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Sheybani L, Vivekananda U, Rodionov R, Diehl B, Chowdhury FA, McEvoy AW, Miserocchi A, Bisby JA, Bush D, Burgess N, Walker MC. Wake slow waves in focal human epilepsy impact network activity and cognition. Nat Commun 2023; 14:7397. [PMID: 38036557 PMCID: PMC10689494 DOI: 10.1038/s41467-023-42971-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 10/27/2023] [Indexed: 12/02/2023] Open
Abstract
Slow waves of neuronal activity are a fundamental component of sleep that are proposed to have homeostatic and restorative functions. Despite this, their interaction with pathology is unclear and there is only indirect evidence of their presence during wakefulness. Using intracortical recordings from the temporal lobe of 25 patients with epilepsy, we demonstrate the existence of local wake slow waves (LoWS) with key features of sleep slow waves, including a down-state of neuronal firing. Consistent with a reduction in neuronal activity, LoWS were associated with slowed cognitive processing. However, we also found that LoWS showed signatures of a homeostatic relationship with interictal epileptiform discharges (IEDs): exhibiting progressive adaptation during the build-up of network excitability before an IED and reducing the impact of subsequent IEDs on network excitability. We therefore propose an epilepsy homeostasis hypothesis: that slow waves in epilepsy reduce aberrant activity at the price of transient cognitive impairment.
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Affiliation(s)
- Laurent Sheybani
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Umesh Vivekananda
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Roman Rodionov
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Fahmida A Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - James A Bisby
- Division of Psychiatry, University College London, London, UK
| | - Daniel Bush
- Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
| | - Neil Burgess
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK.
- Institute of Cognitive Neuroscience, University College London, London, UK.
| | - Matthew C Walker
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK.
- National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK.
- NIHR University College London Hospitals Biomedical Research Centre, London, UK.
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Horsley JJ, Thomas RH, Chowdhury FA, Diehl B, McEvoy AW, Miserocchi A, de Tisi J, Vos SB, Walker MC, Winston GP, Duncan JS, Wang Y, Taylor PN. Complementary structural and functional abnormalities to localise epileptogenic tissue. EBioMedicine 2023; 97:104848. [PMID: 37898096 PMCID: PMC10630610 DOI: 10.1016/j.ebiom.2023.104848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 10/11/2023] [Accepted: 10/11/2023] [Indexed: 10/30/2023] Open
Abstract
BACKGROUND When investigating suitability for epilepsy surgery, people with drug-refractory focal epilepsy may have intracranial EEG (iEEG) electrodes implanted to localise seizure onset. Diffusion-weighted magnetic resonance imaging (dMRI) may be acquired to identify key white matter tracts for surgical avoidance. Here, we investigate whether structural connectivity abnormalities, inferred from dMRI, may be used in conjunction with functional iEEG abnormalities to aid localisation of the epileptogenic zone (EZ), improving surgical outcomes in epilepsy. METHODS We retrospectively investigated data from 43 patients (42% female) with epilepsy who had surgery following iEEG. Twenty-five patients (58%) were free from disabling seizures (ILAE 1 or 2) at one year. Interictal iEEG functional, and dMRI structural connectivity abnormalities were quantified by comparison to a normative map and healthy controls. We explored whether the resection of maximal abnormalities related to improved surgical outcomes, in both modalities individually and concurrently. Additionally, we suggest how connectivity abnormalities may inform the placement of iEEG electrodes pre-surgically using a patient case study. FINDINGS Seizure freedom was 15 times more likely in patients with resection of maximal connectivity and iEEG abnormalities (p = 0.008). Both modalities separately distinguished patient surgical outcome groups and when used simultaneously, a decision tree correctly separated 36 of 43 (84%) patients. INTERPRETATION Our results suggest that both connectivity and iEEG abnormalities may localise epileptogenic tissue, and that these two modalities may provide complementary information in pre-surgical evaluations. FUNDING This research was funded by UKRI, CDT in Cloud Computing for Big Data, NIH, MRC, Wellcome Trust and Epilepsy Research UK.
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Affiliation(s)
- Jonathan J Horsley
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Rhys H Thomas
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Fahmida A Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sjoerd B Vos
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Centre for Microscopy, Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia; Centre for Medical Image Computing, Computer Science Department, University College London, London, United Kingdom
| | - Matthew C Walker
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Gavin P Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Division of Neurology, Department of Medicine, Queen's University, Kingston, Canada
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Yujiang Wang
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Peter N Taylor
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
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Rogeau A, Lilburn DML, Kaplar Z, Anderson C, Scott CJ, Chowdhury FA, Fraioli F, Bomanji JB. Identifying and troubleshooting the pitfalls of ictal/interictal brain perfusion SPECT studies. Nucl Med Commun 2023; 44:1053-1058. [PMID: 37661779 DOI: 10.1097/mnm.0000000000001755] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Epilepsy is a prevalent condition, and surgical intervention can benefit patients with refractory seizures. Single photon emission computed tomography (SPECT) using 99mTc-HMPAO or 99mTc-ECD provides assessment of regional cerebral blood flow and is the primary non-invasive approach for imaging brain perfusion in ictal and interictal states. Ictal/interictal SPECT is valuable in localising epileptogenic foci, particularly when MRI and electroencephalography are negative. However, to obtain accurate images reflecting brain perfusion in both states, meticulous preparation of the patient, timely radiotracer injection and close coordination between neurology and nuclear medicine teams are essential. Tracers also have inherent limitations, and patients may present with coexisting brain pathologies for which coregistration of SPECT images with MRI is recommended to improve diagnostic accuracy. Inconclusive SPECT findings may require repeating the exam or considering additional investigations. A comprehensive approach, considering various factors, is crucial for accurate interpretation of SPECT studies in presurgical epilepsy evaluations. This article provides a summary of the organisation and key challenges involved in conducting ictal/interictal SPECT studies, covering the entire process from a patient's hospital arrival to the integration of results within their presurgical pathway and using our experience of 182 patients over 10 years.
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Affiliation(s)
- Antoine Rogeau
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
- Department of Nuclear Medicine, Lille University Hospitals, Lille, France
| | - David M L Lilburn
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
- Department of Imaging, School of Medicine, University College London
| | - Zoltan Kaplar
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
| | - Cameron Anderson
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
| | - Catherine J Scott
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
| | - Fahmida A Chowdhury
- Department of Neurology, National Hospital for Neurology and Neurosurgery, London, UK
| | - Francesco Fraioli
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
- Department of Imaging, School of Medicine, University College London
| | - Jamshed B Bomanji
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
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Owen TW, Janiukstyte V, Hall GR, Chowdhury FA, Diehl B, McEvoy A, Miserocchi A, de Tisi J, Duncan JS, Rugg-Gunn F, Wang Y, Taylor PN. Interictal magnetoencephalography abnormalities to guide intracranial electrode implantation and predict surgical outcome. Brain Commun 2023; 5:fcad292. [PMID: 37953844 PMCID: PMC10636564 DOI: 10.1093/braincomms/fcad292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 08/24/2023] [Accepted: 10/24/2023] [Indexed: 11/14/2023] Open
Abstract
Intracranial EEG is the gold standard technique for epileptogenic zone localization but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography. Quantitative abnormality mapping using magnetoencephalography has recently been shown to have potential clinical value. We hypothesized that if quantifiable magnetoencephalography abnormalities were sampled by intracranial EEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent magnetoencephalography and subsequent intracranial EEG recordings as part of presurgical evaluation. Eyes-closed resting-state interictal magnetoencephalography band power abnormality maps were derived from 70 healthy controls as a normative baseline. Magnetoencephalography abnormality maps were compared to intracranial EEG electrode implantation, with the spatial overlap of intracranial EEG electrode placement and cerebral magnetoencephalography abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue and subsequent resection of the strongest abnormalities determined by magnetoencephalography and intracranial EEG corresponded to surgical success. We used the area under the receiver operating characteristic curve as a measure of effect size. Intracranial electrodes were implanted in brain tissue with the most abnormal magnetoencephalography findings-in individuals that were seizure-free postoperatively (T = 3.9, P = 0.001) but not in those who did not become seizure-free. The overlap between magnetoencephalography abnormalities and electrode placement distinguished surgical outcome groups moderately well (area under the receiver operating characteristic curve = 0.68). In isolation, the resection of the strongest abnormalities as defined by magnetoencephalography and intracranial EEG separated surgical outcome groups well, area under the receiver operating characteristic curve = 0.71 and area under the receiver operating characteristic curve = 0.74, respectively. A model incorporating all three features separated surgical outcome groups best (area under the receiver operating characteristic curve = 0.80). Intracranial EEG is a key tool to delineate the epileptogenic zone and help render individuals seizure-free postoperatively. We showed that data-driven abnormality maps derived from resting-state magnetoencephalography recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of postoperative seizure freedom, which leverages both magnetoencephalography and intracranial EEG recordings, could aid patient counselling of expected outcome.
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Affiliation(s)
- Thomas W Owen
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Vytene Janiukstyte
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Gerard R Hall
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Fahmida A Chowdhury
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Beate Diehl
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Andrew McEvoy
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Anna Miserocchi
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Jane de Tisi
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - John S Duncan
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Fergus Rugg-Gunn
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Yujiang Wang
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Peter N Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
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Horsley JJ, Thomas RH, Chowdhury FA, Diehl B, McEvoy AW, Miserocchi A, de Tisi J, Vos SB, Walker MC, Winston GP, Duncan JS, Wang Y, Taylor PN. Complementary structural and functional abnormalities to localise epileptogenic tissue. ArXiv 2023:arXiv:2304.03192v3. [PMID: 37064531 PMCID: PMC10104180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Background When investigating suitability for epilepsy surgery, people with drug-refractory focal epilepsy may have intracranial EEG (iEEG) electrodes implanted to localise seizure onset. Diffusion-weighted magnetic resonance imaging (dMRI) may be acquired to identify key white matter tracts for surgical avoidance. Here, we investigate whether structural connectivity abnormalities, inferred from dMRI, may be used in conjunction with functional iEEG abnormalities to aid localisation of the epileptogenic zone (EZ), improving surgical outcomes in epilepsy. Methods We retrospectively investigated data from 43 patients with epilepsy who had surgery following iEEG. Twenty-five patients (58%) were free from disabling seizures (ILAE 1 or 2) at one year. Interictal iEEG functional, and dMRI structural connectivity abnormalities were quantified by comparison to a normative map and healthy controls. We explored whether the resection of maximal abnormalities related to improved surgical outcomes, in both modalities individually and concurrently. Additionally, we suggest how connectivity abnormalities may inform the placement of iEEG electrodes pre-surgically using a patient case study. Findings Seizure freedom was 15 times more likely in patients with resection of maximal connectivity and iEEG abnormalities (p=0.008). Both modalities separately distinguished patient surgical outcome groups and when used simultaneously, a decision tree correctly separated 36 of 43 (84%) patients. Interpretation Our results suggest that both connectivity and iEEG abnormalities may localise epileptogenic tissue, and that these two modalities may provide complementary information in pre-surgical evaluations. Funding This research was funded by UKRI, CDT in Cloud Computing for Big Data, NIH, MRC, Wellcome Trust and Epilepsy Research UK.
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Affiliation(s)
- Jonathan J. Horsley
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Rhys H. Thomas
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Fahmida A. Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Andrew W. McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sjoerd B. Vos
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
- Centre for Microscopy, Characterisation, and Analysis, The University of Western Australia, Nedlands, Australia
- Centre for Medical Image Computing, Computer Science Department, University College London, London, United Kingdom
| | - Matthew C. Walker
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Gavin P. Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
- Division of Neurology, Department of Medicine, Queen’s University, Kingston, Canada
| | - John S. Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Yujiang Wang
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Peter N. Taylor
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
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Sharmin I, Mahmud F, Chowdhury FA, Khatun M, Alam MT, Chowdhury AK. Comparison of Pain Control and Analgesic Consumption With or Without Infiltration of Bupivacaine at Port Sites after Laparoscopic Cholecystectomy. Mymensingh Med J 2023; 32:1133-1139. [PMID: 37777912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/02/2023]
Abstract
Pain management is an essential component of all surgical procedures. Analgesics are used for this purpose but there are some complications in using them. Local anesthetics like bupivacaine can be used to reduce postoperative pain as well as analgesics consumption. The objective of this study is to observe the result of infiltration of bupivacaine at port sites and to compare the postoperative pain relief with that of opioids and NSAID administration following laparoscopic cholecystectomy for chronic calculus cholecystitis. This is a cross sectional study was conducted over one year in the Department of Surgery of Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh from September 2018 to August 2019. Here total 40 patients were enrolled by purposive sampling. They were divided in two groups. One group received bupivacaine while other did not. A numerical pain scale was used as tool. Data will be recorded by peer reviewed interview and observation based semi structured data collection sheet. Data analysis was done by SPSS version 23.0. P-value was significant at (p<0.05) and determined by chi square test. Written informed consent was taken from the patient. The mean Numerical Rating Scale (NRS) score of pain at 6 hour was 2.55±0.6 in Group I and 6.8±1.15 in Group II. The mean NRS score of pain at 12 hour was 4.1±1.21 in Group I and 7.95±0.6 in Group II. The mean time of 1st analgesic administration was 13.85±1.57 hours in Group I and 2.75±0.72 hours in Group II. The mean repeat dose of analgesic was in 22±2.29 hours in Group I and 9.5±1.15 hours in Group II. In Group I one third patients (30.0%) single dose analgesic required in 1st 12 hours while in Group II almost 90.0% patients needed analgesics in 1st 12 hours. In Group I, total doses of analgesics required were 2 in 75.0% patients while in Group II at least 3 doses of analgesics were needed. In Group I only one patient needed analgesic in first 6 hours (5.0%) while in Group II, all the patients (100.0%) needed analgesics. The difference was statistically significant (p<0.05) between two groups. The patients receiving bupivacaine at port sites will experience less pain at postoperative period and will need less analgesic medications.
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Affiliation(s)
- I Sharmin
- Dr Iffat Sharmin, Resident, Department of Surgery, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh; E-mail:
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Sinha N, Duncan JS, Diehl B, Chowdhury FA, de Tisi J, Miserocchi A, McEvoy AW, Davis KA, Vos SB, Winston GP, Wang Y, Taylor PN. Intracranial EEG Structure-Function Coupling and Seizure Outcomes After Epilepsy Surgery. Neurology 2023; 101:e1293-e1306. [PMID: 37652703 PMCID: PMC10558161 DOI: 10.1212/wnl.0000000000207661] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Accepted: 06/02/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Surgery is an effective treatment for drug-resistant epilepsy, which modifies the brain's structure and networks to regulate seizure activity. Our objective was to examine the relationship between brain structure and function to determine the extent to which this relationship affects the success of the surgery in controlling seizures. We hypothesized that a stronger association between brain structure and function would lead to improved seizure control after surgery. METHODS We constructed functional and structural brain networks in patients with drug-resistant focal epilepsy by using presurgery functional data from intracranial EEG (iEEG) recordings, presurgery and postsurgery structural data from T1-weighted MRI, and presurgery diffusion-weighted MRI. We quantified the relationship (coupling) between structural and functional connectivity by using the Spearman rank correlation and analyzed this structure-function coupling at 2 spatial scales: (1) global iEEG network level and (2) individual iEEG electrode contacts using virtual surgeries. We retrospectively predicted postoperative seizure freedom by incorporating the structure-function connectivity coupling metrics and routine clinical variables into a cross-validated predictive model. RESULTS We conducted a retrospective analysis on data from 39 patients who met our inclusion criteria. Brain areas implanted with iEEG electrodes had stronger structure-function coupling in seizure-free patients compared with those with seizure recurrence (p = 0.002, d = 0.76, area under the receiver operating characteristic curve [AUC] = 0.78 [95% CI 0.62-0.93]). Virtual surgeries on brain areas that resulted in stronger structure-function coupling of the remaining network were associated with seizure-free outcomes (p = 0.007, d = 0.96, AUC = 0.73 [95% CI 0.58-0.89]). The combination of global and local structure-function coupling measures accurately predicted seizure outcomes with a cross-validated AUC of 0.81 (95% CI 0.67-0.94). These measures were complementary to other clinical variables and, when included for prediction, resulted in a cross-validated AUC of 0.91 (95% CI 0.82-1.0), accuracy of 92%, sensitivity of 93%, and specificity of 91%. DISCUSSION Our study showed that the strength of structure-function connectivity coupling may play a crucial role in determining the success of epilepsy surgery. By quantitatively incorporating structure-function coupling measures and standard-of-care clinical variables into presurgical evaluations, we may be able to better localize epileptogenic tissue and select patients for epilepsy surgery. CLASSIFICATION OF EVIDENCE This is a Class IV retrospective case series showing that structure-function mapping may help determine the outcome from surgical resection for treatment-resistant focal epilepsy.
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Affiliation(s)
- Nishant Sinha
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada.
| | - John S Duncan
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Beate Diehl
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Fahmida A Chowdhury
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Jane de Tisi
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Anna Miserocchi
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Andrew William McEvoy
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Kathryn A Davis
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Sjoerd B Vos
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Gavin P Winston
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Yujiang Wang
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
| | - Peter Neal Taylor
- From the Department of Neurology (N.S., K.A.D.), Penn Epilepsy Center, Perelman School of Medicine, and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia; Translational and Clinical Research Institute (Y.W., P.N.T.), Faculty of Medical Sciences, and Computational Neuroscience, Neurology, and Psychiatry Lab (Y.W., P.N.T.), ICOS Group, School of Computing, Newcastle University; Department of Epilepsy (J.S.D., B.D., F.A.C., J.d.T., A.M., A.W.M., G.P.W., Y.W., P.N.T.), UCL Queen Square Institute of Neurology; UCL Centre for Medical Image Computing (S.B.V.); Neuroradiological Academic Unit (S.B.V.), UCL Queen Square Institute of Neurology, London; MRI Unit (J.S.D., G.P.W.), Chalfont Centre for Epilepsy, Bucks, United Kingdom; Centre for Microscopy, Characterisation, and Analysis (S.B.V.), The University of Western Australia, Nedlands; and Division of Neurology (G.P.W.), Department of Medicine, Queen's University, Kingston, Canada
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8
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Wang Y, Schroeder GM, Horsley JJ, Panagiotopoulou M, Chowdhury FA, Diehl B, Duncan JS, McEvoy AW, Miserocchi A, de Tisi J, Taylor PN. Temporal stability of intracranial electroencephalographic abnormality maps for localizing epileptogenic tissue. Epilepsia 2023; 64:2070-2080. [PMID: 37226553 PMCID: PMC10962550 DOI: 10.1111/epi.17663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 05/26/2023]
Abstract
OBJECTIVE Identifying abnormalities on interictal intracranial electroencephalogram (iEEG), by comparing patient data to a normative map, has shown promise for the localization of epileptogenic tissue and prediction of outcome. The approach typically uses short interictal segments of approximately 1 min. However, the temporal stability of findings has not been established. METHODS Here, we generated a normative map of iEEG in nonpathological brain tissue from 249 patients. We computed regional band power abnormalities in a separate cohort of 39 patients for the duration of their monitoring period (.92-8.62 days of iEEG data, mean = 4.58 days per patient, >4800 hours recording). To assess the localizing value of band power abnormality, we computedD RS -a measure of how different the surgically resected and spared tissue was in terms of band power abnormalities-over time. RESULTS In each patient, theD RS value was relatively consistent over time. The medianD RS of the entire recording period separated seizure-free (International League Against Epilepsy [ILAE] = 1) and not-seizure-free (ILAE> 1) patients well (area under the curve [AUC] = .69). This effect was similar interictally (AUC = .69) and peri-ictally (AUC = .71). SIGNIFICANCE Our results suggest that band power abnormality D_RS, as a predictor of outcomes from epilepsy surgery, is a relatively robust metric over time. These findings add further support for abnormality mapping of neurophysiology data during presurgical evaluation.
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Affiliation(s)
- Yujiang Wang
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle Upon TyneUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle Upon TyneUK
- UCL Queen Square Institute of NeurologyQueen SquareLondonUK
| | - Gabrielle M. Schroeder
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle Upon TyneUK
| | - Jonathan J. Horsley
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle Upon TyneUK
| | - Mariella Panagiotopoulou
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle Upon TyneUK
| | | | - Beate Diehl
- UCL Queen Square Institute of NeurologyQueen SquareLondonUK
| | - John S. Duncan
- UCL Queen Square Institute of NeurologyQueen SquareLondonUK
| | | | | | - Jane de Tisi
- UCL Queen Square Institute of NeurologyQueen SquareLondonUK
| | - Peter N. Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of ComputingNewcastle UniversityNewcastle Upon TyneUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle Upon TyneUK
- UCL Queen Square Institute of NeurologyQueen SquareLondonUK
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9
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Chowdhury FA, Islam MF, Arefin MK, Akter H, Tithy SA, Sabrin F, Mahmud F, Khan AS, Alam MT. Demographic Characteristics of Patients with Breast Cancer in Bangladesh: A Single-Centre Study. Mymensingh Med J 2023; 32:764-768. [PMID: 37391971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2023]
Abstract
We performed this study to investigate the socio-demographic factors of breast cancer patients of Bangladesh. This cross-sectional study was conducted in the Department of General Surgery at Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh from July 2018 to September 2019 for a period of one (1) year. All consecutive cases of breast carcinoma admitted in hospital and attended at outpatient department during the study period were selected as study population. Total 50 patients were selected. The mean age of the study patients was 51.1. Maximum number (70.0% cases) of breast cancer was belonged in 4th to 5th decade aged group. 70.0% breast cancer patients were housewives. The most of the breast carcinoma was reported in the urban people which were 78.0% cases. The percentage of educated study population was 80.0%. On religious background, 86.0% cases of breast cancer patients were Muslim. Most of breast cancer patients were sporadic in origin 94.0% cases, had no family history of breast cancer. Breast cancer was mostly distributed in pre-menopausal aged group with 82.0% cases. Ninety percent (90.0%) of the study population was come from middle class socio-economic group. In western countries, incidence of breast cancer is more in elderly aged menopause women with high socio-economic class. In this study the breast carcinoma was most prevalent among educated urban Muslim pre-menopausal housewives of age group 4th to 5th decade and most of them belonged to middle socio-economic class. The socio-demographic factors of breast cancer patients in Bangladesh are disparate from western countries in age standard, social class group and menstrual status.
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Affiliation(s)
- F A Chowdhury
- Dr Fatama Akter Chowdhury, Assistant Registrar, Department of Burn and Plastic, Dhaka Medical College Hospital, Dhaka, Bangladesh; E-mail:
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10
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Owen T, Janiukstyte V, Hall GR, Chowdhury FA, Diehl B, McEvoy A, Miserocchi A, de Tisi J, Duncan JS, Rugg-Gunn F, Wang Y, Taylor PN. Interictal MEG abnormalities to guide intracranial electrode implantation and predict surgical outcome. ArXiv 2023:arXiv:2304.05199v1. [PMID: 37090233 PMCID: PMC10120748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Intracranial EEG (iEEG) is the gold standard technique for epileptogenic zone (EZ) localisation, but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography (MEG). Quantitative abnormality mapping using MEG has recently been shown to have potential clinical value. We hypothesised that if quantifiable MEG abnormalities were sampled by iEEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent MEG and subsequent iEEG recordings as part of pre-surgical evaluation. Eyes-closed resting-state interictal MEG band power abnormality maps were derived from 70 healthy controls as a normative baseline. MEG abnormality maps were compared to iEEG electrode implantation, with the spatial overlap of iEEG electrode placement and cerebral MEG abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue, and subsequent resection of the strongest abnormalities determined by MEG and iEEG corresponded to surgical success. Intracranial electrodes were implanted in brain tissue with the most abnormal MEG findings - in individuals that were seizure-free post-operatively (T=3.9, p=0.003), but not in those who did not become seizure free. The overlap between MEG abnormalities and electrode placement distinguished surgical outcome groups moderately well (AUC=0.68). In isolation, the resection of the strongest abnormalities as defined by MEG and iEEG separated surgical outcome groups well, AUC=0.71, AUC=0.74 respectively. A model incorporating all three features separated surgical outcome groups best (AUC=0.80). Intracranial EEG is a key tool to delineate the EZ and help render individuals seizure-free post-operatively. We showed that data-driven abnormality maps derived from resting-state MEG recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of post-operative seizure-freedom, which leverages both MEG and iEEG recordings, could aid patient counselling of expected outcome.
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Affiliation(s)
- Tom Owen
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Vytene Janiukstyte
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Gerard R Hall
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Fahmida A Chowdhury
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Beate Diehl
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Andrew McEvoy
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Anna Miserocchi
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Jane de Tisi
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - John S Duncan
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Fergus Rugg-Gunn
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Yujiang Wang
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
| | - Peter Neal Taylor
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
- UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
- National Hospital for Neurology & Neurosurgery, Queen Square, London, WC1N 3BG, United Kingdom
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11
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Khoo A, Alim-Marvasti A, de Tisi J, Diehl B, Walker MC, Miserocchi A, McEvoy AW, Chowdhury FA, Duncan JS. Value of semiology in predicting epileptogenic zone and surgical outcome following frontal lobe epilepsy surgery. Seizure 2023; 106:29-35. [PMID: 36736149 DOI: 10.1016/j.seizure.2023.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/11/2023] [Accepted: 01/30/2023] [Indexed: 02/01/2023] Open
Abstract
OBJECTIVE To evaluate the ability of semiology alone in localising the epileptogenic zone (EZ) in people with frontal lobe epilepsy (FLE) who underwent resective surgery. METHODS We examined data on all individuals who had FLE surgery at our centre between January 01, 2011 and December 31, 2020. Descriptions of ictal semiology were obtained from video-EEG telemetry reports and presurgical multidisciplinary meeting summaries. The putative EZ was represented by the final site of resection. We assessed how well initial and combined set-of-semiologies correlated anatomically with the EZ, using a semiology visualisation tool to generate probabilistic cortical heatmaps of involvement in seizures. RESULTS Sixty-one individuals had FLE surgery over the study period. Twelve months following surgery, 28/61 (46%) were completely seizure-free, with a further eight experiencing only auras. Comparing the semiology database with the putative EZ, combined set-of-semiology correctly lateralised in 77% (95% CI: 69-85%), localised to the frontal lobe in 57% (95% CI: 48-67%), frontal lobe subregions in 52% (95% CI: 43-62%), and frontal gyri in 25% (95% CI: 16-33%). No difference in degree of correlation was seen comparing those with ongoing seizures 12 months after surgery to those seizure free. SIGNIFICANCE Semiology alone was able to correctly lateralize the putative EZ in 77%, and localise to a sublobar level in approximately half of individuals who had FLE surgery. Semiology is not adequate alone and must be combined with imaging and EEG data to identify the epileptogenic zone.
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Affiliation(s)
- Anthony Khoo
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; College of Medicine and Public Health, Flinders University, Bedford Park, SA, 5042, Australia.
| | - Ali Alim-Marvasti
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Jane de Tisi
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Beate Diehl
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; Department of Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Matthew C Walker
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Anna Miserocchi
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Andrew W McEvoy
- Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - Fahmida A Chowdhury
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK
| | - John S Duncan
- Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK; Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
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12
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Taylor PN, Papasavvas CA, Owen TW, Schroeder GM, Hutchings FE, Chowdhury FA, Diehl B, Duncan JS, McEvoy AW, Miserocchi A, de Tisi J, Vos SB, Walker MC, Wang Y. Normative brain mapping of interictal intracranial EEG to localize epileptogenic tissue. Brain 2022; 145:939-949. [PMID: 35075485 PMCID: PMC9050535 DOI: 10.1093/brain/awab380] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 08/19/2021] [Accepted: 09/03/2021] [Indexed: 11/14/2022] Open
Abstract
The identification of abnormal electrographic activity is important in a wide range of neurological disorders, including epilepsy for localizing epileptogenic tissue. However, this identification may be challenging during non-seizure (interictal) periods, especially if abnormalities are subtle compared to the repertoire of possible healthy brain dynamics. Here, we investigate if such interictal abnormalities become more salient by quantitatively accounting for the range of healthy brain dynamics in a location-specific manner. To this end, we constructed a normative map of brain dynamics, in terms of relative band power, from interictal intracranial recordings from 234 participants (21 598 electrode contacts). We then compared interictal recordings from 62 patients with epilepsy to the normative map to identify abnormal regions. We proposed that if the most abnormal regions were spared by surgery, then patients would be more likely to experience continued seizures postoperatively. We first confirmed that the spatial variations of band power in the normative map across brain regions were consistent with healthy variations reported in the literature. Second, when accounting for the normative variations, regions that were spared by surgery were more abnormal than those resected only in patients with persistent postoperative seizures (t = -3.6, P = 0.0003), confirming our hypothesis. Third, we found that this effect discriminated patient outcomes (area under curve 0.75 P = 0.0003). Normative mapping is a well-established practice in neuroscientific research. Our study suggests that this approach is feasible to detect interictal abnormalities in intracranial EEG, and of potential clinical value to identify pathological tissue in epilepsy. Finally, we make our normative intracranial map publicly available to facilitate future investigations in epilepsy and beyond.
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Affiliation(s)
- Peter N Taylor
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Christoforos A Papasavvas
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
| | - Thomas W Owen
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
| | - Gabrielle M Schroeder
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
| | - Frances E Hutchings
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
| | - Fahmida A Chowdhury
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Beate Diehl
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - John S Duncan
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Andrew W McEvoy
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Anna Miserocchi
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Jane de Tisi
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Sjoerd B Vos
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Matthew C Walker
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
| | - Yujiang Wang
- CNNP Laboratory (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle Helix, Newcastle University, Newcastle-upon-Tyne, NE4 5TG, UK
- UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery (NHNN), Queen Square, London WC1N 3BG, UK
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13
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Schroeder GM, Chowdhury FA, Cook MJ, Diehl B, Duncan JS, Karoly PJ, Taylor PN, Wang Y. Multiple mechanisms shape the relationship between pathway and duration of focal seizures. Brain Commun 2022; 4:fcac173. [PMID: 35855481 PMCID: PMC9280328 DOI: 10.1093/braincomms/fcac173] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 03/18/2022] [Accepted: 06/30/2022] [Indexed: 12/22/2022] Open
Abstract
A seizure's electrographic dynamics are characterized by its spatiotemporal evolution, also termed dynamical 'pathway', and the time it takes to complete that pathway, which results in the seizure's duration. Both seizure pathways and durations have been shown to vary within the same patient. However, it is unclear whether seizures following the same pathway will have the same duration or if these features can vary independently. We compared within-subject variability in these seizure features using (i) epilepsy monitoring unit intracranial EEG (iEEG) recordings of 31 patients (mean: 6.7 days, 16.5 seizures/subject), (ii) NeuroVista chronic iEEG recordings of 10 patients (mean: 521.2 days, 252.6 seizures/subject) and (iii) chronic iEEG recordings of three dogs with focal-onset seizures (mean: 324.4 days, 62.3 seizures/subject). While the strength of the relationship between seizure pathways and durations was highly subject-specific, in most subjects, changes in seizure pathways were only weakly to moderately associated with differences in seizure durations. The relationship between seizure pathways and durations was strengthened by seizures that were 'truncated' versions, both in pathway and duration, of other seizures. However, the relationship was weakened by seizures that had a common pathway, but different durations ('elasticity'), or had similar durations, but followed different pathways ('semblance'). Even in subjects with distinct populations of short and long seizures, seizure durations were not a reliable indicator of different seizure pathways. These findings suggest that seizure pathways and durations are modulated by multiple different mechanisms. Uncovering such mechanisms may reveal novel therapeutic targets for reducing seizure duration and severity.
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Affiliation(s)
- Gabrielle M Schroeder
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Fahmida A Chowdhury
- UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
| | - Mark J Cook
- Graeme Clark Institute and St Vincent’s Hospital, University of Melbourne, Melbourne, VIC, Australia
- Seer Medical Pty Ltd, Melbourne, VIC, Australia
| | - Beate Diehl
- UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
| | - John S Duncan
- UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
| | - Philippa J Karoly
- Graeme Clark Institute and St Vincent’s Hospital, University of Melbourne, Melbourne, VIC, Australia
- Department of Biomedical Engineering, University of Melbourne, Melbourne, VIC, Australia
- Seer Medical Pty Ltd, Melbourne, VIC, Australia
| | - Peter N Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
- UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
| | - Yujiang Wang
- Correspondence to: Dr Yujiang Wang School of Computing Newcastle University, NE4 5TG Newcastle upon Tyne, United Kingdom E-mail: yujiang.
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14
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Whatley BP, Winston JS, Allen LA, Vos SB, Jha A, Scott CA, Smith AL, Chowdhury FA, Bomanji JB, Lhatoo SD, Harper RM, Diehl B. Distinct Patterns of Brain Metabolism in Patients at Risk of Sudden Unexpected Death in Epilepsy. Front Neurol 2021; 12:623358. [PMID: 34899550 PMCID: PMC8651549 DOI: 10.3389/fneur.2021.623358] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 10/25/2021] [Indexed: 12/21/2022] Open
Abstract
Objective: To characterize regional brain metabolic differences in patients at high risk of sudden unexpected death in epilepsy (SUDEP), using fluorine-18-fluorodeoxyglucose positron emission tomography (18FDG-PET). Methods: We studied patients with refractory focal epilepsy at high (n = 56) and low (n = 69) risk of SUDEP who underwent interictal 18FDG-PET as part of their pre-surgical evaluation. Binary SUDEP risk was ascertained by thresholding frequency of focal to bilateral tonic-clonic seizures (FBTCS). A whole brain analysis was employed to explore regional differences in interictal metabolic patterns. We contrasted these findings with regional brain metabolism more directly related to frequency of FBTCS. Results: Regions associated with cardiorespiratory and somatomotor regulation differed in interictal metabolism. In patients at relatively high risk of SUDEP, fluorodeoxyglucose (FDG) uptake was increased in the basal ganglia, ventral diencephalon, midbrain, pons, and deep cerebellar nuclei; uptake was decreased in the left planum temporale. These patterns were distinct from the effect of FBTCS frequency, where increasing frequency was associated with decreased uptake in bilateral medial superior frontal gyri, extending into the left dorsal anterior cingulate cortex. Significance: Regions critical to cardiorespiratory and somatomotor regulation and to recovery from vital challenges show altered interictal metabolic activity in patients with frequent FBTCS considered to be at relatively high-risk of SUDEP, and shed light on the processes that may predispose patients to SUDEP.
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Affiliation(s)
- Benjamin P Whatley
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.,Division of Neurology, Dalhousie University, Halifax, NS, Canada
| | - Joel S Winston
- Department of Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Wellcome Trust Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom.,Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.,Department of Clinical Neurophysiology, King's College Hospital, London, United Kingdom
| | - Luke A Allen
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.,Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom.,The Center for SUDEP Research, National Institutes of Neurological Disorders and Stroke, Bethesda, MD, United States
| | - Sjoerd B Vos
- Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom.,The Center for SUDEP Research, National Institutes of Neurological Disorders and Stroke, Bethesda, MD, United States.,Neuroradiological Academic Unit, Queen Square Institute of Neurology, University College London, London, United Kingdom.,Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Ashwani Jha
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Catherine A Scott
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.,The Center for SUDEP Research, National Institutes of Neurological Disorders and Stroke, Bethesda, MD, United States
| | - April-Louise Smith
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | - Fahmida A Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Jamshed B Bomanji
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | - Samden D Lhatoo
- The Center for SUDEP Research, National Institutes of Neurological Disorders and Stroke, Bethesda, MD, United States.,Epilepsy Center, Neurological Institute, University Hospitals Case Medical Center, Cleveland, OH, United States.,Department of Neurology, University of Texas Health Sciences Center at Houston, Houston, TX, United States
| | - Ronald M Harper
- The Center for SUDEP Research, National Institutes of Neurological Disorders and Stroke, Bethesda, MD, United States.,Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Neurobiology, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA, United States
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.,Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom.,The Center for SUDEP Research, National Institutes of Neurological Disorders and Stroke, Bethesda, MD, United States
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15
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Isen J, Perera-Ortega A, Vos SB, Rodionov R, Kanber B, Chowdhury FA, Duncan JS, Mousavi P, Winston GP. Non-parametric combination of multimodal MRI for lesion detection in focal epilepsy. Neuroimage Clin 2021; 32:102837. [PMID: 34619650 PMCID: PMC8503566 DOI: 10.1016/j.nicl.2021.102837] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 09/10/2021] [Accepted: 09/20/2021] [Indexed: 12/21/2022]
Abstract
Multivariate voxel-based analysis useful for lesion detection in focal epilepsy. Non-parametric combination algorithm used to combine data from various MR sequences. Successful lesion detection demonstrated in MRI-positive and MRI-negative patients. Multimodal analysis detected abnormalities from diverse epileptogenic pathologies. Sensitivity of multivariate analysis notably higher than univariate analyses.
One third of patients with medically refractory focal epilepsy have normal-appearing MRI scans. This poses a problem as identification of the epileptogenic region is required for surgical treatment. This study performs a multimodal voxel-based analysis (VBA) to identify brain abnormalities in MRI-negative focal epilepsy. Data was collected from 69 focal epilepsy patients (42 with discrete lesions on MRI scans, 27 with no visible findings on scans), and 62 healthy controls. MR images comprised T1-weighted, fluid-attenuated inversion recovery (FLAIR), fractional anisotropy (FA) and mean diffusivity (MD) from diffusion tensor imaging, and neurite density index (NDI) from neurite orientation dispersion and density imaging. These multimodal images were coregistered to T1-weighted scans, normalized to a standard space, and smoothed with 8 mm FWHM. Initial analysis performed voxel-wise one-tailed t-tests separately on grey matter concentration (GMC), FLAIR, FA, MD, and NDI, comparing patients with epilepsy to controls. A multimodal non-parametric combination (NPC) analysis was also performed simultaneously on FLAIR, FA, MD, and NDI. Resulting p-maps were family-wise error rate corrected, threshold-free cluster enhanced, and thresholded at p < 0.05. Sensitivity was established through visual comparison of results to manually drawn lesion masks or seizure onset zone (SOZ) from stereoelectroencephalography. A leave-one-out cross-validation with the same analysis protocols was performed on controls to determine specificity. NDI was the best performing individual modality, detecting focal abnormalities in 38% of patients with normal MRI and conclusive SOZ. GMC demonstrated the lowest sensitivity at 19%. NPC provided superior performance to univariate analyses with 50% sensitivity. Specificity in controls ranged between 96 and 100% for all analyses. This study demonstrated the utility of a multimodal VBA utilizing NPC for detecting epileptogenic lesions in MRI-negative focal epilepsy. Future work will apply this approach to datasets from other centres and will experiment with different combinations of MR sequences.
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Affiliation(s)
- Jonah Isen
- School of Computing, Queen's University, Kingston, Canada
| | | | - Sjoerd B Vos
- Centre for Medical Image Computing, University College London, London, UK; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK; Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Roman Rodionov
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK
| | - Baris Kanber
- Centre for Medical Image Computing, University College London, London, UK; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK
| | - Fahmida A Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK
| | - Parvin Mousavi
- School of Computing, Queen's University, Kingston, Canada
| | - Gavin P Winston
- School of Computing, Queen's University, Kingston, Canada; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; MRI Unit, Epilepsy Society, Chalfont St Peter, UK; National Institute for Health Research Biomedical Research Centre at University College London and University College London NHS Foundation Trust, London, UK; Department of Medicine, Division of Neurology & Centre for Neuroscience Studies, Queen's University, Kingston, Canada.
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16
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Abstract
The semiology of epileptic seizures reflects activation, or dysfunction, of areas of brain (often termed the symptomatogenic zone) as a seizure begins and evolves. Specific semiologies in focal epilepsies provide an insight into the location of the seizure onset zone, which is particularly important for presurgical epilepsy assessment. The correct diagnosis of paroxysmal events also depends on the clinician being familiar with the spectrum of semiologies. Here, we summarise the current literature on localisation in focal epilepsies using illustrative cases and discussing possible pitfalls in localisation.
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Affiliation(s)
- Fahmida A Chowdhury
- Department of Epilepsy, National Hospital for Neurology and Neurosurgery, London, UK .,Department of Clinical and Experimental Epilepsy, Institute of Neurology, London, UK
| | - Rui Silva
- Department of Epilepsy, National Hospital for Neurology and Neurosurgery, London, UK
| | - Benjamin Whatley
- Department of Epilepsy, National Hospital for Neurology and Neurosurgery, London, UK.,Department of Neurology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Matthew C Walker
- Department of Epilepsy, National Hospital for Neurology and Neurosurgery, London, UK.,Department of Clinical and Experimental Epilepsy, Institute of Neurology, London, UK
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17
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Vivekananda U, Bush D, Bisby JA, Baxendale S, Rodionov R, Diehl B, Chowdhury FA, McEvoy AW, Miserocchi A, Walker MC, Burgess N. Theta power and theta-gamma coupling support long-term spatial memory retrieval. Hippocampus 2020; 31:213-220. [PMID: 33263940 PMCID: PMC7898809 DOI: 10.1002/hipo.23284] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 11/11/2020] [Accepted: 11/15/2020] [Indexed: 11/07/2022]
Abstract
Hippocampal theta oscillations have been implicated in spatial memory function in both rodents and humans. What is less clear is how hippocampal theta interacts with higher frequency oscillations to support long‐term memory. Here we asked 10 presurgical epilepsy patients undergoing intracranial EEG recording to perform a long‐term spatial memory task in desktop virtual reality and found that increased theta power in two discrete bands (“low” 2‐5 Hz and “high” 6‐11 Hz) during cued retrieval was associated with improved task performance. Similarly, increased coupling between “low” theta phase and gamma amplitude during the same period was associated with improved task performance. Finally, low and high gamma amplitude appeared to peak at different phases of the theta cycle; providing a novel connection between human hippocampal function and rodent data. These results help to elucidate the role of theta oscillations and theta‐gamma phase‐amplitude coupling in human long‐term memory.
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Affiliation(s)
- Umesh Vivekananda
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Daniel Bush
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,UCL Institute of Cognitive Neuroscience, London, UK
| | - James A Bisby
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,UCL Institute of Cognitive Neuroscience, London, UK
| | - Sallie Baxendale
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Roman Rodionov
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Fahmida A Chowdhury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Matthew C Walker
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Neil Burgess
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,UCL Institute of Cognitive Neuroscience, London, UK.,Wellcome Centre for Human NeuroImaging, University College London, London, UK
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18
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Wang Y, Sinha N, Schroeder GM, Ramaraju S, McEvoy AW, Miserocchi A, de Tisi J, Chowdhury FA, Diehl B, Duncan JS, Taylor PN. Interictal intracranial electroencephalography for predicting surgical success: The importance of space and time. Epilepsia 2020; 61:1417-1426. [PMID: 32589284 PMCID: PMC7611164 DOI: 10.1111/epi.16580] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 05/21/2020] [Accepted: 05/21/2020] [Indexed: 12/14/2022]
Abstract
Objective Predicting postoperative seizure freedom using functional correlation networks derived from interictal intracranial electroencephalography (EEG) has shown some success. However, there are important challenges to consider: (1) electrodes physically closer to each other naturally tend to be more correlated, causing a spatial bias; (2) implantation location and number of electrodes differ between patients, making cross-subject comparisons difficult; and (3) functional correlation networks can vary over time but are currently assumed to be static. Methods In this study, we address these three challenges using intracranial EEG data from 55 patients with intractable focal epilepsy. Patients additionally underwent preoperative magnetic resonance imaging (MRI), intraoperative computed tomography, and postoperative MRI, allowing accurate localization of electrodes and delineation of the removed tissue. Results We show that normalizing for spatial proximity between nearby electrodes improves prediction of postsurgery seizure outcomes. Moreover, patients with more extensive electrode coverage were more likely to have their outcome predicted correctly (area under the receiver operating characteristic curve > 0.9, P « 0.05) but not necessarily more likely to have a better outcome. Finally, our predictions are robust regardless of the time segment analyzed. Significance Future studies should account for the spatial proximity of electrodes in functional network construction to improve prediction of postsurgical seizure outcomes. Greater coverage of both removed and spared tissue allows for predictions with higher accuracy.
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Affiliation(s)
- Yujiang Wang
- CNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.,Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK.,Institute of Neurology, University College London, London, UK
| | - Nishant Sinha
- CNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.,Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK
| | - Gabrielle M Schroeder
- CNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK
| | - Sriharsha Ramaraju
- CNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK
| | - Andrew W McEvoy
- Institute of Neurology, University College London, London, UK
| | - Anna Miserocchi
- Institute of Neurology, University College London, London, UK
| | - Jane de Tisi
- Institute of Neurology, University College London, London, UK
| | | | - Beate Diehl
- Institute of Neurology, University College London, London, UK
| | - John S Duncan
- Institute of Neurology, University College London, London, UK
| | - Peter N Taylor
- CNNP lab (www.cnnp-lab.com), Interdisciplinary Complex Systems Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.,Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK.,Institute of Neurology, University College London, London, UK
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19
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Schroeder GM, Diehl B, Chowdhury FA, Duncan JS, de Tisi J, Trevelyan AJ, Forsyth R, Jackson A, Taylor PN, Wang Y. Seizure pathways change on circadian and slower timescales in individual patients with focal epilepsy. Proc Natl Acad Sci U S A 2020; 117:11048-11058. [PMID: 32366665 PMCID: PMC7245106 DOI: 10.1073/pnas.1922084117] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Personalized medicine requires that treatments adapt to not only the patient but also changing factors within each individual. Although epilepsy is a dynamic disorder characterized by pathological fluctuations in brain state, surprisingly little is known about whether and how seizures vary in the same patient. We quantitatively compared within-patient seizure network evolutions using intracranial electroencephalographic (iEEG) recordings of over 500 seizures from 31 patients with focal epilepsy (mean 16.5 seizures per patient). In all patients, we found variability in seizure paths through the space of possible network dynamics. Seizures with similar pathways tended to occur closer together in time, and a simple model suggested that seizure pathways change on circadian and/or slower timescales in the majority of patients. These temporal relationships occurred independent of whether the patient underwent antiepileptic medication reduction. Our results suggest that various modulatory processes, operating at different timescales, shape within-patient seizure evolutions, leading to variable seizure pathways that may require tailored treatment approaches.
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Affiliation(s)
- Gabrielle M Schroeder
- Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University, Newcastle upon Tyne, NE4 5TG, United Kingdom
| | - Beate Diehl
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, United Kingdom
| | - Fahmida A Chowdhury
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, United Kingdom
| | - John S Duncan
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, United Kingdom
| | - Jane de Tisi
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, United Kingdom
| | - Andrew J Trevelyan
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Rob Forsyth
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Andrew Jackson
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Peter N Taylor
- Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University, Newcastle upon Tyne, NE4 5TG, United Kingdom
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Yujiang Wang
- Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University, Newcastle upon Tyne, NE4 5TG, United Kingdom;
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
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20
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Chowdhury FA, Caciagli L, Whatley BP, McLaughlin C, Sanders B, Wehner T, Diehl B. Preoperative language mapping using navigated TMS compared with extra-operative direct cortical stimulation using intracranial electrodes: A case report. Seizure 2020; 76:96-99. [PMID: 32045870 DOI: 10.1016/j.seizure.2020.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 01/26/2020] [Accepted: 01/27/2020] [Indexed: 11/26/2022] Open
Affiliation(s)
- Fahmida A Chowdhury
- Department of Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, United Kingdom; Department of Clinical & Experimental Epilepsy, UCL, Queen Square Institute of Neurology, United Kingdom.
| | - Lorenzo Caciagli
- Department of Clinical & Experimental Epilepsy, UCL, Queen Square Institute of Neurology, United Kingdom; MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, United Kingdom; Department of Bioengineering, University of Pennsylvania, Philadelphia, United States
| | - Benjamin P Whatley
- Department of Clinical & Experimental Epilepsy, UCL, Queen Square Institute of Neurology, United Kingdom
| | - Charlotte McLaughlin
- Department of Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, United Kingdom
| | - Brett Sanders
- Department of Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, United Kingdom
| | - Tim Wehner
- Department of Neurology, Ruhr-Universität, Bochum, Germany
| | - Beate Diehl
- Department of Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, United Kingdom; Department of Clinical & Experimental Epilepsy, UCL, Queen Square Institute of Neurology, United Kingdom
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21
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Abela E, Pawley AD, Tangwiriyasakul C, Yaakub SN, Chowdhury FA, Elwes RDC, Brunnhuber F, Richardson MP. Slower alpha rhythm associates with poorer seizure control in epilepsy. Ann Clin Transl Neurol 2019; 6:333-343. [PMID: 30847365 PMCID: PMC6389754 DOI: 10.1002/acn3.710] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Accepted: 11/26/2018] [Indexed: 01/27/2023] Open
Abstract
Objective Slowing and frontal spread of the alpha rhythm have been reported in multiple epilepsy syndromes. We investigated whether these phenomena are associated with seizure control. Methods We prospectively acquired resting-state electroencephalogram (EEG) in 63 patients with focal and idiopathic generalized epilepsy (FE and IGE) and 39 age- and gender-matched healthy subjects (HS). Patients were divided into good and poor (≥4 seizures/12 months) seizure control groups based on self-reports and clinical records. We computed spectral power from 20-sec EEG segments during eyes-closed wakefulness, free of interictal abnormalities, and quantified power in high- and low-alpha bands. Analysis of covariance and post hoc t-tests were used to assess group differences in alpha-power shift across all EEG channels. Permutation-based statistics were used to assess the topography of this shift across the whole scalp. Results Compared to HS, patients showed a statistically significant shift of spectral power from high- to low-alpha frequencies (effect size g = 0.78 [95% confidence interval 0.43, 1.20]). This alpha-power shift was driven by patients with poor seizure control in both FE and IGE (g = 1.14, [0.65, 1.74]), and occurred over midline frontal and bilateral occipital regions. IGE exhibited less alpha power shift compared to FE over bilateral frontal regions (g = -1.16 [-0.68, -1.74]). There was no interaction between syndrome and seizure control. Effects were independent of antiepileptic drug load, time of day, or subgroup definitions. Interpretation Alpha slowing and anteriorization are a robust finding in patients with epilepsy and might represent a generic indicator of seizure liability.
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Affiliation(s)
- Eugenio Abela
- Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUnited Kingdom
- Department of Clinical NeurophysiologyKing's College Hospital NHS Foundation TrustLondonUnited Kingdom
| | - Adam D. Pawley
- Social, Genetic and Developmental Psychiatry Research CenterInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUnited Kingdom
| | - Chayanin Tangwiriyasakul
- Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUnited Kingdom
| | - Siti N. Yaakub
- Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUnited Kingdom
- School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUnited Kingdom
| | - Fahmida A. Chowdhury
- National Hospital for Neurology and NeurosurgeryUCL Hospitals NHS Foundation TrustLondonUnited Kingdom
| | - Robert D. C. Elwes
- Department of Clinical NeurophysiologyKing's College Hospital NHS Foundation TrustLondonUnited Kingdom
| | - Franz Brunnhuber
- Department of Clinical NeurophysiologyKing's College Hospital NHS Foundation TrustLondonUnited Kingdom
| | - Mark P. Richardson
- Department of Basic and Clinical NeuroscienceInstitute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUnited Kingdom
- Department of Clinical NeurophysiologyKing's College Hospital NHS Foundation TrustLondonUnited Kingdom
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22
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Bauer PR, de Goede AA, Stern WM, Pawley AD, Chowdhury FA, Helling RM, Bouet R, Kalitzin SN, Visser GH, Sisodiya SM, Rothwell JC, Richardson MP, van Putten MJAM, Sander JW. Long-interval intracortical inhibition as biomarker for epilepsy: a transcranial magnetic stimulation study. Brain 2018; 141:409-421. [PMID: 29340584 PMCID: PMC5837684 DOI: 10.1093/brain/awx343] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 10/08/2017] [Accepted: 10/24/2017] [Indexed: 11/13/2022] Open
Abstract
Cortical excitability, as measured by transcranial magnetic stimulation combined with electromyography, is a potential biomarker for the diagnosis and follow-up of epilepsy. We report on long-interval intracortical inhibition data measured in four different centres in healthy controls (n = 95), subjects with refractory genetic generalized epilepsy (n = 40) and with refractory focal epilepsy (n = 69). Long-interval intracortical inhibition was measured by applying two supra-threshold stimuli with an interstimulus interval of 50, 100, 150, 200 and 250 ms and calculating the ratio between the response to the second (test stimulus) and to the first (conditioning stimulus). In all subjects, the median response ratio showed inhibition at all interstimulus intervals. Using a mixed linear-effects model, we compared the long-interval intracortical inhibition response ratios between the different subject types. We conducted two analyses; one including data from the four centres and one excluding data from Centre 2, as the methods in this centre differed from the others. In the first analysis, we found no differences in long-interval intracortical inhibition between the different subject types. In all subjects, the response ratios at interstimulus intervals 100 and 150 ms showed significantly more inhibition than the response ratios at 50, 200 and 250 ms. Our second analysis showed a significant interaction between interstimulus interval and subject type (P = 0.0003). Post hoc testing showed significant differences between controls and refractory focal epilepsy at interstimulus intervals of 100 ms (P = 0.02) and 200 ms (P = 0.04). There were no significant differences between controls and refractory generalized epilepsy groups or between the refractory generalized and focal epilepsy groups. Our results do not support the body of previous work that suggests that long-interval intracortical inhibition is significantly reduced in refractory focal and genetic generalized epilepsy. Results from the second analysis are even in sharper contrast with previous work, showing inhibition in refractory focal epilepsy at 200 ms instead of facilitation previously reported. Methodological differences, especially shorter intervals between the pulse pairs, may have contributed to our inability to reproduce previous findings. Based on our results, we suggest that long-interval intracortical inhibition as measured by transcranial magnetic stimulation and electromyography is unlikely to have clinical use as a biomarker of epilepsy.
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Affiliation(s)
- Prisca R Bauer
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands
| | - Annika A de Goede
- Department of Clinical Neurophysiology, MIRA – Institute for Biomedical Technology and Technical Medicine, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
| | - William M Stern
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, SL9 0RJ, UK
| | - Adam D Pawley
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London 16 De Crespigny Park, London, SE5 8AF, UK
| | - Fahmida A Chowdhury
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London 16 De Crespigny Park, London, SE5 8AF, UK
| | - Robert M Helling
- Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands
- Image Sciences Institute, University Medical Centre Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands
| | - Romain Bouet
- Lyon Neuroscience Research Center, INSERM U1028 - CNRS UMR5292, Université Claude Bernard Lyon1, Brain Dynamics and Cognition Team, Centre Hospitalier Le Vinatier (Bât. 452), 95 Bd Pinel, 69500 Bron, France
| | - Stiliyan N Kalitzin
- Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands
- Image Sciences Institute, University Medical Centre Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands
| | - Gerhard H Visser
- Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands
| | - Sanjay M Sisodiya
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, SL9 0RJ, UK
| | - John C Rothwell
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - Mark P Richardson
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London 16 De Crespigny Park, London, SE5 8AF, UK
| | - Michel J A M van Putten
- Department of Clinical Neurophysiology, MIRA – Institute for Biomedical Technology and Technical Medicine, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
- Department of Clinical Neurophysiology and Neurology, Medisch Spectrum Twente, Koningsplein 1, 7512 KZ Enschede, The Netherlands
| | - Josemir W Sander
- NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Stichting Epilepsie Instellingen Nederland (SEIN), Achterweg 5, 2103 SW Heemstede, The Netherlands
- Chalfont Centre for Epilepsy, Chalfont St Peter, SL9 0RJ, UK
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23
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Pawley AD, Chowdhury FA, Tangwiriyasakul C, Ceronie B, Elwes RDC, Nashef L, Richardson MP. Cortical excitability correlates with seizure control and epilepsy duration in chronic epilepsy. Ann Clin Transl Neurol 2017; 4:87-97. [PMID: 28168208 PMCID: PMC5288462 DOI: 10.1002/acn3.383] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Revised: 11/06/2016] [Accepted: 11/08/2016] [Indexed: 11/30/2022] Open
Abstract
Objective Cortical excitability differs between treatment responders and nonresponders in new‐onset epilepsy. Moreover, during the first 3 years of epilepsy, cortical excitability becomes more abnormal in nonresponders but normalizes in responders. Here, we study chronic active epilepsy, to examine whether cortical excitability continues to evolve over time, in association with epilepsy duration and treatment response. Methods We studied 28 normal subjects, 28 patients with moderately controlled epilepsy (≤4 seizures per year) and 40 patients with poorly controlled epilepsy (≥20 or more seizures per year). Resting motor threshold (RMT), active motor threshold (AMT), short‐interval intracortical inhibition (SICI), intracortical facilitation (ICF) and cortical silent period (CSP) were measured, using transcranial magnetic stimulation (TMS). Disease and treatment covariates were collected (age at onset of epilepsy, epilepsy duration, number of drugs prescribed, total drug load, sodium channel drug load). Results RMT and AMT were higher in patients than in normal subjects; RMT and AMT were higher in poorly controlled than moderately controlled patients. ICF at 12 msec and 15 msec were lower in poorly controlled patients than in normal subjects. Long‐interval intracortical inhibition (LICI) at 50 msec was higher in poorly controlled compared to moderately controlled patients. These differences were not explained by antiepileptic drug (AED) treatment or duration of epilepsy. RMT and AMT increased with duration in the poorly controlled group, but did not increase with duration in the moderately controlled group. Interpretation Cortical excitability differs markedly between moderately controlled and poorly controlled patients with chronic epilepsy, not explained by disease or treatment variables. Moreover, the evolution of cortical excitability over time differs, becoming more abnormal in the poorly controlled group.
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Affiliation(s)
- Adam D Pawley
- Department of Basic and Clinical Neuroscience King's College London London United Kingdom
| | - Fahmida A Chowdhury
- Department of Basic and Clinical Neuroscience King's College London London United Kingdom
| | | | - Bryan Ceronie
- Department of Basic and Clinical Neuroscience King's College London London United Kingdom
| | - Robert D C Elwes
- Centre for Epilepsy King's College Hospital London United Kingdom
| | - Lina Nashef
- Centre for Epilepsy King's College Hospital London United Kingdom
| | - Mark P Richardson
- Department of Basic and Clinical Neuroscience King's College London London United Kingdom
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Abstract
The clinical diagnosis of Brown-Vialetto-Van Laere syndrome in this woman with rapidly progressive pontobulbar palsy led to empirical high-dose oral riboflavin (1200 mg/day) therapy. This resulted in a dramatic improvement in her motor function from being anarthric, dysphagic, tetraparetic and in ventilatory failure to living independently with mild dysarthria and distal limb weakness. DNA sequencing of the SLC52A3 gene found compound heterozygous C-terminus mutations, V413A1/D461Y, consistent with recent reports of mutations within the riboflavin transporter genes (SLC52A2 and SLC52A3) in this condition. Early diagnosis and empirical riboflavin therapy can lead to major motor recovery in this condition, that can be sustained with long-term maintenance therapy.
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Affiliation(s)
- James A Bashford
- Maurice Wohl Clinical Neuroscience Institute, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
| | - Fahmida A Chowdhury
- Neurology Department, St George's University Hospitals NHS Foundation Trust, London, UK
| | - Chris E Shaw
- Maurice Wohl Clinical Neuroscience Institute, King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK
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25
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Schmidt H, Woldman W, Goodfellow M, Chowdhury FA, Koutroumanidis M, Jewell S, Richardson MP, Terry JR. A computational biomarker of idiopathic generalized epilepsy from resting state EEG. Epilepsia 2016; 57:e200-e204. [PMID: 27501083 PMCID: PMC5082517 DOI: 10.1111/epi.13481] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/05/2016] [Indexed: 01/19/2023]
Abstract
Epilepsy is one of the most common serious neurologic conditions. It is characterized by the tendency to have recurrent seizures, which arise against a backdrop of apparently normal brain activity. At present, clinical diagnosis relies on the following: (1) case history, which can be unreliable; (2) observation of transient abnormal activity during electroencephalography (EEG), which may not be present during clinical evaluation; and (3) if diagnostic uncertainty occurs, undertaking prolonged monitoring in an attempt to observe EEG abnormalities, which is costly. Herein, we describe the discovery and validation of an epilepsy biomarker based on computational analysis of a short segment of resting-state (interictal) EEG. Our method utilizes a computer model of dynamic networks, where the network is inferred from the extent of synchrony between EEG channels (functional networks) and the normalized power spectrum of the clinical data. We optimize model parameters using a leave-one-out classification on a dataset comprising 30 people with idiopathic generalized epilepsy (IGE) and 38 normal controls. Applying this scheme to all 68 subjects we find 100% specificity at 56.7% sensitivity, and 100% sensitivity at 65.8% specificity. We believe this biomarker could readily provide additional support to the diagnostic process.
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Affiliation(s)
- Helmut Schmidt
- College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter, United Kingdom.,Wellcome Trust ISSF Centre for Biomedical Modelling and Analysis, University of Exeter, Exeter, United Kingdom.,EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom
| | - Wessel Woldman
- College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter, United Kingdom.,Wellcome Trust ISSF Centre for Biomedical Modelling and Analysis, University of Exeter, Exeter, United Kingdom.,EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom
| | - Marc Goodfellow
- College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter, United Kingdom.,Wellcome Trust ISSF Centre for Biomedical Modelling and Analysis, University of Exeter, Exeter, United Kingdom.,EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom
| | - Fahmida A Chowdhury
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Michalis Koutroumanidis
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.,Department of EEG and Epilepsy, St. Thomas's Hospital, Guy's and St. Thomas's NHS Foundation Trust, London, United Kingdom
| | - Sharon Jewell
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Mark P Richardson
- EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom.,Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - John R Terry
- College of Engineering, Mathematics & Physical Sciences, University of Exeter, Exeter, United Kingdom. .,Wellcome Trust ISSF Centre for Biomedical Modelling and Analysis, University of Exeter, Exeter, United Kingdom. .,EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom.
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26
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Chowdhury FA, Connor S, Ferner R, Leschziner G. Focal inhibitory seizures: a cause of recurrent transient weakness. Pract Neurol 2015; 15:460-2. [DOI: 10.1136/practneurol-2014-001017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/13/2015] [Indexed: 11/03/2022]
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27
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Kibria MG, Chowdhury FA, Trudeau ML, Guo H, Mi Z. Dye-sensitized InGaN nanowire arrays for efficient hydrogen production under visible light irradiation. Nanotechnology 2015; 26:285401. [PMID: 26120103 DOI: 10.1088/0957-4484/26/28/285401] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Solar water splitting is a key sustainable energy technology for clean, storable and renewable source of energy in the future. Here we report that Merocyanine-540 dye-sensitized and Rh nanoparticle-decorated molecular beam epitaxially grown In0.25Ga0.75N nanowire arrays have produced hydrogen from ethylenediaminetetraacetic acid (EDTA) and acetonitrile mixture solution under green, yellow and orange solar spectra (up to 610 nm) for the first time. An apparent quantum efficiency of 0.3% is demonstrated for wavelengths 525-600 nm, providing a viable approach to harness deep-visible and near-infrared solar energy for efficient and stable water splitting.
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Affiliation(s)
- M G Kibria
- Department of Electrical and Computer Engineering, McGill University, 3480 University Street, Montreal, Québec H3A 0E9, Canada
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28
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Chowdhury FA, Pawley AD, Ceronie B, Nashef L, Elwes RDC, Richardson MP. Motor evoked potential polyphasia: a novel endophenotype of idiopathic generalized epilepsy. Neurology 2015; 84:1301-7. [PMID: 25740859 PMCID: PMC4388750 DOI: 10.1212/wnl.0000000000001413] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Objective: We compared the motor evoked potential (MEP) phases using transcranial magnetic stimulation in patients with idiopathic generalized epilepsy (IGE), their relatives, and healthy controls, hypothesizing that patients and their unaffected relatives may share a subtle pathophysiologic abnormality. Methods: In a cross-sectional study, we investigated 23 patients with IGE, 34 first-degree relatives, and 30 matched healthy controls. Transcranial magnetic stimulation was performed to produce a series of suprathreshold single-pulse MEPs. A semiautomated method was used to count phases. We compared between groups the mean number of MEP phases, the stimulus-to-stimulus variability in MEP phases, and the proportion of polyphasic MEPs within subjects. Results: Patients with IGE and their relatives had a significantly increased number of MEP phases (median for patients 2.24, relatives 2.17, controls 2.01) and a significantly higher proportion of MEPs with more than 2 phases than controls (median for patients 0.118, relatives 0.088, controls 0.013). Patients had a greater stimulus-to-stimulus variability in number of MEP phases than controls. There were no differences between patients and relatives. Conclusion: Increased MEP polyphasia in patients with IGE and their first-degree relatives may reflect transient abnormal evoked oscillations. The presence of polyphasic MEPs in relatives as well as patients suggests that MEP polyphasia is not related to treatment, and is in isolation insufficient to predispose to epilepsy. Polyphasic MEP may be a novel endophenotype in IGE.
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Affiliation(s)
- Fahmida A Chowdhury
- From the Department of Clinical Neuroscience (F.A.C., A.D.P., B.C., M.P.R.) and Centre for Epilepsy (L.N., R.D.C.E.), King's College London, UK
| | - Adam D Pawley
- From the Department of Clinical Neuroscience (F.A.C., A.D.P., B.C., M.P.R.) and Centre for Epilepsy (L.N., R.D.C.E.), King's College London, UK.
| | - Bryan Ceronie
- From the Department of Clinical Neuroscience (F.A.C., A.D.P., B.C., M.P.R.) and Centre for Epilepsy (L.N., R.D.C.E.), King's College London, UK
| | - Lina Nashef
- From the Department of Clinical Neuroscience (F.A.C., A.D.P., B.C., M.P.R.) and Centre for Epilepsy (L.N., R.D.C.E.), King's College London, UK
| | - Robert D C Elwes
- From the Department of Clinical Neuroscience (F.A.C., A.D.P., B.C., M.P.R.) and Centre for Epilepsy (L.N., R.D.C.E.), King's College London, UK
| | - Mark P Richardson
- From the Department of Clinical Neuroscience (F.A.C., A.D.P., B.C., M.P.R.) and Centre for Epilepsy (L.N., R.D.C.E.), King's College London, UK
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29
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Chowdhury FA, Woldman W, FitzGerald THB, Elwes RDC, Nashef L, Terry JR, Richardson MP. Revealing a brain network endophenotype in families with idiopathic generalised epilepsy. PLoS One 2014; 9:e110136. [PMID: 25302690 PMCID: PMC4193864 DOI: 10.1371/journal.pone.0110136] [Citation(s) in RCA: 76] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2014] [Accepted: 09/17/2014] [Indexed: 12/16/2022] Open
Abstract
Idiopathic generalised epilepsy (IGE) has a genetic basis. The mechanism of seizure expression is not fully known, but is assumed to involve large-scale brain networks. We hypothesised that abnormal brain network properties would be detected using EEG in patients with IGE, and would be manifest as a familial endophenotype in their unaffected first-degree relatives. We studied 117 participants: 35 patients with IGE, 42 unaffected first-degree relatives, and 40 normal controls, using scalp EEG. Graph theory was used to describe brain network topology in five frequency bands for each subject. Frequency bands were chosen based on a published Spectral Factor Analysis study which demonstrated these bands to be optimally robust and independent. Groups were compared, using Bonferroni correction to account for nonindependent measures and multiple groups. Degree distribution variance was greater in patients and relatives than controls in the 6-9 Hz band (p = 0.0005, p = 0.0009 respectively). Mean degree was greater in patients than healthy controls in the 6-9 Hz band (p = 0.0064). Clustering coefficient was higher in patients and relatives than controls in the 6-9 Hz band (p = 0.0025, p = 0.0013). Characteristic path length did not differ between groups. No differences were found between patients and unaffected relatives. These findings suggest brain network topology differs between patients with IGE and normal controls, and that some of these network measures show similar deviations in patients and in unaffected relatives who do not have epilepsy. This suggests brain network topology may be an inherited endophenotype of IGE, present in unaffected relatives who do not have epilepsy, as well as in affected patients. We propose that abnormal brain network topology may be an endophenotype of IGE, though not in itself sufficient to cause epilepsy.
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Affiliation(s)
- Fahmida A. Chowdhury
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Centre for Epilepsy, King's College Hospital, London, United Kingdom
| | - Wessel Woldman
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
| | - Thomas H. B. FitzGerald
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Wellcome Trust Centre for Neuroimaging, UCL, London, United Kingdom
| | | | - Lina Nashef
- Centre for Epilepsy, King's College Hospital, London, United Kingdom
| | - John R. Terry
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
| | - Mark P. Richardson
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Centre for Epilepsy, King's College Hospital, London, United Kingdom
- * E-mail:
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30
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Chowdhury FA, Elwes RDC, Koutroumanidis M, Morris RG, Nashef L, Richardson MP. Impaired cognitive function in idiopathic generalized epilepsy and unaffected family members: An epilepsy endophenotype. Epilepsia 2014; 55:835-40. [DOI: 10.1111/epi.12604] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/20/2014] [Indexed: 01/28/2023]
Affiliation(s)
- Fahmida A. Chowdhury
- Department of Clinical Neuroscience; Institute of Psychiatry; King's College London; London United Kingdom
| | | | | | - Robin G. Morris
- Department of Psychology; Institute of Psychiatry; King's College London; London United Kingdom
| | - Lina Nashef
- Centre for Epilepsy; King's College Hospital; London United Kingdom
| | - Mark P. Richardson
- Department of Clinical Neuroscience; Institute of Psychiatry; King's College London; London United Kingdom
- Centre for Epilepsy; King's College Hospital; London United Kingdom
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31
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Chowdhury FA, O'Gorman RL, Nashef L, Elwes RD, Edden RA, Murdoch JB, Barker GJ, Richardson MP. Investigation of glutamine and GABA levels in patients with idiopathic generalized epilepsy using MEGAPRESS. J Magn Reson Imaging 2014; 41:694-9. [PMID: 24585443 DOI: 10.1002/jmri.24611] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2013] [Accepted: 02/11/2014] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Idiopathic generalized epilepsies (IGE) comprise a group of clinical syndromes associated with spike wave discharges, putatively linked to alterations in neurotransmission. The purpose of this study was to investigate whether patients with IGE have altered glutamine and γ-aminobutyric acid (GABA) levels indicative of altered excitatory and inhibitory neurotransmission in frontal regions. MATERIALS AND METHODS Single-voxel MEGA-edited PRESS magnetic resonance imaging (MRI) spectra were acquired from a 30-mL voxel in the dorsolateral prefrontal cortex in 13 patients with IGE (8 female) and 16 controls (9 female) at 3T. Metabolite concentrations were derived using LCModel. Differences between groups were investigated using an unpaired t-test. RESULTS Patients with IGE were found to have significantly higher glutamine than controls (P = 0.02). GABA levels were also elevated in patients with IGE (P = 0.03). CONCLUSION Patients with IGE have increased frontal glutamine and GABA compared with controls. Since glutamine has been suggested to act as a surrogate for metabolically active glutamate, it may represent a marker for excitatory neurotransmission.
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Affiliation(s)
- Fahmida A Chowdhury
- Department of Clinical Neuroscience Institute of Psychiatry, King's College London, London, UK
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Goodhand JR, Kamperidis N, Sirwan B, Macken L, Tshuma N, Koodun Y, Chowdhury FA, Croft NM, Direkze N, Langmead L, Irving PM, Rampton DS, Lindsay JO. Factors associated with thiopurine non-adherence in patients with inflammatory bowel disease. Aliment Pharmacol Ther 2013; 38:1097-108. [PMID: 24099471 DOI: 10.1111/apt.12476] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2013] [Revised: 06/05/2013] [Accepted: 08/15/2013] [Indexed: 12/22/2022]
Abstract
BACKGROUND Medication non-adherence seems to be a particular problem in younger patients with inflammatory bowel disease (IBD) and has a negative impact on disease outcome. AIMS To assess whether non-adherence, defined using thiopurine metabolite levels, is more common in young adults attending a transition clinic than adults with IBD and whether psychological co-morbidity is a contributing factor. We also determined the usefulness of the Modified Morisky 8-item Adherence Scale (MMAS-8) to detect non-adherence. METHODS Seventy young adults [51% (36) male] and 74 [62% (46) male] adults were included. Psychological co-morbidity was assessed using the Hospital Anxiety Depression Scale (HADS) and self-reported adherence using the MMAS-8. RESULTS Twelve percent (18/144) of the patients were non-adherent. Multivariate analysis [OR, (95% CI), P value] confirmed that being young adult [6.1 (1.7-22.5), 0.001], of lower socio-economic status [1.1 (1.0-1.1), <0.01] and reporting higher HADS-D scores [1.2 (1.0-1.4), 0.01] were associated with non-adherence. Receiver operator curve analysis of MMAS-8 scores gave an area under the curve (95% CI) of 0.85 (0.77-0.92), (P < 0.0001): using a cut-off of <6, the MMAS-8 score has a sensitivity of 94% and a specificity of 64% to predict thiopurine non-adherence. Non-adherence was associated with escalation in therapy, hospital admission and surgeries in the subsequent 6 months of follow up. CONCLUSIONS Non-adherence to thiopurines is more common in young adults with inflammatory bowel disease, and is associated with lower socio-economic status and depression. The high negative predictive value of MMAS-8 scores <6 suggests that it could be a useful screen for thiopurine non-adherence.
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Affiliation(s)
- J R Goodhand
- Centre for Digestive Diseases, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
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Apu AS, Chowdhury FA, Khatun F, Jamaluddin ATM, Pathan AH, Pal A. Phytochemical Screening and In vitro Evaluation of Pharmacological Activities of <i>Aphanamixis polystachya</i> (Wall) Parker Fruit Extracts. TROP J PHARM RES 2013. [DOI: 10.4314/tjpr.v12i1.18] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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Abstract
We develop a technique that now enables surface plasmon polaritons (SPPs) coupled by nano-patterned slits in a metal film to be detected using conventional optical microscopy with standard objective lenses. The crux of this method is an ultra-thin polymer layer on the metal surface, whose thickness can be varied over a nanoscale range to enable controllable tuning of the SPP momentum. At an optimal layer thickness for which the SPP momentum matches the momentum of light emerging from the slit, the SPP coupling efficiency is enhanced about six times relative to that without the layer. The enhanced efficiency results in distinctive and bright plasmonic signatures near the slit visible by naked eye under an optical microscope. We demonstrate how this capability can be used for parallel measurement through a simple experiment in which the SPP propagation distance is extracted from a single microscope image of an illuminated array of nano-patterned slits on a metal surface. We also use optical microscopy to image the focal region of a plasmonic lens and obtain results consistent with a previously-reported results using near-field optical microscopy. Measurement of SPPs near a nano-slit using conventional and widely-available optical microscopy is an important step towards making nano-plasmonic device technology highly accessible and easy-to-use.
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Affiliation(s)
- R Mehfuz
- School of Engineering, The University of British Columbia, Kelowna, British Columbia, Canada
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Siddique MA, Rahman KM, Muazzam N, Hossain T, Islam KM, Rahman MA, Chowdhury FA, Ali CM. Study on Mycobacterium tuberculosis: the primary drug resistance pattern. Bangladesh Med Res Counc Bull 1995; 21:18-23. [PMID: 7575339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The study was carried out to investigate the primary drug resistance pattern of tubercle bacilli isolated from the pulmonary tuberculosis patient attended in Shyamoli TB clinic, Dhaka. Sputum from 961 suspected tuberculous patients were randomly collected and stained by Ziehl-Neelsen (Z.N) stain. 135 were microscopically positive for Acid Fast Bacilli (AFB). Among them 30 patients were excluded from the study as they received antitubercular treatment before. So only 105 microscopically positive cases were cultured on Lowenstein-Jensen (L-J) media and 100 showed pure growth and rest 5 were contaminated with fungus. These 100 cases were studied on 4 antitubercular drugs. Out of these 100 isolates, 91 were M. tuberculosis and rest 9 in the nonchromogen group of mycobacteria other than tuberculosis (MOTT) species. Among 91 M. tuberculosis species, 89 (97.80%) to Isoniazid (INH), 73 (80.21%) to Rifampicin (RMP) and 91 (100%) to Streptomycin (SM) and Ethambutol (ETHM) were sensitive. Of the 9 MOTT species, 4 (44.44%) to SM, 7 (77.78%) to ETHM were sensitive and all (100%) were resistant to INH and RMP. Among the 100 isolates, 27 (18 M. tuberculosis and 9 MOTT) were resistant to 4 drugs either single or in combination. Of the 18 (66.67%) M. tuberculosis species, 16 (59.26%) to RMP, and 2 (7.41%) to RMP and INH were resistant. Of the 9 (33.33%) MOTT species, 4 (14.81%) to RMP and INH, 3 (11.11%) to RMP, INH and SM and 2 (7.41%) to RMP, INH, SM and ETHM were resistant.
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Affiliation(s)
- M A Siddique
- Deptt. of Microbiology, Dhaka Medical College, Bangladesh
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Chowdhury FA, Miah RA, Begum M, Rahman KM. The transformation in vitro of peripheral lymphocytes of malnourished children. Bangladesh Med Res Counc Bull 1993; 19:67-70. [PMID: 8161338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Children with protein energy malnutrition showed high deranged cellular immunity as evidenced by impairment of lymphocyte transformation after stimulation by phytohaemagglutination (PHA). The proliferative response (PR) to PHA measured by estimating incorporation of tritiated thymidine into newly synthesized DNA. In-vitro proliferative response to PHA was used as a marker for studying the functional characteristics of T lymphocytes of children with different categories of malnutrition. PHA response of peripheral blood lymphocytes obtained from different categories of severely malnourished children were significantly low compared to healthy control children (P < 0.01). The results indicate that cell mediated immunity was grossly depressed in severe malnutrition.
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Affiliation(s)
- F A Chowdhury
- Department of Pathology and Microbiology, Sir Salimullah Medical College
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