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Xie H, Illapani VSP, Vezina LG, Gholipour T, Oluigbo C, Gaillard WD, Cohen NT. Mapping Functional Connectivity Signatures of Pharmacoresistant Focal Cortical Dysplasia-Related Epilepsy. Ann Neurol 2024. [PMID: 39192492 DOI: 10.1002/ana.27069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 08/06/2024] [Accepted: 08/09/2024] [Indexed: 08/29/2024]
Abstract
OBJECTIVE To determine common network alterations in focal cortical dysplasia pharmacoresistant epilepsy (FCD-PRE) using functional connectivity analysis of resting-state functional magnetic resonance imaging (rsfMRI). METHODS This is a retrospective imaging cohort from Children's National Hospital (Washington, DC, USA) from January, 2011 to January, 2022. Patients with 3-T MRI-confirmed FCD-PRE underwent rsfMRI as part of routine clinical care. Patients were included if they were age 5-22 years at the time of the scan, and had a minimum of 18 months of follow-up. Healthy, typically-developing controls were included from Children's National Hospital (n = 16) and matched from Human Connectome Project-Development public dataset (n = 100). RESULTS A total of 42 FCD-PRE patients (20 M:22 F, aged 14.2 ± 4.1 years) and 116 healthy controls (56 M:60 F, aged 13.7 ± 3.3 years) with rsfMRI were included. Seed-based functional connectivity maps were generated for each FCD, and each seed was used to generate a patient-specific z-scored connectivity map on 116 controls. FCD-PRE patients had mutual altered connectivity in regions of dorsal attention, default mode, and control networks. Functional connectivity was diminished within the FCD dominant functional network, as well as in homotopic regions. Cluster specific connectivity patterns varied by pathological subtype. Higher FCD connectivity to the limbic network was associated with increased odds of Engel I outcome. INTERPRETATION This study demonstrates diminished functional connectivity patterns in FCD-PRE, which may represent a neuromarker for the disease, independent of FCD location, involving the dorsal attention, default mode, and control functional networks. Higher connectivity to the limbic network is associated with a seizure-free outcome. Future multicenter, prospective studies are needed to allow for much earlier detection of signatures of treatment-resistant epilepsy. ANN NEUROL 2024.
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Affiliation(s)
- Hua Xie
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC, USA
| | - Venkata Sita Priyanka Illapani
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC, USA
| | - L Gilbert Vezina
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC, USA
| | - Taha Gholipour
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA
| | - Chima Oluigbo
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC, USA
| | - William D Gaillard
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC, USA
| | - Nathan T Cohen
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC, USA
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Cohen NT, Xie H, Gholipour T, Gaillard WD. A scoping review of the functional magnetic resonance imaging-based functional connectivity of focal cortical dysplasia-related epilepsy. Epilepsia 2023; 64:3130-3142. [PMID: 37731142 DOI: 10.1111/epi.17775] [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: 06/13/2023] [Revised: 09/17/2023] [Accepted: 09/18/2023] [Indexed: 09/22/2023]
Abstract
Focal cortical dysplasia (FCD) is the most frequent etiology of operable pharmacoresistant epilepsy in children. There is burgeoning evidence that FCD-related epilepsy is a disorder that involves distributed brain networks. Functional magnetic resonance imaging (fMRI) is a tool that allows one to infer neuronal activity and to noninvasively map whole-brain functional networks. Despite its relatively widespread availability at most epilepsy centers, the clinical application of fMRI remains mostly task-based in epilepsy. Another approach is to map and characterize cortical functional networks of individuals using resting state fMRI (rsfMRI). The focus of this scoping review is to summarize the evidence to date of investigations of the network basis of FCD-related epilepsy, and to highlight numerous potential future applications of rsfMRI in the exploration of diagnostic and therapeutic strategies for FCD-related epilepsy. There are numerous studies demonstrating a global disruption of cortical functional networks in FCD-related epilepsy. The underlying pathological subtypes of FCD influence overall functional network patterns. There is evidence that cortical functional network mapping may help to predict postsurgical seizure outcomes, highlighting the translational potential of these findings. Additionally, several studies emphasize the important effect of FCD interaction with cortical networks and the expression of epilepsy and its comorbidities.
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Affiliation(s)
- Nathan T Cohen
- Center for Neuroscience Research, Children's National Hospital, George Washington University School of Medicine, Washington, District of Columbia, USA
- Department of Neurology, Children's National Hospital, George Washington University School of Medicine, Washington, District of Columbia, USA
| | - Hua Xie
- Center for Neuroscience Research, Children's National Hospital, George Washington University School of Medicine, Washington, District of Columbia, USA
- Department of Neurology, Children's National Hospital, George Washington University School of Medicine, Washington, District of Columbia, USA
| | - Taha Gholipour
- Center for Neuroscience Research, Children's National Hospital, George Washington University School of Medicine, Washington, District of Columbia, USA
- Department of Neurology, George Washington University Epilepsy Center, Washington, District of Columbia, USA
| | - William D Gaillard
- Center for Neuroscience Research, Children's National Hospital, George Washington University School of Medicine, Washington, District of Columbia, USA
- Department of Neurology, Children's National Hospital, George Washington University School of Medicine, Washington, District of Columbia, USA
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Cohen NT, Chang P, Gholipour T, Oluigbo C, Vezina LG, Xie H, Zhang A, Gaillard WD. Limbic network co-localization predicts pharmacoresistance in dysplasia-related epilepsy. Ann Clin Transl Neurol 2023; 10:2161-2165. [PMID: 37700505 PMCID: PMC10646997 DOI: 10.1002/acn3.51892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 08/21/2023] [Indexed: 09/14/2023] Open
Abstract
To evaluate the role of focal cortical dysplasia co-localization to cortical functional networks in the development of pharmacoresistance. One hundred thirty-six focal cortical dysplasia patients with 3.0 T or 1.5 T MRI were identified from clinical databases at Children's National Hospital. Clinico-radio-pathologic factors and network co-localization were determined. Using binomial logistic regression, limbic network co-localization (odds ratio 4.164 95% confidence interval 1.02-17.08, p = 0.048), and focal to bilateral tonic-clonic seizures (4.82, 1.30-18.03, p = 0.019) predicted pharmacoresistance. These findings provide clinicians with markers to identify patients with focal cortical dysplasia-related epilepsy at high risk of developing pharmacoresistance and should facilitate earlier epilepsy surgical evaluation.
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Affiliation(s)
- Nathan T. Cohen
- Center for Neuroscience ResearchChildren's National Hospital, The George Washington University School of MedicineWashingtonDCUSA
| | - Phat Chang
- Center for Neuroscience ResearchChildren's National Hospital, The George Washington University School of MedicineWashingtonDCUSA
| | - Taha Gholipour
- Center for Neuroscience ResearchChildren's National Hospital, The George Washington University School of MedicineWashingtonDCUSA
| | - Chima Oluigbo
- Center for Neuroscience ResearchChildren's National Hospital, The George Washington University School of MedicineWashingtonDCUSA
| | - L. Gilbert Vezina
- Center for Neuroscience ResearchChildren's National Hospital, The George Washington University School of MedicineWashingtonDCUSA
| | - Hua Xie
- Center for Neuroscience ResearchChildren's National Hospital, The George Washington University School of MedicineWashingtonDCUSA
| | - Anqing Zhang
- Division of Biostatistics and Study MethodologyChildren's National Research InstituteWashingtonDCUSA
| | - William D. Gaillard
- Center for Neuroscience ResearchChildren's National Hospital, The George Washington University School of MedicineWashingtonDCUSA
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Sklenarova B, Zatloukalova E, Cimbalnik J, Klimes P, Dolezalova I, Pail M, Kocvarova J, Hendrych M, Hermanova M, Gotman J, Dubeau F, Hall J, Pana R, Frauscher B, Brazdil M. Interictal high-frequency oscillations, spikes, and connectivity profiles: A fingerprint of epileptogenic brain pathologies. Epilepsia 2023; 64:3049-3060. [PMID: 37592755 DOI: 10.1111/epi.17749] [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: 12/28/2022] [Revised: 08/14/2023] [Accepted: 08/15/2023] [Indexed: 08/19/2023]
Abstract
OBJECTIVE Focal cortical dysplasia (FCD), hippocampal sclerosis (HS), nonspecific gliosis (NG), and normal tissue (NT) comprise the majority of histopathological results of surgically treated drug-resistant epilepsy patients. Epileptic spikes, high-frequency oscillations (HFOs), and connectivity measures are valuable biomarkers of epileptogenicity. The question remains whether they could also be utilized for preresective differentiation of the underlying brain pathology. This study explored spikes and HFOs together with functional connectivity in various epileptogenic pathologies. METHODS Interictal awake stereoelectroencephalographic recordings of 33 patients with focal drug-resistant epilepsy with seizure-free postoperative outcomes were analyzed (15 FCD, 8 HS, 6 NT, and 4 NG). Interictal spikes and HFOs were automatically identified in the channels contained in the overlap of seizure onset zone and resected tissue. Functional connectivity measures (relative entropy, linear correlation, cross-correlation, and phase consistency) were computed for neighboring electrode pairs. RESULTS Statistically significant differences were found between the individual pathologies in HFO rates, spikes, and their characteristics, together with functional connectivity measures, with the highest values in the case of HS and NG/NT. A model to predict brain pathology based on all interictal measures achieved up to 84.0% prediction accuracy. SIGNIFICANCE The electrophysiological profile of the various epileptogenic lesions in epilepsy surgery patients was analyzed. Based on this profile, a predictive model was developed. This model offers excellent potential to identify the nature of the underlying lesion prior to resection. If validated, this model may be particularly valuable for counseling patients, as depending on the lesion type, different outcomes are achieved after epilepsy surgery.
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Affiliation(s)
- Barbora Sklenarova
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Eva Zatloukalova
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Jan Cimbalnik
- International Clinical Research Center, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Petr Klimes
- International Clinical Research Center, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Irena Dolezalova
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Martin Pail
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Jitka Kocvarova
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Michal Hendrych
- First Department of Pathology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Marketa Hermanova
- First Department of Pathology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - François Dubeau
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jeffery Hall
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Raluca Pana
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Milan Brazdil
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
- Behavioral and Social Neuroscience Research Group, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
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Hamid C, Maiworm M, Wagner M, Knake S, Nöth U, Deichmann R, Gracien RM, Seiler A. Focal epilepsy without overt epileptogenic lesions: no evidence of microstructural brain tissue damage in multi-parametric quantitative MRI. Front Neurol 2023; 14:1175971. [PMID: 37528856 PMCID: PMC10389268 DOI: 10.3389/fneur.2023.1175971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 07/03/2023] [Indexed: 08/03/2023] Open
Abstract
Background and purpose In patients with epilepsies of structural origin, brain atrophy and pathological alterations of the tissue microstructure extending beyond the putative epileptogenic lesion have been reported. However, in patients without any evidence of epileptogenic lesions on diagnostic magnetic resonance imaging (MRI), impairment of the brain microstructure has been scarcely elucidated. Using multiparametric quantitative (q) magnetic resonance imaging MRI, we aimed to investigate diffuse impairment of the microstructural tissue integrity in MRI-negative focal epilepsy patients. Methods 27 MRI-negative patients with focal epilepsy (mean age 33.1 ± 14.2 years) and 27 matched healthy control subjects underwent multiparametric qMRI including T1, T2, and PD mapping at 3 T. After tissue segmentation based on synthetic anatomies, mean qMRI parameter values were extracted from the cerebral cortex, the white matter (WM) and the deep gray matter (GM) and compared between patients and control subjects. Apart from calculating mean values for the qMRI parameters across the respective compartments, voxel-wise analyses were performed for each tissue class. Results There were no significant differences for mean values of quantitative T1, T2, and PD obtained from the cortex, the WM and the deep GM between the groups. Furthermore, the voxel-wise analyses did not reveal any clusters indicating significant differences between patients and control subjects for the qMRI parameters in the respective compartments. Conclusions Based on the employed methodology, no indication for an impairment of the cerebral microstructural tissue integrity in MRI-negative patients with focal epilepsy was found in this study. Further research will be necessary to identify relevant factors and mechanisms contributing to microstructural brain tissue damage in various subgroups of patients with epilepsy.
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Affiliation(s)
- Celona Hamid
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - Michelle Maiworm
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Marlies Wagner
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
- Institute of Neuroradiology, Goethe University Hospital, Frankfurt, Germany
| | - Susanne Knake
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
- Epilepsy Center Hessen and Department of Neurology, Philipps-University Marburg, Marburg, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - Alexander Seiler
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
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Li Z, Hou X, Lu Y, Zhao H, Wang M, Xu B, Shi Q, Gui Q, Wu G, Shen M, Zhu W, Xu Q, Dong X, Cheng Q, Zhang J, Feng H. Study of brain network alternations in non-lesional epilepsy patients by BOLD-fMRI. Front Neurosci 2023; 16:1031163. [PMID: 36741055 PMCID: PMC9889547 DOI: 10.3389/fnins.2022.1031163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 12/30/2022] [Indexed: 01/20/2023] Open
Abstract
Objective To investigate the changes of brain network in epilepsy patients without intracranial lesions under resting conditions. Methods Twenty-six non-lesional epileptic patients and 42 normal controls were enrolled for BOLD-fMRI examination. The differences in brain network topological characteristics and functional network connectivity between the epilepsy group and the healthy controls were compared using graph theory analysis and independent component analysis. Results The area under the curve for local efficiency was significantly lower in the epilepsy patients compared with healthy controls, while there were no differences in global indicators. Patients with epilepsy had higher functional connectivity in 4 connected components than healthy controls (orbital superior frontal gyrus and medial superior frontal gyrus, medial superior frontal gyrus and angular gyrus, superior parietal gyrus and paracentral lobule, lingual gyrus, and thalamus). In addition, functional connectivity was enhanced in the default mode network, frontoparietal network, dorsal attention network, sensorimotor network, and auditory network in the epilepsy group. Conclusion The topological characteristics and functional connectivity of brain networks are changed in in non-lesional epilepsy patients. Abnormal functional connectivity may suggest reduced brain efficiency in epilepsy patients and also may be a compensatory response to brain function early at earlier stages of the disease.
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Affiliation(s)
- Zhisen Li
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Xiaoxia Hou
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Yanli Lu
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Huimin Zhao
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Meixia Wang
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Bo Xu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qianru Shi
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qian Gui
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Guanhui Wu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Mingqiang Shen
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Wei Zhu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qinrong Xu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Xiaofeng Dong
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qingzhang Cheng
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Jibin Zhang
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Hongxuan Feng
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China,*Correspondence: Hongxuan Feng,
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Bacon EJ, Jin C, He D, Hu S, Wang L, Li H, Qi S. Functional and effective connectivity analysis of drug-resistant epilepsy: a resting-state fMRI analysis. Front Neurosci 2023; 17:1163111. [PMID: 37152592 PMCID: PMC10157077 DOI: 10.3389/fnins.2023.1163111] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 04/03/2023] [Indexed: 05/09/2023] Open
Abstract
Objective Epilepsy is considered as a neural network disorder. Seizure activity in epilepsy may disturb brain networks and damage brain functions. We propose using resting-state functional magnetic resonance imaging (rs-fMRI) data to characterize connectivity patterns in drug-resistant epilepsy. Methods This study enrolled 47 participants, including 28 with drug-resistant epilepsy and 19 healthy controls. Functional and effective connectivity was employed to assess drug-resistant epilepsy patients within resting state networks. The resting state functional connectivity (FC) analysis was performed to assess connectivity between each patient and healthy controls within the default mode network (DMN) and the dorsal attention network (DAN). In addition, dynamic causal modeling was used to compute effective connectivity (EC). Finally, a statistical analysis was performed to evaluate our findings. Results The FC analysis revealed significant connectivity changes in patients giving 64.3% (18/28) and 78.6% (22/28) for DMN and DAN, respectively. Statistical analysis of FC was significant between the medial prefrontal cortex, posterior cingulate cortex, and bilateral inferior parietal cortex for DMN. For DAN, it was significant between the left and the right intraparietal sulcus and the frontal eye field. For the DMN, the patient group showed significant EC connectivity in the right inferior parietal cortex and the medial prefrontal cortex for the DMN. There was also bilateral connectivity between the medial prefrontal cortex and the posterior cingulate cortex, as well as between the left and right inferior parietal cortex. For DAN, patients showed significant connectivity in the right frontal eye field and the right intraparietal sulcus. Bilateral connectivity was also found between the left frontal eye field and the left intraparietal sulcus, as well as between the right frontal eye field and the right intraparietal sulcus. The statistical analysis of the EC revealed a significant result in the medial prefrontal cortex and the right intraparietal cortex for the DMN. The DAN was found significant in the left frontal eye field, as well as the left and right intraparietal sulcus. Conclusion Our results provide preliminary evidence to support that the combination of functional and effective connectivity analysis of rs-fMRI can aid in diagnosing epilepsy in the DMN and DAN networks.
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Affiliation(s)
- Eric Jacob Bacon
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
- Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China
| | - Chaoyang Jin
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Dianning He
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Shuaishuai Hu
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lanbo Wang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Han Li
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, China
- *Correspondence: Han Li,
| | - Shouliang Qi
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
- Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China
- Shouliang Qi,
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Cohen NT, You X, Krishnamurthy M, Sepeta LN, Zhang A, Oluigbo C, Whitehead MT, Gholipour T, Baldeweg T, Wagstyl K, Adler S, Gaillard WD. Networks Underlie Temporal Onset of Dysplasia-Related Epilepsy: A MELD Study. Ann Neurol 2022; 92:503-511. [PMID: 35726354 PMCID: PMC10410674 DOI: 10.1002/ana.26442] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 04/22/2022] [Accepted: 06/10/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE The purpose of this study was to evaluate if focal cortical dysplasia (FCD) co-localization to cortical functional networks is associated with the temporal distribution of epilepsy onset in FCD. METHODS International (20 center), retrospective cohort from the Multi-Centre Epilepsy Lesion Detection (MELD) project. Patients included if >3 years old, had 3D pre-operative T1 magnetic resonance imaging (MRI; 1.5 or 3 T) with radiologic or histopathologic FCD after surgery. Images processed using the MELD protocol, masked with 3D regions-of-interest (ROI), and co-registered to fsaverage_sym (symmetric template). FCDs were then co-localized to 1 of 7 distributed functional cortical networks. Negative binomial regression evaluated effect of FCD size, network, histology, and sulcal depth on age of epilepsy onset. From this model, predictive age of epilepsy onset was calculated for each network. RESULTS Three hundred eighty-eight patients had median age seizure onset 5 years (interquartile range [IQR] = 3-11 years), median age at pre-operative scan 18 years (IQR = 11-28 years). FCDs co-localized to the following networks: limbic (90), default mode (87), somatomotor (65), front parietal control (52), ventral attention (32), dorsal attention (31), and visual (31). Larger lesions were associated with younger age of onset (p = 0.01); age of epilepsy onset was associated with dominant network (p = 0.04) but not sulcal depth or histology. Sensorimotor networks had youngest onset; the limbic network had oldest age of onset (p values <0.05). INTERPRETATION FCD co-localization to distributed functional cortical networks is associated with age of epilepsy onset: sensory neural networks (somatomotor and visual) with earlier onset, and limbic latest onset. These variations may reflect developmental differences in synaptic/white matter maturation or network activation and may provide a biological basis for age-dependent epilepsy onset expression. ANN NEUROL 2022;92:503-511.
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Affiliation(s)
- Nathan T Cohen
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
| | - Xiaozhen You
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
| | - Manu Krishnamurthy
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
| | - Leigh N Sepeta
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
| | - Anqing Zhang
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
- Division of Biostatistics and Study Methodology, Children's National Research Institute, Washington, DC
| | - Chima Oluigbo
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
- Department of Neurosurgery, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
| | - Matthew T Whitehead
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
- Department of Neuroradiology, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
| | - Taha Gholipour
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
- George Washington University Epilepsy Center, The George Washington University School of Medicine, Washington, DC
| | - Torsten Baldeweg
- Great Ormond Street Institute for Child Health, University College of London, London, UK
| | | | - Sophie Adler
- Great Ormond Street Institute for Child Health, University College of London, London, UK
| | - William D Gaillard
- Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC
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Lee DA, Lee HJ, Kim HC, Park KM. Alterations of structural connectivity and structural co-variance network in focal cortical dysplasia. BMC Neurol 2021; 21:330. [PMID: 34452597 PMCID: PMC8394627 DOI: 10.1186/s12883-021-02358-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 08/17/2021] [Indexed: 12/04/2022] Open
Abstract
Background The aim of this study was to investigate alterations in structural connectivity and structural co-variance network in patients with focal cortical dysplasia (FCD). Methods We enrolled 37 patients with FCD and 35 healthy controls. All subjects underwent brain MRI with the same scanner and with the same protocol, which included diffusion tensor imaging (DTI) and T1-weighted imaging. We analyzed the structural connectivity based on DTI, and structural co-variance network based on the structural volume with T1-weighted imaging. We created a connectivity matrix and obtained network measures from the matrix using the graph theory. We tested the difference in network measure between patients with FCD and healthy controls. Results In the structural connectivity analysis, we found that the local efficiency in patients with FCD was significantly lower than in healthy controls (2.390 vs. 2.578, p = 0.031). Structural co-variance network analysis revealed that the mean clustering coefficient, global efficiency, local efficiency, and transitivity were significantly decreased in patients with FCD compared to those in healthy controls (0.527 vs. 0.635, p = 0.036; 0.545 vs. 0.648, p = 0.026; 2.699 vs. 3.801, p = 0.019; 0.791 vs. 0.954, p = 0.026, respectively). Conclusions We demonstrate that there are significant alterations in structural connectivity, based on DTI, and structural co-variance network, based on the structural volume, in patients with FCD compared to healthy controls. These findings suggest that focal lesions with FCD could affect the whole-brain network and that FCD is a network disease.
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Affiliation(s)
- Dong Ah Lee
- Neurology Department, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, 48108, Busan, Korea
| | - Ho-Joon Lee
- Radiology Department, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Hyung Chan Kim
- Neurology Department, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, 48108, Busan, Korea
| | - Kang Min Park
- Neurology Department, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, 48108, Busan, Korea.
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Liu W, Yue Q, Gong Q, Zhou D, Wu X. Regional and remote connectivity patterns in focal extratemporal lobe epilepsy. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1128. [PMID: 34430569 PMCID: PMC8350670 DOI: 10.21037/atm-21-1374] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 05/28/2021] [Indexed: 02/05/2023]
Abstract
Background Focal epilepsy accounts for most epilepsy cases, and frontal lobe epilepsy (FLE) accounts for the largest proportion of cases of extratemporal epilepsy syndrome. The epileptogenic zone is usually not easy to locate, contributing to a lack of imaging studies. The objective of this study was to evaluate functional connectivity patterns to explore the underlying pathological mechanisms of this disorder. Methods Forty-three patients with focal extratemporal epilepsy [mean age ± standard deviation (SD): 29.51±8.04 years, 19 males] and the same number of healthy controls (mean age ± SD: 29.56±8.02 years, 19 males) were recruited to undergo functional magnetic resonance imaging. Mean regional homogeneity (ReHo) was measured, and regions showing significant alterations in ReHo in patients were identified to examine functional connectivity (FC). In particular, FC within the default mode network (DMN) in patients was analyzed. Results Patients with extratemporal lobe epilepsy showed significantly higher ReHo in the bilateral precentral gyrus, and lower ReHo in frontal-cerebellum regions than healthy controls [P<0.05, Gaussian random field (GRF)-corrected]. FC analysis based on regions of interest showed significantly higher connectivity in the frontoparietal-insula region and lowered FC in the frontal-cerebellum regions (P<0.05, GRF-corrected). Altered FC within DMN was also demonstrated (P<0.05, GRF-corrected). Conclusions Analyses of ReHo and FC based on regions of interest suggest epilepsy-related neural networks are located mainly in frontal regions in extratemporal lobe epilepsy. These findings reveal disruptions of interactions and connectivity of large-scale neural networks and frontotemporal-cerebellar regions, suggesting connectivity-based pathophysiology.
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Affiliation(s)
- Wenyu Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiang Yue
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Xintong Wu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
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Li W, Jiang Y, Qin Y, Zhou B, Lei D, Zhang H, Lei D, Yao D, Luo C, Gong Q, Zhou D, An D. Structural and functional reorganization of contralateral hippocampus after temporal lobe epilepsy surgery. NEUROIMAGE-CLINICAL 2021; 31:102714. [PMID: 34102537 PMCID: PMC8187253 DOI: 10.1016/j.nicl.2021.102714] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 05/27/2021] [Accepted: 05/28/2021] [Indexed: 02/08/2023]
Abstract
Postoperative changes of contralateral hippocampus in temporal lobe epilepsy. No obvious hippocampal volume change was observed after successful surgery. Surgical manipulation may lead to a transient functional connectivity reduction. Increased functional connectivity mostly involved bilateral frontal regions.
Objective To explore the structural and functional reorganization of contralateral hippocampus in patients with unilateral mesial temporal lobe epilepsy (mTLE) who achieved seizure-freedom after anterior temporal lobectomy (ATL). Methods We obtained high-resolution structural MRI and resting-state functional MRI data in 28 unilateral mTLE patients and 29 healthy controls. Patients were scanned before and three and 24 months after surgery while controls were scanned only once. Hippocampal gray matter volume (GMV) and functional connectivity (FC) were assessed. Results No obvious GMV changes were observed in contralateral hippocampus before and after successful surgery. Before surgery, ipsilateral hippocampus showed increased FC with ipsilateral insula (INS) and temporoparietal junction (TPJ), but decreased FC with widespread bilateral regions, as well as contralateral hippocampus. After successful ATL, contralateral hippocampus showed: (1) decreased FC with ipsilateral INS at three months follow-up, without further changes; (2) decreased FC with ipsilateral TPJ, postcentral gyrus and rolandic operculum at three months, with an obvious increase at 24 months follow-up; (3) increased FC with bilateral medial prefrontal cortex (MPFC) and superior frontal gyrus (SFG) at three months follow-up, without further changes. Conclusions Successful ATL may not lead to an obvious structural reorganization in contralateral hippocampus. Surgical manipulation may lead to a transient FC reduction of contralateral hippocampus. Increased FC between contralateral hippocampus and bilateral MPFC and SFG may be related to postoperative functional remodeling.
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Affiliation(s)
- Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Yingjie Qin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Baiwan Zhou
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Du Lei
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Heng Zhang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ding Lei
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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