian Federation; Institute of Linguistics, Russian Academy of Sciences, Moscow, Russian Federation
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Dorji T, Yangchen, Wangmo S, Tenzin K, Jamtsho S, Pema D, Chhetri B, Nirola DK, Dhakal GP. Challenges in epilepsy diagnosis and management in a low-resource setting: An experience from Bhutan. Epilepsy Res 2023; 192:107126. [PMID: 36965308 DOI: 10.1016/j.eplepsyres.2023.107126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 02/09/2023] [Accepted: 03/13/2023] [Indexed: 03/18/2023]
Abstract
Epilepsy is an important cause of morbidity and mortality especially in low- and middle-income countries. People with epilepsy (PWE) face difficulties in access to healthcare, appropriate diagnostic tests and anti-seizure medications (ASM). Bhutan is one such country in the Himalayas that has reported doubling of the prevalence of epilepsy from 155.7 per 100,000 population in 2017 to 312.4 in 2021. The country has one centre for electroencephalography and magnetic resonance imaging for a population of 0.7 million and does not have any neurologists as of 2023. There are 16 ASMs registered in the country but only selected medications are available at the primary level hospitals (phenobarbital, phenytoin and diazepam). There are challenges in the availability of these medicines all time round the year in all levels of hospitals. Neurosurgical treatment options are limited by the lack of adequate pre-surgical evaluation facilities and lack of trained human resources. The majority of PWE have reported facing societal stigma with significant impact on the overall quality of life. It is important to screen for psychiatric comorbidities and provide psychological support wherever possible. There is a need for a comprehensive national guideline that will cater to the needs of PWE and their caregivers within the resources available in the country. A special focus on the institutional and human resource capacity development for the study and care of epilepsy is recommended.
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Affiliation(s)
- Thinley Dorji
- Department of Internal Medicine, Central Regional Referral Hospital, Gelegphu, Bhutan.
| | - Yangchen
- Department of Internal Medicine, Jigme Dorji Wangchuck National Referral Hospital, Thimphu, Bhutan
| | | | - Karma Tenzin
- Faculty of Postgraduate Medicine, Khesar Gyalpo University of Medical Sciences of Bhutan, Thimphu, Bhutan
| | - Sonam Jamtsho
- Department of Surgery, Jigme Dorji Wangchuck National Referral Hospital, Thimphu, Bhutan
| | - Dechen Pema
- Department of Radiodiagnosis and Imaging, Central Regional Referral Hospital, Gelegphu, Bhutan
| | - Bikram Chhetri
- Department of Psychiatry, Jigme Dorji Wangchuck National Referral Hospital, Thimphu, Bhutan
| | - Damber Kumar Nirola
- Department of Psychiatry, Jigme Dorji Wangchuck National Referral Hospital, Thimphu, Bhutan
| | - Guru Prasad Dhakal
- Department of Internal Medicine, Jigme Dorji Wangchuck National Referral Hospital, Thimphu, Bhutan; Faculty of Postgraduate Medicine, Khesar Gyalpo University of Medical Sciences of Bhutan, Thimphu, Bhutan
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10
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Reda AM, Elsharkawy A, Hasby SE. Usefulness of combined diffusion tensor imaging, arterial spin labelling and spectroscopic interictal analysis in refractory epilepsy. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2023. [DOI: 10.1186/s43055-023-00988-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2023] Open
Abstract
Abstract
Background
Epilepsy is a common neurological disorder especially in pediatric population. Patients with non-lesional epilepsy have normal conventional MRI findings. In the recent era of advances in neuroimaging studies, diffusion tensor imaging (DTI) and MR spectroscopy (MRS) can assess the tissue microstructure. Also, arterial spin labeling (ASL) is a noninvasive modality that evaluates cerebral blood flow. Multiple recent publications aimed at use of single or two new modalities in lateralization of epileptogenic focus in epilepsy, but the current study aimed to evaluate the added value of combined (DTI, ASL and MRS) in vivo localization of interactable epilepsy with negative conventional MRI findings.
Results
This prospective case control study was carried out in the period from January 1st, 2022 to October 1st, 2022 after approval of local ethical committee in our institution. Written informed consent was obtained from patients and healthy volunteers who were enrolled in this study. The current study included 46 patients with temporal lobe epilepsy and 20 age- and sex-matched healthy volunteers as a control group. The mean age in the patient group was 22.3 ± 12.2 years, and in the control group, it was 23.8 ± 15.1 years. The highest area under the curve (AUC) was for spectroscopy (0.913), the difference in NAA/Cr showed sensitivity of 94.1% and a specificity of 90%, while NAA/Cho + Cr showed a sensitivity of 91.8% and a specificity of 88%, the difference in rCBF showed an AUC of 0.89, with a cutoff value of 3.815 had a sensitivity of 80.4% and a specificity of 85%. As regards DTI, the changes in DTI parameters show sensitivity of 79.6% and a specificity of 80% in lateralization of the epileptic focus. The difference in FA only showed an AUC of 0.86, with a cutoff value of 0.01 had a sensitivity of 77% and a specificity of 75% and the difference in MD only showed an AUC of 0.771, with a cutoff value of 0.545 had a sensitivity of 67.4% and a specificity of 70%. The diagnostic performance of MRS in terms of the AUC was significantly higher than ASL parameters (difference in NAA/Cr, p = 0.033 and difference in NAA/Cho + Cr, p = 0.044), and MD (p = 0.02). No other statistically significant differences were shown between the studied parameters. When the three methods were combined, all patients’ epileptogenic foci were correctly localized and lateralized.
Conclusions
Combining ASL, DTI and H-MRS provided excellent diagnostic performance in localization and lateralization of the epileptogenic focus. If this combination is not applicable in clinical practice, ASL could provide a considerably accurate and feasible method in this context. The present study supported the value of the new noninvasive MRI techniques in the elaboration of hidden brain pathology.
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Kang K, Sathe A, Mandloi S, Muller J, Ozuna GAG, Franco D, Miller C, Sharan A, Mohamed FB, Faro S, Alizadeh M, Wu C. Evaluation of eight registration algorithms applied to the insula and insular gyri. J Neuroimaging 2023; 33:446-454. [PMID: 36813464 DOI: 10.1111/jon.13091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 02/01/2023] [Accepted: 02/07/2023] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND AND PURPOSE Spatial registration is crucial in establishing correspondence between anatomic brain regions for research and clinical purposes. The insular cortex (IC) and gyri (IG) are implicated in various functions and pathologies including epilepsy. Optimizing registration of the insula to a common atlas can improve the accuracy of group-level analyses. Here, we compared six nonlinear, one linear, and one semiautomated registration algorithms (RAs) for registering the IC and IG to the Montreal Neurologic Institute standard space (MNI152). METHODS 3T images acquired from 20 controls and 20 temporal lobe epilepsy patients with mesial temporal sclerosis underwent automated segmentation of the insula. This was followed by manual segmentation of the entire IC and six individual IGs. Consensus segmentations were created at 75% agreement for IC and IG before undergoing registration to MNI152 space with eight RAs. Dice similarity coefficients (DSCs) were calculated between segmentations after registration and the IC and IG in MNI152 space. Statistical analysis involved the Kruskal-Wallace test with Dunn's test for IC and two-way analysis of variance with Tukey's honest significant difference test for IG. RESULTS DSCs were significantly different between RAs. Based on multiple pairwise comparisons, we report that certain RAs performed better than others across population groups. Additionally, registration performance differed according to specific IG. CONCLUSION We compared different methods for registering the IC and IG to MNI152 space. We found differences in performance between RAs, which suggests that algorithm choice is important factor in analyses involving the insula.
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Affiliation(s)
- KiChang Kang
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Anish Sathe
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Shreya Mandloi
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Jennifer Muller
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Glenn Arturo Gonzalez Ozuna
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Daniel Franco
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Christopher Miller
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Ashwini Sharan
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Feroze B Mohamed
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Scott Faro
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Mahdi Alizadeh
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.,Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Chengyuan Wu
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.,Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
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12
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Goodman AM, Kakulamarri P, Nenert R, Allendorfer JB, Philip NS, Correia S, LaFrance WC, Szaflarski JP. Relationship between intrinsic network connectivity and psychiatric symptom severity in functional seizures. J Neurol Neurosurg Psychiatry 2023; 94:136-143. [PMID: 36302640 DOI: 10.1136/jnnp-2022-329838] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 10/11/2022] [Indexed: 01/12/2023]
Abstract
BACKGROUND Traumatic brain injury (TBI) may precipitate the onset of functional seizures (FSs). Many patients with FS report at least one prior TBI, and these patients typically present with more severe psychiatric comorbidities. TBI and psychopathology are linked to changes in neural network connectivity, but their combined effects on these networks and relationship to the effects of FS remain unclear. We hypothesised that resting-state functional connectivity (rsFC) would differ between patients with FS and TBI (FS+TBI) compared with TBI without FS (TBI only), with variability only partially explained by the presence of psychopathology. METHODS Patients with FS+TBI (n=52) and TBI only (n=54) were matched for age and sex. All participants completed psychiatric assessments prior to resting-state functional MRI at 3 T. Independent component analysis identified five canonical rsFC networks related to emotion and motor functions. RESULTS Five linear mixed-effects analyses identified clusters of connectivity coefficients that differed between groups within the posterior cingulate of the default mode network, insula and supramarginal gyrus of the executive control network and bilateral anterior cingulate of the salience network (all α=0.05, corrected). Cluster signal extractions revealed decreased contributions to each network for FS+TBI compared to TBI only. Planned secondary analyses demonstrated correlations between signal and severity of mood, anxiety, somatisation and global functioning symptoms. CONCLUSIONS These findings indicate the presence of aberrant connectivity in FS and extend the biopsychosocial network model by demonstrating that common aetiology is linked to both FS and comorbidities, but the overlap in affected networks varies by comorbid symptoms.
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Affiliation(s)
- Adam M Goodman
- Neurology, The University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Pranav Kakulamarri
- Neurology, The University of Alabama at Birmingham, Birmingham, Alabama, USA.,Psychology, The University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Rodolphe Nenert
- Neurology, The University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Jane B Allendorfer
- Neurology, The University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Noah S Philip
- RR&D Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, Rhode Island, USA.,Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Stephen Correia
- RR&D Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, Rhode Island, USA.,Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - W Curt LaFrance
- RR&D Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, Rhode Island, USA.,Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.,Neurology, Alpert Medical School of Brown University, Providence, RI, USA.,Division of Neuropsychiatry and Behavioral Neurology, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Jerzy P Szaflarski
- Neurology, The University of Alabama at Birmingham, Birmingham, Alabama, USA
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Wang Y, Li Y, Yang L, Huang W. Altered topological organization of resting-state functional networks in children with infantile spasms. Front Neurosci 2022; 16:952940. [PMID: 36248635 PMCID: PMC9562010 DOI: 10.3389/fnins.2022.952940] [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: 05/25/2022] [Accepted: 09/14/2022] [Indexed: 11/15/2022] Open
Abstract
Covering neuroimaging evidence has demonstrated that epileptic symptoms are associated with the disrupted topological architecture of the brain network. Infantile spasms (IS) as an age-specific epileptic encephalopathy also showed abnormal structural or functional connectivity in specific brain regions or specific networks. However, little is known about the topological alterations of whole-brain functional networks in patients with IS. To fill this gap, we used the graph theoretical analysis to investigate the topological properties (whole-brain small-world property and modular interaction) in 17 patients with IS and 34 age- and gender-matched healthy controls. The functional networks in both groups showed efficient small-world architecture over the sparsity range from 0.05 to 0.4. While patients with IS showed abnormal global properties characterized by significantly decreased normalized clustering coefficient, normalized path length, small-worldness, local efficiency, and significantly increased global efficiency, implying a shift toward a randomized network. Modular analysis revealed decreased intra-modular connectivity within the default mode network (DMN) and fronto-parietal network but increased inter-modular connectivity between the cingulo-opercular network and occipital network. Moreover, the decreased intra-modular connectivity in DMN was significantly negatively correlated with seizure frequency. The inter-modular connectivity between the cingulo-opercular and occipital network also showed a significant correlation with epilepsy frequency. Together, the current study revealed the disrupted topological organization of the whole-brain functional network, which greatly advances our understanding of neuronal architecture in IS and may contribute to predict the prognosis of IS as disease biomarkers.
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Affiliation(s)
- Ya Wang
- School of Basic Medical Sciences, Engineering Research Center for Translation of Medical 3D Printing Application, Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics, National Key Discipline of Human Anatomy, Southern Medical University, Guangzhou, China
| | - Yongxin Li
- Formula-Pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
- *Correspondence: Yongxin Li,
| | - Lin Yang
- Department of Anesthesiology, The Fifth Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Wenhua Huang
- School of Basic Medical Sciences, Engineering Research Center for Translation of Medical 3D Printing Application, Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics, National Key Discipline of Human Anatomy, Southern Medical University, Guangzhou, China
- Wenhua Huang,
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14
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Epilepsy in Pediatric Patients—Evaluation of Brain Structures’ Volume Using VolBrain Software. J Clin Med 2022; 11:jcm11164657. [PMID: 36012894 PMCID: PMC9409991 DOI: 10.3390/jcm11164657] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/19/2022] [Accepted: 08/05/2022] [Indexed: 11/17/2022] Open
Abstract
Epilepsy is one of the most frequent serious brain disorders. Approximately 30,000 of the 150,000 children and adolescents who experience unprovoked seizures are diagnosed with epilepsy each year. Magnetic resonance imaging is the method of choice in diagnosing and monitoring patients with this condition. However, one very effective tool using MR images is volBrain software, which automatically generates information about the volume of brain structures. A total of 57 consecutive patients (study group) suffering from epilepsy and 34 healthy patients (control group) who underwent MR examination qualified for the study. Images were then evaluated by volBrain. Results showed atrophy of the brain and particular structures—GM, cerebrum, cerebellum, brainstem, putamen, thalamus, hippocampus and nucleus accumbens volume. Moreover, the statistically significant difference in the volume between the study and the control group was found for brain, lateral ventricle and putamen. A volumetric analysis of the CNS in children with epilepsy confirms a decrease in the volume of brain tissue. A volumetric assessment of brain structures based on MR data has the potential to be a useful diagnostic tool in children with epilepsy and can be implemented in clinical work; however, further studies are necessary to enhance the effectiveness of this software.
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Li Y, Wang J, Wang X, Chen Q, Qin B, Chen J. Reconfiguration of static and dynamic thalamo-cortical network functional connectivity of epileptic children with generalized tonic-clonic seizures. Front Neurosci 2022; 16:953356. [PMID: 35937891 PMCID: PMC9353948 DOI: 10.3389/fnins.2022.953356] [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: 05/26/2022] [Accepted: 06/24/2022] [Indexed: 12/05/2022] Open
Abstract
Objective A number of studies in adults and children with generalized tonic-clonic seizure (GTCS) have reported the alterations in morphometry, functional activity, and functional connectivity (FC) in the thalamus. However, the neural mechanisms underlying the alterations in the thalamus of patients with GTCS are not well understood, particularly in children. The aim of the current study was to explore the temporal properties of functional pathways connecting thalamus in children with GTCS. Methods Here, we recruited 24 children with GTCS and 36 age-matched healthy controls. Static and dynamic FC approaches were used to evaluate alterations in the temporal variability of thalamo-cortical networks in children with GTCS. The dynamic effective connectivity (dEC) method was also used to evaluate the directions of the fluctuations in effective connectivity. In addition, the relationships between the dynamic properties and clinical features were assessed. Results The static FC analysis presented significantly decreased connectivity patterns between the bilateral thalamus and between the thalamus and right inferior temporal gyrus. The dynamic connectivity analysis found decreased FC variability in the thalamo-cortical network of children with epilepsy. Dynamic EC analyses identified increased connectivity variability from the frontal gyrus to the bilateral thalamus, and decreased connectivity variability from the right thalamus to the left thalamus and from the right thalamus to the right superior parietal lobe. In addition, correlation analysis revealed that both static FC and connectivity temporal variability in the thalamo-cortical network related to the clinical features (epilepsy duration and epilepsy onset time). Significance Our findings of both increased and decreased connectivity variability in the thalamo-cortical network imply a dynamic restructuring of the functional pathways connecting the thalamus in children with GTCS. These alterations in static and temporal dynamic pathways connecting the bilateral thalamus may extend our understanding of the neural mechanisms underlying the GTCS in children.
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Affiliation(s)
- Yongxin Li
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
- *Correspondence: Yongxin Li,
| | - Jianping Wang
- The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiao Wang
- Epilepsy Center and Department of Neurosurgery, The First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Qian Chen
- Department of Pediatric Neurosurgery, Shenzhen Children’s Hospital, Shenzhen, China
| | - Bing Qin
- Epilepsy Center and Department of Neurosurgery, The First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Jiaxu Chen
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
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16
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Li Y, Qin B, Chen Q, Chen J. Altered dynamic functional network connectivity within default mode network of epileptic children with generalized tonic-clonic seizures. Epilepsy Res 2022; 184:106969. [PMID: 35738202 DOI: 10.1016/j.eplepsyres.2022.106969] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/13/2022] [Accepted: 06/14/2022] [Indexed: 11/24/2022]
Abstract
OBJECTIVE Generalized tonic-clonic seizures (GTCS) is a group of epileptic disorders characterized by widespread generalized spike-and-waves discharges along with unresponsiveness and convulsions. Abnormal connectivity in the DMN is the common findings in children with generalized epilepsy. However, the neural mechanisms underlying the altered brain connectivity of DMN in children with GTCS remain unclear. The aim of the current study was to explore the temporal properties of functional connectivity states by dynamic functional connectivity (dFC) within the DMN of GTCS children. METHODS We collected resting-state functional MRI data from 22 GTCS children and 29 age-matched healthy controls. Sliding window approach and k-mean clustering analysis were applied to analyze the dFC and identify transient states of the DMN. Furthermore, the relationship between the dynamic properties and clinical features was assessed. RESULTS The dFC analyses identified two reoccurring states: a more frequent and weak connected state (State 1) and a less frequent and strong connected state (State 2). Relative to the normal control, GTCS children spent more time in State 1 showing weak connections and spent less time in State 2 showing strong connections. Dynamic functional network connectivity strength within the DMN showed both increase and decrease in patient group. In addition, the changes of dynamic metric were found to be correlated with epilepsy duration. SIGNIFICANT Our findings imply abnormal interactions and the state dynamics in DMN of the children with GTCS. These disruptions of temporal dynamic in DMN may provide significance for understanding the neural mechanism underlying the GTCS in children and suggest that dFC method can be considered as a valuable tool in children with epilepsy.
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Affiliation(s)
- Yongxin Li
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
| | - Bing Qin
- Epilepsy Center and Department of Neurosurgery, The First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Qian Chen
- Department of Pediatric Neurosurgery, Shenzhen Children's Hospital, Shenzhen, China
| | - Jiaxu Chen
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
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17
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Li Y, Qin B, Chen Q, Chen J. Impaired Functional Homotopy and Topological Properties Within the Default Mode Network of Children With Generalized Tonic-Clonic Seizures: A Resting-State fMRI Study. Front Neurosci 2022; 16:833837. [PMID: 35720710 PMCID: PMC9201640 DOI: 10.3389/fnins.2022.833837] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 04/27/2022] [Indexed: 12/02/2022] Open
Abstract
Introduction The aim of the present study was to examine interhemispheric functional connectivity (FC) and topological organization within the default-mode network (DMN) in children with generalized tonic-clonic seizures (GTCS). Methods Resting-state functional MRI was collected in 24 children with GTCS and 34 age-matched typically developing children (TDC). Between-group differences in interhemispheric FC were examined by an automated voxel-mirrored homotopic connectivity (VMHC) method. The topological properties within the DMN were also analyzed using graph theoretical approaches. Consistent results were detected and the VMHC values were extracted as features in machine learning for subject classification. Results Children with GTCS showed a significant decrease in VMHC in the DMN, including the hippocampal formation (HF), lateral temporal cortex (LTC), and angular and middle frontal gyrus. Although the patients exhibited efficient small-world properties of the DMN similar to the TDC, significant changes in regional topological organization were found in the patients, involving the areas of the bilateral temporal parietal junction, bilateral LTC, left temporal pole, and HF. Within the DMN, disrupted interhemispheric FC was found between the bilateral HF and LTC, which was consistent with the VMHC results. The VMHC values in bilateral HF and LTC were significantly correlated with clinical information in patients. Support vector machine analysis using average VMHC information in the bilateral HF and LTC as features achieved a correct classification rate of 89.34% for the classification. Conclusion These results indicate that decreased homotopic coordination in the DMN can be used as an effective biomarker to reflect seizure effects and to distinguish children with GTCSs from TDC.
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Affiliation(s)
- Yongxin Li
- Formula-Pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
- *Correspondence: Yongxin Li,
| | - Bing Qin
- Department of Neurosurgery, Epilepsy Center, The First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Qian Chen
- Department of Pediatric Neurosurgery, Shenzhen Children’s Hospital, Shenzhen, China
- Qian Chen,
| | - Jiaxu Chen
- Formula-Pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
- Jiaxu Chen,
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Vetkas A, Germann J, Elias G, Loh A, Boutet A, Yamamoto K, Sarica C, Samuel N, Milano V, Fomenko A, Santyr B, Tasserie J, Gwun D, Jung HH, Valiante T, Ibrahim GM, Wennberg R, Kalia SK, Lozano AM. Identifying the neural network for neuromodulation in epilepsy through connectomics and graphs. Brain Commun 2022; 4:fcac092. [PMID: 35611305 PMCID: PMC9123846 DOI: 10.1093/braincomms/fcac092] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 12/13/2021] [Accepted: 03/31/2022] [Indexed: 02/01/2023] Open
Abstract
Deep brain stimulation is a treatment option for patients with drug-resistant epilepsy. The precise mechanism of neuromodulation in epilepsy is unknown, and biomarkers are needed for optimizing treatment. The aim of this study was to describe the neural network associated with deep brain stimulation targets for epilepsy and to explore its potential application as a novel biomarker for neuromodulation. Using seed-to-voxel functional connectivity maps, weighted by seizure outcomes, brain areas associated with stimulation were identified in normative resting state functional scans of 1000 individuals. To pinpoint specific regions in the normative epilepsy deep brain stimulation network, we examined overlapping areas of functional connectivity between the anterior thalamic nucleus, centromedian thalamic nucleus, hippocampus and less studied epilepsy deep brain stimulation targets. Graph network analysis was used to describe the relationship between regions in the identified network. Furthermore, we examined the associations of the epilepsy deep brain stimulation network with disease pathophysiology, canonical resting state networks and findings from a systematic review of resting state functional MRI studies in epilepsy deep brain stimulation patients. Cortical nodes identified in the normative epilepsy deep brain stimulation network were in the anterior and posterior cingulate, medial frontal and sensorimotor cortices, frontal operculum and bilateral insulae. Subcortical nodes of the network were in the basal ganglia, mesencephalon, basal forebrain and cerebellum. Anterior thalamic nucleus was identified as a central hub in the network with the highest betweenness and closeness values, while centromedian thalamic nucleus and hippocampus showed average centrality values. The caudate nucleus and mammillothalamic tract also displayed high centrality values. The anterior cingulate cortex was identified as an important cortical hub associated with the effect of deep brain stimulation in epilepsy. The neural network of deep brain stimulation targets shared hubs with known epileptic networks and brain regions involved in seizure propagation and generalization. Two cortical clusters identified in the epilepsy deep brain stimulation network included regions corresponding to resting state networks, mainly the default mode and salience networks. Our results were concordant with findings from a systematic review of resting state functional MRI studies in patients with deep brain stimulation for epilepsy. Our findings suggest that the various epilepsy deep brain stimulation targets share a common cortico-subcortical network, which might in part underpin the antiseizure effects of stimulation. Interindividual differences in this network functional connectivity could potentially be used as biomarkers in selection of patients, stimulation parameters and neuromodulation targets.
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Affiliation(s)
- Artur Vetkas
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Neurology clinic, Department of Neurosurgery, Tartu University Hospital, University of Tartu, Tartu, Estonia
| | - Jürgen Germann
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Gavin Elias
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Aaron Loh
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Alexandre Boutet
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Joint Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - Kazuaki Yamamoto
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Can Sarica
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Nardin Samuel
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Vanessa Milano
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Anton Fomenko
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Section of Neurosurgery, Health Sciences Centre, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Brendan Santyr
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Jordy Tasserie
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Dave Gwun
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - Hyun Ho Jung
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Taufik Valiante
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Krembil Research Institute, Toronto, Ontario, Canada
- CRANIA, University Health Network and University of Toronto, Toronto, ON, M5G 2A2, Canada
- The KITE Research Institute, University Health Network, Toronto, ON, M5G 2A2, Canada
| | - George M Ibrahim
- Division of Pediatric Neurosurgery, Sick Kids Toronto, University of Toronto, Toronto, ON, Canada
| | - Richard Wennberg
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Krembil Research Institute, Toronto, Ontario, Canada
| | - Suneil K Kalia
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Krembil Research Institute, Toronto, Ontario, Canada
- CRANIA, University Health Network and University of Toronto, Toronto, ON, M5G 2A2, Canada
- The KITE Research Institute, University Health Network, Toronto, ON, M5G 2A2, Canada
| | - Andres M Lozano
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
- Krembil Research Institute, Toronto, Ontario, Canada
- CRANIA, University Health Network and University of Toronto, Toronto, ON, M5G 2A2, Canada
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19
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Abstract
The brain is a highly energy-demanding organ and requires bioenergetic adaptability to balance normal activity with pathophysiological fuelling of spontaneous recurrent seizures, the hallmark feature of the epilepsies. Recurrent or prolonged seizures have long been known to permanently alter neuronal circuitry and to cause excitotoxic injury and aberrant inflammation. Furthermore, pathological changes in bioenergetics and metabolism are considered downstream consequences of epileptic seizures that begin at the synaptic level. However, as we highlight in this Review, evidence is also emerging that primary derangements in cellular or mitochondrial metabolism can result in seizure genesis and lead to spontaneous recurrent seizures. Basic and translational research indicates that the relationships between brain metabolism and epileptic seizures are complex and bidirectional, producing a vicious cycle that compounds the deleterious consequences of seizures. Metabolism-based treatments such as the high-fat, antiseizure ketogenic diet have become mainstream, and metabolic substrates and enzymes have become attractive molecular targets for seizure prevention and recovery. Moreover, given that metabolism is crucial for epigenetic as well as inflammatory changes, the idea that epileptogenesis can be both negatively and positively influenced by metabolic changes is rapidly gaining ground. Here, we review evidence that supports both pathophysiological and therapeutic roles for brain metabolism in epilepsy.
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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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21
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Risacher SL, Saykin AJ. Neuroimaging Advances in Neurologic and Neurodegenerative Diseases. Neurotherapeutics 2021; 18:659-660. [PMID: 34410634 PMCID: PMC8423931 DOI: 10.1007/s13311-021-01105-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/06/2021] [Indexed: 01/01/2023] Open
Affiliation(s)
- Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
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