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Sablik M, Fleury MN, Binding LP, Carey DP, d'Avossa G, Baxendale S, Winston GP, Duncan JS, Sidhu MK. Long-term neuroplasticity in language networks after anterior temporal lobe resection. Epilepsia 2024. [PMID: 39503631 DOI: 10.1111/epi.18147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2024] [Revised: 09/27/2024] [Accepted: 09/30/2024] [Indexed: 11/08/2024]
Abstract
OBJECTIVE Anterior temporal lobe resection (ATLR) is an effective treatment for drug-resistant temporal lobe epilepsy (TLE), although language deficits may occur after both left and right ATLR. Functional reorganization of the language network has been observed in the ipsilateral and contralateral hemispheres within 12 months after ATLR, but little is known of longer-term plasticity effects. Our aim was to examine the plasticity of language functions up to a decade after ATLR, in relation to cognitive profiles. METHODS We examined 24 TLE patients (12 left [LTLE]) and 10 controls across four time points: pre-surgery, 4 months, 12 months, and ~9 years post-ATLR. Participants underwent standard neuropsychological assessments (naming, phonemic, and categorical fluency tests) and a verbal fluency functional magnetic resonance imaging (fMRI) task. Using a flexible factorial design, we analyzed longitudinal fMRI activations from 12 months to ~9 years post-ATLR, relative to controls, with separate analyses for people with hippocampal sclerosis (HS). Change in cognitive profiles was correlated with the long-term change in fMRI activations to determine the "efficiency" of reorganized networks. RESULTS LTLE patients had increased long-term engagement of the left extra-temporal and contralateral temporal regions, with better language performance linked to bilateral activation. Those with HS exhibited more widespread bilateral activations. RTLE patients showed plasticity in the left extra-temporal regions, with better language outcomes associated with these areas. Both groups of patients achieved cognitive stability over 9 years, with more than 50% of LTLE patients improving. Older age, longer epilepsy duration, and lower pre-operative cognitive reserve negatively affected long-term language performance. SIGNIFICANCE Neuroplasticity continues for up to ~9 years post-epilepsy surgery in LTLE and RTLE, with effective language recovery linked to bilateral engagement of temporal and extra-temporal regions. This adaptive reorganization is associated with improved cognitive outcomes, challenging the traditional view of localized surgery effects. These findings emphasize the need for early intervention, tailored pre-operative counseling, and the potential for continued cognitive gains with extended post-ATLR rehabilitation.
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Affiliation(s)
- Maria Sablik
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St. Peter, UK
- College of Medicine and Health, Cognitive Neuroscience Institute, Bangor University, Bangor, UK
| | - Marine N Fleury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St. Peter, UK
| | - Lawrence P Binding
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St. Peter, UK
- Department of Computer Science, UCL Centre for Medical Image Computing, London, UK
| | - David P Carey
- Department of Computer Science, UCL Centre for Medical Image Computing, London, UK
| | - Giovanni d'Avossa
- Department of Computer Science, UCL Centre for Medical Image Computing, London, UK
| | - Sallie Baxendale
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St. Peter, UK
| | - Gavin P Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St. Peter, UK
- Division of Neurology, Department of Medicine, Queen's University, Kingston, Ontario, Canada
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St. Peter, UK
| | - Meneka K Sidhu
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St. Peter, UK
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Crespo Pimentel B, Kuchukhidze G, Xiao F, Caciagli L, Hoefler J, Rainer L, Kronbichler M, Vollmar C, Duncan JS, Trinka E, Koepp MJ, Wandschneider B. Quantitative MRI Measures and Cognitive Function in People With Drug-Resistant Juvenile Myoclonic Epilepsy. Neurology 2024; 103:e209802. [PMID: 39303180 PMCID: PMC11446167 DOI: 10.1212/wnl.0000000000209802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Neuroimaging studies have so far identified structural changes in individuals with juvenile myoclonic epilepsy (JME) when compared with controls. However, the underlying mechanisms of drug-resistant JME remain unknown. In this study, we aimed at characterizing the structural underpinnings of drug-resistant JME using MRI-derived cortical morphologic markers. METHODS In this prospective cross-sectional 2-center study, T1-weighted MRI and neuropsychological measures of verbal memory and executive function were obtained in individuals with drug-resistant and drug-responsive JME recruited from epilepsy outpatient clinics and healthy controls. We performed vertexwise measurements of cortical thickness, surface area, and local gyrification index (LGI). Vertexwise group comparisons were corrected for multiple comparisons at a familywise error (FWE) of 0.05. The neuropsychological profile of disease subgroups was analyzed through principal component analysis. RESULTS We studied 42 individuals with drug-resistant JME (mean age 29 ± 11 years, 50% female), 37 with drug-responsive JME (mean age 34 ± 10, years, 59% female), and 71 healthy controls (mean age 21 ± 9 years, 61% female). Surface area was increased in participants with drug-resistant JME in the left temporal lobe (Cohen d = 0.82 [-0.52 to -1.12], pFWE < 0.05) when compared with the drug-responsive group. Although no cortical thickness changes were observed between disease subgroups, drug-resistant and drug-sensitive participants showed discrete cortical thinning against controls (Cohen d = -0.42 [-0.83 to -0.01], pFWE < 0.05; Cohen d = -0.57 [-1.03 to -0.11], pFWE < 0.05, respectively). LGI was increased in the left temporal and occipital lobes in drug-resistant participants (Cohen d = 0.60 [0.34-0.86], pFWE < 0.05) when contrasting against drug-sensitive participants, but not controls. The composite executive function score was reduced in drug-resistant individuals compared with controls and drug-sensitive individuals (-1.74 [-2.58 to -0.90], p < 0.001 and -1.29 [-2.25 to -0.33], p < 0.01, respectively). Significant correlations were observed between executive function impairment and increased surface area in the precuneus and medial prefrontal regions (r = -0.79, pFWE < 0.05) in participants with drug-resistant JME. DISCUSSION We identified a developmental phenotype in individuals with drug-resistant JME characterized by changes in cortical surface area and folding complexity, the extent of which correlates with executive dysfunction. No association was observed between cortical thickness and disease severity. Our findings support a neurodevelopmental basis for drug resistance and cognitive impairment in JME.
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Affiliation(s)
- Bernardo Crespo Pimentel
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - Giorgi Kuchukhidze
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - Fenglai Xiao
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - Lorenzo Caciagli
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - Julia Hoefler
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - Lucas Rainer
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - Martin Kronbichler
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - Christian Vollmar
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - John S Duncan
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - Eugen Trinka
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - Matthias J Koepp
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
| | - Britta Wandschneider
- From the Department of Neurology, Neurointensive Care and Neurorehabilitation (B.C.P., G.K., J.H., L.R., E.T.), Neuroscience Institute (B.C.P., G.K., J.H., M.K., E.T.), and Department of Child and Adolescent Psychiatry (L.R.), Christian Doppler University Hospital, Paracelsus Medical University, Centre for Neuroscience Salzburg, Member of the European Reference Network, EpiCARE, Austria; Department of Clinical & Experimental Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), UCL Queen Square Institute of Neurology, London; Chalfont Centre for Epilepsy (B.C.P., F.X., L.C., J.S.D., M.J.K., B.W.), Chalfont St. Peter, United Kingdom; Department of Neurology (L.C.), Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Switzerland; Department of Psychology (M.K.), University of Salzburg, Austria; Department of Neurology (C.V.), Epilepsy Center, University Hospital of the Ludwig-Maximilians-University of Munich, Germany; Department of Public Health, Health Services Research and Health Technology Assessment (E.T.), UMIT-University of Health Sciences, Medical Informatics and Technology, Hall in Tirol; and Karl Landsteiner Institute for Neurorehabilitation and Space Neurology (E.T.), Salzburg, Austria
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Phillips KHT, Patterson K, Butler CR, Woodberry E, Ralph MAL, Cope TE. Does epilepsy differentially affect different types of memory? Seizure 2024; 121:217-225. [PMID: 39243667 DOI: 10.1016/j.seizure.2024.08.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Accepted: 08/23/2024] [Indexed: 09/09/2024] Open
Abstract
Despite the recognition that epilepsy can substantially disrupt memory, there are few published accounts of whether and how this disruption varies across different types of memory and/or different types of epilepsy. This review explores four main questions: (1) Are working, episodic and semantic memory differentially affected by epilepsy? (2) Do various types of epilepsy, and their treatment, have different, specifiable effects on memory? (3) Are the usual forms of neuropsychological assessments of memory - many or most designed for other conditions - appropriate for patients with epilepsy? (4) How can research on epilepsy contribute to our understanding of the neuroscience of memory? We conclude that widespread and multifactorial problems are seen in working memory in all patient groups, while patients with temporal lobe epilepsy seem particularly prone to episodic memory deficit, and those with frontal lobe epilepsy to executive function deficits that may in turn impair semantic control. Currently, it is difficult to make individual patient predictions about likely memory deficits based on seizure aetiology and type, but it is possible to guide and tailor neuropsychological assessments in an individualised way. We make recommendations for future directions in validating and optimising neuropsychological assessments, and consider how to approach effective shared decision making about the pros and cons of seizure treatment strategies, especially at crucial educational stages such as adolescence.
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Affiliation(s)
| | - Karalyn Patterson
- Cambridge University Hospitals, Cambridge, UK; MRC Cognition and Brain Sciences Unit, Cambridge, UK
| | | | | | - Matthew A Lambon Ralph
- Cambridge University Hospitals, Cambridge, UK; MRC Cognition and Brain Sciences Unit, Cambridge, UK
| | - Thomas E Cope
- Cambridge University Hospitals, Cambridge, UK; MRC Cognition and Brain Sciences Unit, Cambridge, UK
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4
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Larivière S, Schaper FLWVJ, Royer J, Rodríguez-Cruces R, Xie K, DeKraker J, Ngo A, Sahlas E, Chen J, Tavakol S, Drew W, Morton-Dutton M, Warren AEL, Baratono SR, Rolston JD, Weng Y, Bernasconi A, Bernasconi N, Concha L, Zhang Z, Frauscher B, Bernhardt BC, Fox MD. Brain Networks for Cortical Atrophy and Responsive Neurostimulation in Temporal Lobe Epilepsy. JAMA Neurol 2024; 81:2824204. [PMID: 39348148 DOI: 10.1001/jamaneurol.2024.2952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Importance Drug-resistant temporal lobe epilepsy (TLE) has been associated with hippocampal pathology. Most surgical treatment strategies, including resection and responsive neurostimulation (RNS), focus on this disease epicenter; however, imaging alterations distant from the hippocampus, as well as emerging data from responsive neurostimulation trials, suggest conceptualizing TLE as a network disorder. Objective To assess whether brain networks connected to areas of atrophy in the hippocampus align with the topography of distant neuroimaging alterations and RNS response. Design, Setting, and Participants This retrospective case-control study was conducted between July 2009 and June 2022. Data collection for this multicenter, population-based study took place across 4 tertiary referral centers in Montréal, Canada; Querétaro, México; Nanjing, China; and Salt Lake City, Utah. Eligible patients were diagnosed with TLE according to International League Against Epilepsy criteria and received either neuroimaging or neuroimaging and RNS to the hippocampus. Patients with encephalitis, traumatic brain injury, or bilateral TLE were excluded. Main Outcomes and Measures Spatial alignment between brain network topographies. Results Of the 110 eligible patients, 94 individuals diagnosed with TLE were analyzed (51 [54%] female; mean [SD] age, 31.3 [10.9] years). Hippocampal thickness maps in TLE were compared to 120 healthy control individuals (66 [55%] female; mean [SD] age, 29.8 [9.5] years), and areas of atrophy were identified. Using an atlas of normative connectivity (n = 1000), 2 brain networks were identified that were functionally connected to areas of hippocampal atrophy. The first network was defined by positive correlations to temporolimbic, medial prefrontal, and parietal regions, whereas the second network by negative correlations to frontoparietal regions. White matter changes colocalized to the positive network (t93 = -3.82; P = 2.44 × 10-4). In contrast, cortical atrophy localized to the negative network (t93 = 3.54; P = 6.29 × 10-3). In an additional 38 patients (20 [53%] female; mean [SD] age, 35.8 [11.3] years) treated with RNS, connectivity between the stimulation site and atrophied regions within the negative network was associated with seizure reduction (t212 = -2.74; P = .007). Conclusions and Relevance The findings in this study indicate that distributed pathology in TLE may occur in brain networks connected to the hippocampal epicenter. Connectivity to these same networks was associated with improvement following RNS. A network approach to TLE may reveal therapeutic targets outside the traditional target in the hippocampus.
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Affiliation(s)
- Sara Larivière
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts
| | - Frédéric L W V J Schaper
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Raúl Rodríguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Ella Sahlas
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Judy Chen
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - William Drew
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts
| | - Mae Morton-Dutton
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts
| | - Aaron E L Warren
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts
- Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Sheena R Baratono
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts
| | - John D Rolston
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts
- Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Luis Concha
- Brain Connectivity Laboratory, Institute of Neurobiology, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, México
| | - Zhiqiang Zhang
- Department of Neurology, Neurosurgery, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts
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Sone D, Sato N, Shigemoto Y, Beheshti I, Kimura Y, Matsuda H. Estimated Disease Progression Trajectory of White Matter Disruption in Unilateral Temporal Lobe Epilepsy: A Data-Driven Machine Learning Approach. Brain Sci 2024; 14:992. [PMID: 39452006 PMCID: PMC11506697 DOI: 10.3390/brainsci14100992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 09/23/2024] [Accepted: 09/28/2024] [Indexed: 10/26/2024] Open
Abstract
BACKGROUND/OBJECTIVES Although the involvement of progressive brain alterations in epilepsy was recently suggested, individual patients' trajectories of white matter (WM) disruption are not known. METHODS We investigated the disease progression patterns of WM damage and its associations with clinical metrics. We examined the cross-sectional diffusion tensor imaging (DTI) data of 155 patients with unilateral temporal lobe epilepsy (TLE) and 270 age/gender-matched healthy controls, and we then calculated the average fractional anisotropy (FA) values within 20 WM tracts of the whole brain. We used the Subtype and Stage Inference (SuStaIn) program to detect the progression trajectory of FA changes and investigated its association with clinical parameters including onset age, disease duration, drug-responsiveness, and the number of anti-seizure medications (ASMs). RESULTS The SuStaIn algorithm identified a single subtype model in which the initial damage occurs in the ipsilateral uncinate fasciculus (UF), followed by damage in the forceps, superior longitudinal fasciculus (SLF), and anterior thalamic radiation (ATR). This pattern was replicated when analyzing TLE with hippocampal sclerosis (n = 50) and TLE with no lesions (n = 105) separately. Further-progressed stages were associated with longer disease duration (p < 0.001) and a greater number of ASMs (p = 0.001). CONCLUSIONS the disease progression model based on WM tracts may be useful as a novel individual-level biomarker.
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Affiliation(s)
- Daichi Sone
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan; (N.S.); (Y.S.); (Y.K.); (H.M.)
- Department of Psychiatry, Jikei University School of Medicine, Tokyo 105-8461, Japan
| | - Noriko Sato
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan; (N.S.); (Y.S.); (Y.K.); (H.M.)
| | - Yoko Shigemoto
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan; (N.S.); (Y.S.); (Y.K.); (H.M.)
| | - Iman Beheshti
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB R3E 0J9, Canada;
| | - Yukio Kimura
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan; (N.S.); (Y.S.); (Y.K.); (H.M.)
| | - Hiroshi Matsuda
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan; (N.S.); (Y.S.); (Y.K.); (H.M.)
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6
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Zawar I, Kapur J, Mattos MK, Aldridge CM, Manning C, Quigg M. Association of Seizure Control With Cognition in People With Normal Cognition and Mild Cognitive Impairment. Neurology 2024; 103:e209820. [PMID: 39173101 PMCID: PMC11343585 DOI: 10.1212/wnl.0000000000209820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 07/01/2024] [Indexed: 08/24/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Seizures are common in dementia and associated with accelerated cognitive decline. However, the impact of active vs remote seizures on cognition remains understudied. This study aimed to investigate the impact of active vs remote seizures on cognition in people with normal cognition and mild cognitive impairment (MCI). METHODS This longitudinal, multicenter cohort is based on National Alzheimer's Coordinating Center data of participants recruited from 39 Alzheimer's Disease Centers in the United States from September 2005 to December 2021. All participants with normal cognition and MCI and at least 2 visits were included. Primary outcome, that is, cognitive decline, was determined using Clinical Dementia Rating (CDR) from (1) normal-to-impaired (CDR ≥0.5) and (2) MCI-to-dementia (CDR ≥1) groups. The effect of active seizures (over the preceding 12 months), remote seizures (previous seizures but none over the preceding 12 months), and no seizures (controls) on cognition was assessed. Subgroups of chronic seizures at enrollment and new-onset seizures were further analyzed. Cox regression models assessed the risk of all-cause MCI and/or dementia. All models were adjusted for age, sex, education, race, hypertension, and diabetes. RESULTS Of the 13,726 participants with normal cognition at enrollment (9,002 [66%] female; median age 71 years), 118 had active seizures and 226 had remote seizures. Of the 11,372 participants with MCI at enrollment (5,605 [49%] female; median age 73 years), 197 had active seizures and 226 had remote seizures. Active seizures were associated with 2.1 times higher risk of cognitive impairment (adjusted hazard ratio [aHR] 2.13, 95% CI 1.60-2.84, p < 0.001) in cognitively healthy adults (median years to decline: active seizures = ∼1, remote seizures = ∼3, no seizures = ∼3) and 1.6 times higher risk of dementia (aHR 1.58, 95% CI 1.24-2.01, p < 0.001) in those with MCI (median years to decline: active seizures = ∼1, remote seizures = ∼2, controls = ∼2). This risk was not observed with remote seizures. DISCUSSION In this study, active seizures but not remote seizures were associated with earlier cognitive decline in both cognitively normal adults and those with MCI, independent of other dementia risk factors. Therefore, early identification and management of seizures may present a path to mitigation of cognitive decline in the aging epileptic population. A limitation is that causality cannot be confirmed in our observational longitudinal study.
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Affiliation(s)
- Ifrah Zawar
- From the Department of Neurology (I.Z., J.K., C.M.A., C.M., M.Q.), and School of Nursing (M.K.M.), University of Virginia, Charlottesville
| | - Jaideep Kapur
- From the Department of Neurology (I.Z., J.K., C.M.A., C.M., M.Q.), and School of Nursing (M.K.M.), University of Virginia, Charlottesville
| | - Meghan K Mattos
- From the Department of Neurology (I.Z., J.K., C.M.A., C.M., M.Q.), and School of Nursing (M.K.M.), University of Virginia, Charlottesville
| | - Chad M Aldridge
- From the Department of Neurology (I.Z., J.K., C.M.A., C.M., M.Q.), and School of Nursing (M.K.M.), University of Virginia, Charlottesville
| | - Carol Manning
- From the Department of Neurology (I.Z., J.K., C.M.A., C.M., M.Q.), and School of Nursing (M.K.M.), University of Virginia, Charlottesville
| | - Mark Quigg
- From the Department of Neurology (I.Z., J.K., C.M.A., C.M., M.Q.), and School of Nursing (M.K.M.), University of Virginia, Charlottesville
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7
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Hashmi SA, Sachdeva S, Sindhu U, Tsai C, Bonda K, Keezer M, Zawar I, Punia V. The implications of frailty in older adults with epilepsy. Epilepsia Open 2024. [PMID: 39248297 DOI: 10.1002/epi4.13046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 08/15/2024] [Accepted: 08/29/2024] [Indexed: 09/10/2024] Open
Abstract
Older adults constitute a large proportion of people with epilepsy (PWE) due to the changing demographics worldwide and epilepsy's natural history. Aging-related pathophysiological changes lower the tolerance and increase our vulnerability to stressors, which manifests as frailty. Frailty is closely associated with adverse health outcomes. This narrative review examines the interplay between frailty and epilepsy, especially in older adults, emphasizing its clinical implications, including its role in managing PWE. Mechanistically, frailty develops through complex interactions among molecular and cellular damage, including genomic instability, mitochondrial dysfunction, and hormonal changes. These contribute to systemic muscle mass, bone density, and organ function decline. The concept of frailty has evolved from a primarily physical syndrome to include social, psychological, and cognitive dimensions. The "phenotypic frailty" model, which focuses on physical performance, and the "deficit accumulation" model, which quantifies health deficits, provide frameworks for understanding and assessing frailty. PWE are potentially more prone to developing frailty due to a higher prevalence of risk factors predisposing to frailty. These include, but are not limited to, polypharmacy, higher comorbidity, low exercise level, social isolation, low vitamin D, and osteoporosis. We lack commercial biomarkers to measure frailty but can diagnose it using self- or healthcare provider-administered frailty scales. Recent attempts to develop a PWE-specific frailty scale are promising. Unlike chronological age, frailty is reversible, so its management using multidisciplinary care teams should be strongly considered. Frailty can affect antiseizure medication (ASM) tolerance secondary to its impact on pharmacokinetics and pharmacodynamics. While frailty's effect on seizure control efficacy of ASM is poorly understood, its undoubted association with overall poor outcomes, including epilepsy surgery, behooves us to consider its presence and implication while treating older PWE. Incorporation of frailty measures in future research is essential to improve our understanding of frailty's role in PWE health. PLAIN LANGUAGE SUMMARY: Frailty is the declining state of the human body. People with epilepsy are more prone to it. It should be factored into their management.
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Affiliation(s)
- Syeda Amrah Hashmi
- Department of Neurology, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Seerat Sachdeva
- Clinical Observer, Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Udeept Sindhu
- Clinical Observer, Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Carolyn Tsai
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
| | | | - Mark Keezer
- Department of Neurosciences, Université de Montréal, Montreal, Quebec, Canada
| | - Ifrah Zawar
- Department of Neurology, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Vineet Punia
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
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Aydin H, Aytac A, Bulbul E, Yanik B, Korkut O, Gulcen B. A Comparison of Pre- and Post-Treatment Cranial MRI Characteristics in Patients with Pediatric Epilepsy Receiving Levetiracetam. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:1355. [PMID: 39202636 PMCID: PMC11356224 DOI: 10.3390/medicina60081355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 08/08/2024] [Accepted: 08/15/2024] [Indexed: 09/03/2024]
Abstract
Background and Objectives: This study was performed for the purpose of assessing whether antiepileptic levetiracetam treatment produces a change in brain volumes in children with epilepsy. To that end, we compared the volumes of the basal ganglia (caudate nucleus, putamen, globus, hip-pocampus, and thalamus) at magnetic resonance imaging (MRI) before and after treatment (months 18-24) in pediatric epilepsy patients using levetiracetam. Materials and Methods: This retrospective study involved a volumetric comparison of patients presenting to the Balikesir University Medical Faculty pediatric neurology clinic between 01.08.2019 and 01.11.2023 and diagnosed with epilepsy, and who underwent cranial MRI before and 18-24 months after treatment at the radiology department. The demographic and clinical characteristics (age, sex, family history of epilepsy, type of epilepsy, and EEG features (normal, abnormal, epileptiform)) of the patients included in the study were recorded. Results: The comparison of basal ganglia volumes at cranial MRI before and at months 18-24 of treatment revealed significant differences in the left caudate nucleus, right putamen, left putamen, left globus pallidus, right thalamus, left thalamus, and right hippocampal regions. Conclusions: In conclusion, differing findings are encountered at cranial imaging in patients with epilepsy, depending on the seizure frequency, activity, and the type of antiepileptic drugs used. This study compared basal ganglia volumes on cranial MRIs taken before and 18-24 months after treatment in pediatric epilepsy patients using levetiracetam. A significant increase was observed in the volumes of basal ganglia (caudate nucleus, putamen, globus pallidus, hippocampus, and thalamus) on the MRIs of pediatric epilepsy patients using levetiracetam.
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Affiliation(s)
- Hilal Aydin
- Department of Pediatrics, Faculty of Medicine, Balikesir University, Balikesir 10145, Türkiye
| | - Adil Aytac
- Department of Radiology, Faculty of Medicine, Balikesir University, Balikesir 10145, Türkiye; (A.A.); (E.B.); (B.Y.)
| | - Erdogan Bulbul
- Department of Radiology, Faculty of Medicine, Balikesir University, Balikesir 10145, Türkiye; (A.A.); (E.B.); (B.Y.)
| | - Bahar Yanik
- Department of Radiology, Faculty of Medicine, Balikesir University, Balikesir 10145, Türkiye; (A.A.); (E.B.); (B.Y.)
| | - Oguzhan Korkut
- Department of Medical Pharmacology, Faculty of Medicine, Balikesir University, Balikesir 10145, Türkiye;
| | - Burak Gulcen
- Department of Anatomy, Faculty of Medicine, Balikesir University, Balikesir 10145, Türkiye;
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9
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Lee HM, Fadaie F, Gill RS, Caldairou B, Sziklas V, Crane J, Hong SJ, Bernhardt BC, Bernasconi A, Bernasconi N. MRI-Derived Modeling of Disease Progression Patterns in Patients With Temporal Lobe Epilepsy. Neurology 2024; 103:e209524. [PMID: 38981074 DOI: 10.1212/wnl.0000000000209524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Temporal lobe epilepsy (TLE) is assumed to follow a steady course that is similar across patients. To date, phenotypic and temporal diversities of TLE evolution remain unknown. In this study, we aimed at simultaneously characterizing these sources of variability based on cross-sectional data. METHODS We studied consecutive patients with TLE referred for evaluation by neurologists to the Montreal Neurological Institute epilepsy clinic, who underwent in-patient video EEG monitoring and multimodal imaging at 3 Tesla, comprising 3D T1 and fluid-attenuated inversion recovery and 2D diffusion-weighted MRI. The cohort included patients with drug-resistant epilepsy and patients with drug-responsive epilepsy. The neuropsychological evaluation included Wechsler Adult Intelligence Scale-III and Leonard tapping task. The control group consisted of participants without TLE recruited through advertisement and who underwent the same MRI acquisition as patients. Based on surface-based analysis of key MRI markers of pathology (gray matter morphology and white matter microstructure), the Subtype and Stage Inference algorithm estimated subtypes and stages of brain pathology to which individual patients were assigned. The number of subtypes was determined by running the algorithm 100 times and estimating mean and SD of disease trajectories and the consistency of patients' assignments based on 1,000 bootstrap samples. Effect of normal aging was subtracted from patients. We examined associations with clinical and cognitive parameters and utility for individualized predictions. RESULTS We studied 82 patients with TLE (52 female, mean age 35 ± 10 years; 11 drug-responsive) and 41 control participants (23 male, mean age 32 ± 8 years). Among 57 operated, 43/37/20 had Engel-I outcome/hippocampal sclerosis/hippocampal isolated gliosis, respectively. We identified 3 trajectory subtypes: S1 (n = 35), led by ipsilateral hippocampal atrophy and gliosis, followed by white-matter damage; S2 (n = 27), characterized by bilateral neocortical atrophy, followed by ipsilateral hippocampal atrophy and gliosis; and S3 (n = 20), typified by bilateral limbic white-matter damage, followed by bilateral hippocampal gliosis. Patients showed high assignability to their subtypes and stages (>90% bootstrap agreement). S1 had the highest proportions of patients with early disease onset (effect size d = 0.27 vs S2, d = 0.73 vs S3), febrile convulsions (χ2 = 3.70), drug resistance (χ2 = 2.94), a positive MRI (χ2 = 8.42), hippocampal sclerosis (χ2 = 7.57), and Engel-I outcome (χ2 = 1.51), pFDR < 0.05 across all comparisons. S2 and S3 exhibited the intermediate and lowest proportions, respectively. Verbal IQ and digit span were lower in S1 (d = 0.65 and d = 0.50, pFDR < 0.05) and S2 (d = 0.76 and d = 1.09, pFDR < 0.05), compared with S3. We observed progressive decline in sequential motor tapping in S1 and S3 (T = -3.38 and T = -4.94, pFDR = 0.027), compared with S2 (T = 2.14, pFDR = 0.035). S3 showed progressive decline in digit span (T = -5.83, p = 0.021). Supervised classifiers trained on subtype and stage outperformed subtype-only and stage-only models predicting drug response in 73% ± 1.0% (vs 70% ± 1.4% and 63% ± 1.3%) and 76% ± 1.6% for Engel-I outcome (vs 71% ± 0.8% and 72% ± 1.1%), pFDR < 0.05 across all comparisons. DISCUSSION Cross-sectional MRI-derived models provide reliable prognostic markers of TLE disease evolution, which follows distinct trajectories, each associated with divergent patterns of hippocampal and whole-brain structural alterations, as well as cognitive and clinical profiles.
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Affiliation(s)
- Hyo M Lee
- From the Neuroimaging of Epilepsy Laboratory (H.M.L., F.F., R.S.G., B.C., S.-J.H., A.B., N.B.), and Multimodal Imaging and Connectome Analysis Lab (B.C.B.), Montreal Neurological Institute (V.S., J.C.), Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Fatemeh Fadaie
- From the Neuroimaging of Epilepsy Laboratory (H.M.L., F.F., R.S.G., B.C., S.-J.H., A.B., N.B.), and Multimodal Imaging and Connectome Analysis Lab (B.C.B.), Montreal Neurological Institute (V.S., J.C.), Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Ravnoor S Gill
- From the Neuroimaging of Epilepsy Laboratory (H.M.L., F.F., R.S.G., B.C., S.-J.H., A.B., N.B.), and Multimodal Imaging and Connectome Analysis Lab (B.C.B.), Montreal Neurological Institute (V.S., J.C.), Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Benoit Caldairou
- From the Neuroimaging of Epilepsy Laboratory (H.M.L., F.F., R.S.G., B.C., S.-J.H., A.B., N.B.), and Multimodal Imaging and Connectome Analysis Lab (B.C.B.), Montreal Neurological Institute (V.S., J.C.), Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Viviane Sziklas
- From the Neuroimaging of Epilepsy Laboratory (H.M.L., F.F., R.S.G., B.C., S.-J.H., A.B., N.B.), and Multimodal Imaging and Connectome Analysis Lab (B.C.B.), Montreal Neurological Institute (V.S., J.C.), Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Joelle Crane
- From the Neuroimaging of Epilepsy Laboratory (H.M.L., F.F., R.S.G., B.C., S.-J.H., A.B., N.B.), and Multimodal Imaging and Connectome Analysis Lab (B.C.B.), Montreal Neurological Institute (V.S., J.C.), Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Seok-Jun Hong
- From the Neuroimaging of Epilepsy Laboratory (H.M.L., F.F., R.S.G., B.C., S.-J.H., A.B., N.B.), and Multimodal Imaging and Connectome Analysis Lab (B.C.B.), Montreal Neurological Institute (V.S., J.C.), Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Boris C Bernhardt
- From the Neuroimaging of Epilepsy Laboratory (H.M.L., F.F., R.S.G., B.C., S.-J.H., A.B., N.B.), and Multimodal Imaging and Connectome Analysis Lab (B.C.B.), Montreal Neurological Institute (V.S., J.C.), Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Andrea Bernasconi
- From the Neuroimaging of Epilepsy Laboratory (H.M.L., F.F., R.S.G., B.C., S.-J.H., A.B., N.B.), and Multimodal Imaging and Connectome Analysis Lab (B.C.B.), Montreal Neurological Institute (V.S., J.C.), Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- From the Neuroimaging of Epilepsy Laboratory (H.M.L., F.F., R.S.G., B.C., S.-J.H., A.B., N.B.), and Multimodal Imaging and Connectome Analysis Lab (B.C.B.), Montreal Neurological Institute (V.S., J.C.), Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
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10
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Wan X, Zeng Y, Wang J, Tian M, Yin X, Zhang J. Structural and functional abnormalities and cognitive profiles in older adults with early-onset and late-onset focal epilepsy. Cereb Cortex 2024; 34:bhae300. [PMID: 39052362 DOI: 10.1093/cercor/bhae300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 06/26/2024] [Accepted: 07/09/2024] [Indexed: 07/27/2024] Open
Abstract
This study aimed to determine the patterns of changes in structure, function, and cognitive ability in early-onset and late-onset older adults with focal epilepsy (OFE). This study first utilized the deformation-based morphometry analysis to identify structural abnormalities, which were used as the seed region to investigate the functional connectivity with the whole brain. Next, a correlation analysis was performed between the altered imaging findings and neuropsychiatry assessments. Finally, the potential role of structural-functional abnormalities in the diagnosis of epilepsy was further explored by using mediation analysis. Compared with healthy controls (n = 28), the area of reduced structural volume was concentrated in the bilateral cerebellum, right thalamus, and right middle cingulate cortex, with frontal, temporal, and occipital lobes also affected in early-onset focal epilepsy (n = 26), while late-onset patients (n = 31) displayed cerebellar, thalamic, and cingulate atrophy. Furthermore, correlation analyses suggest an association between structural abnormalities and cognitive assessments. Dysfunctional connectivity in the cerebellum, cingulate cortex, and frontal gyrus partially mediates the relationship between structural abnormalities and the diagnosis of early-onset focal epilepsy. This study identified structural and functional abnormalities in early-onset and late-onset focal epilepsy and explored characters in cognitive performance. Structural-functional coupling may play a potential role in the diagnosis of epilepsy.
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Affiliation(s)
- Xinyue Wan
- Department of Radiology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai 200040, China
- Human Phenome Institute, Fudan University, Shanghai 201203, China
| | - Yanwei Zeng
- Department of Radiology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai 200040, China
| | - Jianhong Wang
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai 201203, China
| | - Xuyang Yin
- Department of Radiology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai 200040, China
| | - Jun Zhang
- Department of Radiology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai 200040, China
- National Center for Neurological Disorders, Fudan University, Shanghai 200040, China
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11
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Kaestner E, Stasenko A, Schadler A, Roth R, Hewitt K, Reyes A, Qiu D, Bonilha L, Voets N, Hu R, Willie J, Pedersen N, Shih J, Ben-Haim S, Gross R, Drane D, McDonald CR. Impact of white matter networks on risk for memory decline following resection versus ablation in temporal lobe epilepsy. J Neurol Neurosurg Psychiatry 2024; 95:663-670. [PMID: 38212059 PMCID: PMC11187680 DOI: 10.1136/jnnp-2023-332682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 12/19/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND With expanding neurosurgical options in epilepsy, it is important to characterise each options' risk for postoperative cognitive decline. Here, we characterise how patients' preoperative white matter (WM) networks relates to postoperative memory changes following different epilepsy surgeries. METHODS Eighty-nine patients with temporal lobe epilepsy with T1-weighted and diffusion-weighted imaging as well as preoperative and postoperative verbal memory scores (prose recall) underwent either anterior temporal lobectomy (ATL: n=38) or stereotactic laser amygdalohippocampotomy (SLAH; n=51). We computed laterality indices (ie, asymmetry) for volume of the hippocampus and fractional anisotropy (FA) of two deep WM tracts (uncinate fasciculus (UF) and inferior longitudinal fasciculus (ILF)). RESULTS Preoperatively, left-lateralised FA of the ILF was associated with higher prose recall (p<0.01). This pattern was not observed for the UF or hippocampus (ps>0.05). Postoperatively, right-lateralised FA of the UF was associated with less decline following left ATL (p<0.05) but not left SLAH (p>0.05), while right-lateralised hippocampal asymmetry was associated with less decline following both left ATL and SLAH (ps<0.05). After accounting for preoperative memory score, age of onset and hippocampal asymmetry, the association between UF and memory decline in left ATL remained significant (p<0.01). CONCLUSIONS Asymmetry of the hippocampus is an important predictor of risk for memory decline following both surgeries. However, asymmetry of UF integrity, which is only severed during ATL, is an important predictor of memory decline after ATL only. As surgical procedures and pre-surgical mapping evolve, understanding the role of frontal-temporal WM in memory networks could help to guide more targeted surgical approaches to mitigate cognitive decline.
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Affiliation(s)
- Erik Kaestner
- Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California, USA
| | - Alena Stasenko
- Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California, USA
| | - Adam Schadler
- Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California, USA
| | - Rebecca Roth
- Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Kelsey Hewitt
- Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Anny Reyes
- Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California, USA
| | - Deqiang Qiu
- Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
| | - Leonardo Bonilha
- Department of Neurology, University of South Carolina System, Columbia, South Carolina, USA
| | | | - Ranliang Hu
- Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
| | - Jon Willie
- Neurosurgery, Washington University in St Louis, St Louis, Missouri, USA
| | | | - Jerry Shih
- Neurosciences, University of California, San Diego, La Jolla, California, USA
| | - Sharona Ben-Haim
- Neurosurgery, University of California, San Diego, La Jolla, California, USA
| | - Robert Gross
- Department of Neurological Surgery, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Daniel Drane
- Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Carrie R McDonald
- Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California, USA
- Psychiatry, University of California, San Diego, La Jolla, California, USA
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12
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Englot DJ. Chronicles of Change: The Shrinking Brain in Epilepsy. Epilepsy Curr 2024; 24:159-161. [PMID: 38898902 PMCID: PMC11185202 DOI: 10.1177/15357597241228475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2024] Open
Abstract
Identification of Different MRI Atrophy Progression Trajectories in Epilepsy by Subtype and Stage Inference Xiao F, Caciagli L, Wandschneider B, Sone D, Young AL, Vos SB, Winston GP, Zhang Y, Liu W, An D, Kanber B, Zhou D, Sander JW, Thom M, Duncan JS, Alexander DC, Galovic M, Koepp MJ. Brain . 2023;146(11):4702-4716. doi:10.1093/brain/awad284 Artificial intelligence (AI)-based tools are widely employed, but their use for diagnosis and prognosis of neurological disorders is still evolving. Here we analyse a cross-sectional multicentre structural MRI dataset of 696 people with epilepsy and 118 control subjects. We use an innovative machine-learning algorithm, Subtype and Stage Inference, to develop a novel data-driven disease taxonomy, whereby epilepsy subtypes correspond to distinct patterns of spatiotemporal progression of brain atrophy. In a discovery cohort of 814 individuals, we identify two subtypes common to focal and idiopathic generalized epilepsies, characterized by progression of grey matter atrophy driven by the cortex or the basal ganglia. A third subtype, only detected in focal epilepsies, was characterized by hippocampal atrophy. We corroborate external validity via an independent cohort of 254 people and confirm that the basal ganglia subtype is associated with the most severe epilepsy. Our findings suggest fundamental processes underlying the progression of epilepsy-related brain atrophy. We deliver a novel MRI- and AI-guided epilepsy taxonomy, which could be used for individualized prognostics and targeted therapeutics.
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Affiliation(s)
- Dario J Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center
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13
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Xie K, Royer J, Larivière S, Rodriguez-Cruces R, Frässle S, Cabalo DG, Ngo A, DeKraker J, Auer H, Tavakol S, Weng Y, Abdallah C, Arafat T, Horwood L, Frauscher B, Caciagli L, Bernasconi A, Bernasconi N, Zhang Z, Concha L, Bernhardt BC. Atypical connectome topography and signal flow in temporal lobe epilepsy. Prog Neurobiol 2024; 236:102604. [PMID: 38604584 DOI: 10.1016/j.pneurobio.2024.102604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 12/18/2023] [Accepted: 04/07/2024] [Indexed: 04/13/2024]
Abstract
Temporal lobe epilepsy (TLE) is the most common pharmaco-resistant epilepsy in adults. While primarily associated with mesiotemporal pathology, recent evidence suggests that brain alterations in TLE extend beyond the paralimbic epicenter and impact macroscale function and cognitive functions, particularly memory. Using connectome-wide manifold learning and generative models of effective connectivity, we examined functional topography and directional signal flow patterns between large-scale neural circuits in TLE at rest. Studying a multisite cohort of 95 patients with TLE and 95 healthy controls, we observed atypical functional topographies in the former group, characterized by reduced differentiation between sensory and transmodal association cortices, with most marked effects in bilateral temporo-limbic and ventromedial prefrontal cortices. These findings were consistent across all study sites, present in left and right lateralized patients, and validated in a subgroup of patients with histopathological validation of mesiotemporal sclerosis and post-surgical seizure freedom. Moreover, they were replicated in an independent cohort of 30 TLE patients and 40 healthy controls. Further analyses demonstrated that reduced differentiation related to decreased functional signal flow into and out of temporolimbic cortical systems and other brain networks. Parallel analyses of structural and diffusion-weighted MRI data revealed that topographic alterations were independent of TLE-related cortical thinning but partially mediated by white matter microstructural changes that radiated away from paralimbic circuits. Finally, we found a strong association between the degree of functional alterations and behavioral markers of memory dysfunction. Our work illustrates the complex landscape of macroscale functional imbalances in TLE, which can serve as intermediate markers bridging microstructural changes and cognitive impairment.
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Affiliation(s)
- Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Donna Gift Cabalo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Hans Auer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Chifaou Abdallah
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Thaera Arafat
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Linda Horwood
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Department of Neurology, Duke University School of Medicine and Department of Biomedical Engineering, Duke University Pratt School of Engineering, Durham, NC 27705, USA
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Bern, Switzerland; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3 BG, United Kingdom
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de Mexico (UNAM), Queretaro, Mexico
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada.
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14
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Feng X, Piper RJ, Prentice F, Clayden JD, Baldeweg T. Functional brain connectivity in children with focal epilepsy: A systematic review of functional MRI studies. Seizure 2024; 117:164-173. [PMID: 38432080 DOI: 10.1016/j.seizure.2024.02.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 02/26/2024] [Accepted: 02/27/2024] [Indexed: 03/05/2024] Open
Abstract
Epilepsy is increasingly recognised as a brain network disorder and many studies have investigated functional connectivity (FC) in children with epilepsy using functional MRI (fMRI). This systematic review of fMRI studies, published up to November 2023, investigated profiles of FC changes and their clinical relevance in children with focal epilepsy compared to healthy controls. A literature search in PubMed and Web of Science yielded 62 articles. We categorised the results into three groups: 1) differences in correlation-based FC between patients and controls; 2) differences in other FC measures between patients and controls; and 3) associations between FC and disease variables (for example, age of onset), cognitive and seizure outcomes. Studies revealed either increased or decreased FC across multiple brain regions in children with focal epilepsy. However, findings lacked consistency: conflicting FC alterations (decreased and increased FC) co-existed within or between brain regions across all focal epilepsy groups. The studies demonstrated overall that 1) interhemispheric connections often displayed abnormal connectivity and 2) connectivity within and between canonical functional networks was decreased, particularly for the default mode network. Focal epilepsy disrupted FC in children both locally (e.g., seizure-onset zones, or within-brain subnetworks) and globally (e.g., whole-brain network architecture). The wide variety of FC study methodologies limits clinical application of the results. Future research should employ longitudinal designs to understand the evolution of brain networks during the disease course and explore the potential of FC biomarkers for predicting cognitive and postsurgical seizure outcomes.
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Affiliation(s)
- Xiyu Feng
- Developmental Neurosciences Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford, London WC1N 1EH, United Kingdom
| | - Rory J Piper
- Developmental Neurosciences Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford, London WC1N 1EH, United Kingdom; Department of Neurosurgery, Great Ormond Street Hospital, London, United Kingdom
| | - Freya Prentice
- Developmental Neurosciences Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford, London WC1N 1EH, United Kingdom
| | - Jonathan D Clayden
- Developmental Neurosciences Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford, London WC1N 1EH, United Kingdom
| | - Torsten Baldeweg
- Developmental Neurosciences Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford, London WC1N 1EH, United Kingdom.
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15
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Jiang Y, Li W, Li J, Li X, Zhang H, Sima X, Li L, Wang K, Li Q, Fang J, Jin L, Gong Q, Yao D, Zhou D, Luo C, An D. Identification of four biotypes in temporal lobe epilepsy via machine learning on brain images. Nat Commun 2024; 15:2221. [PMID: 38472252 DOI: 10.1038/s41467-024-46629-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 03/05/2024] [Indexed: 03/14/2024] Open
Abstract
Artificial intelligence provides an opportunity to try to redefine disease subtypes based on similar pathobiology. Using a machine-learning algorithm (Subtype and Stage Inference) with cross-sectional MRI from 296 individuals with focal epilepsy originating from the temporal lobe (TLE) and 91 healthy controls, we show phenotypic heterogeneity in the pathophysiological progression of TLE. This study was registered in the Chinese Clinical Trials Registry (number: ChiCTR2200062562). We identify two hippocampus-predominant phenotypes, characterized by atrophy beginning in the left or right hippocampus; a third cortex-predominant phenotype, characterized by hippocampus atrophy after the neocortex; and a fourth phenotype without atrophy but amygdala enlargement. These four subtypes are replicated in the independent validation cohort (109 individuals). These subtypes show differences in neuroanatomical signature, disease progression and epilepsy characteristics. Five-year follow-up observations of these individuals reveal differential seizure outcomes among subtypes, indicating that specific subtypes may benefit from temporal surgery or pharmacological treatment. These findings suggest a diverse pathobiological basis underlying focal epilepsy that potentially yields to stratification and prognostication - a necessary step for precise medicine.
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Affiliation(s)
- Yuchao Jiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
| | - Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Geriatrics, West China Hospital, Sichuan University, China National Clinical Research Center for Geriatric Medicine, Chengdu, China
| | - Jinmei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiuli Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Heng Zhang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiutian Sima
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Luying Li
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Kang Wang
- Epilepsy Center, Department of Neurology, The first affiliated hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Qifu Li
- Department of Neurology, The first affiliated hospital, Hainan Medical University and the Key Laboratory of Brain Science Research and Transformation in Tropical Environment of Hainan Province, Haikou, Hainan, China
| | - Jiajia Fang
- Department of Neurology, The fourth affiliated hospital, School of Medicine, Zhejiang University, Yiwu, Zhejiang, China
| | - Lu Jin
- Psychological Medicine Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and technology, University of Electronic Science and Technology of China, Chengdu, China.
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China.
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China.
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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16
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Chen J, Ngo A, Rodríguez-Cruces R, Royer J, Caligiuri ME, Gambardella A, Concha L, Keller SS, Cendes F, Yasuda CL, Alvim MKM, Bonilha L, Gleichgerrcht E, Focke NK, Kreilkamp B, Domin M, von Podewils F, Langner S, Rummel C, Wiest R, Martin P, Kotikalapudi R, Bender B, O’Brien TJ, Sinclair B, Vivash L, Kwan P, Desmond PM, Lui E, Duma GM, Bonanni P, Ballerini A, Vaudano AE, Meletti S, Tondelli M, Alhusaini S, Doherty CP, Cavalleri GL, Delanty N, Kälviäinen R, Jackson GD, Kowalczyk M, Mascalchi M, Semmelroch M, Thomas RH, Soltanian-Zadeh H, Davoodi-Bojd E, Zhang J, Lenge M, Guerrini R, Bartolini E, Hamandi K, Foley S, Rüber T, Bauer T, Weber B, Caldairou B, Depondt C, Absil J, Carr SJA, Abela E, Richardson MP, Devinsky O, Pardoe H, Severino M, Striano P, Tortora D, Kaestner E, Hatton SN, Arienzo D, Vos SB, Ryten M, Taylor PN, Duncan JS, Whelan CD, Galovic M, Winston GP, Thomopoulos SI, Thompson PM, Sisodiya SM, Labate A, McDonald CR, Caciagli L, Bernasconi N, Bernasconi A, Larivière S, Schrader D, Bernhardt BC. A WORLDWIDE ENIGMA STUDY ON EPILEPSY-RELATED GRAY AND WHITE MATTER COMPROMISE ACROSS THE ADULT LIFESPAN. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.02.583073. [PMID: 38496668 PMCID: PMC10942350 DOI: 10.1101/2024.03.02.583073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Objectives Temporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of grey and white matter structures. Evidence supports a progressive condition although the temporal evolution of TLE is poorly defined. This ENIGMA-Epilepsy study utilized multimodal magnetic resonance imaging (MRI) data to investigate structural alterations in TLE patients across the adult lifespan. We charted both grey and white matter changes and explored the covariance of age-related alterations in both compartments. Methods We studied 769 TLE patients and 885 healthy controls across an age range of 17-73 years, from multiple international sites. To assess potentially non-linear lifespan changes in TLE, we harmonized data and combined median split assessments with cross-sectional sliding window analyses of grey and white matter age-related changes. Covariance analyses examined the coupling of grey and white matter lifespan curves. Results In TLE, age was associated with a robust grey matter thickness/volume decline across a broad cortico-subcortical territory, extending beyond the mesiotemporal disease epicentre. White matter changes were also widespread across multiple tracts with peak effects in temporo-limbic fibers. While changes spanned the adult time window, changes accelerated in cortical thickness, subcortical volume, and fractional anisotropy (all decreased), and mean diffusivity (increased) after age 55 years. Covariance analyses revealed strong limbic associations between white matter tracts and subcortical structures with cortical regions. Conclusions This study highlights the profound impact of TLE on lifespan changes in grey and white matter structures, with an acceleration of aging-related processes in later decades of life. Our findings motivate future longitudinal studies across the lifespan and emphasize the importance of prompt diagnosis as well as intervention in patients.
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Affiliation(s)
- Judy Chen
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Raúl Rodríguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | | | - Antonio Gambardella
- Neuroscience Research Center, University Magna Græcia, Catanzaro, CZ, Italy
- Institute of Neurology, University Magna Græcia, Catanzaro, CZ, Italy
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Querétaro, México
| | - Simon S. Keller
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
- Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Fernando Cendes
- Department of Neurology, University of Campinas-–UNICAMP, Campinas, São Paulo, Brazil
| | - Clarissa L. Yasuda
- Department of Neurology, University of Campinas-–UNICAMP, Campinas, São Paulo, Brazil
| | - Marina K. M. Alvim
- Department of Neurology, University of Campinas-–UNICAMP, Campinas, São Paulo, Brazil
| | | | | | - Niels K. Focke
- Department of Neurology, University of Medicine Göttingen, Göttingen, Germany
| | - Barbara Kreilkamp
- Department of Neurology, University of Medicine Göttingen, Göttingen, Germany
| | - Martin Domin
- Institute of Diagnostic Radiology and Neuroradiology, Functional Imaging Unit, University Medicine Greifswald, Greifswald, Germany
| | - Felix von Podewils
- Department of Neurology, University Medicine Greifswald, Epilepsy Center, Greifswald, Germany
| | - Soenke Langner
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Pascal Martin
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Raviteja Kotikalapudi
- Department of Neurology, University of Medicine Göttingen, Göttingen, Germany
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Benjamin Bender
- Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Germany
| | - Terence J. O’Brien
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Benjamin Sinclair
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patrick Kwan
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patricia M. Desmond
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Elaine Lui
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Gian Marco Duma
- Scientific Institute IRCCS E.Medea, Epilepsy Unit, Conegliano (TV), Italy
| | - Paolo Bonanni
- Scientific Institute IRCCS E.Medea, Epilepsy Unit, Conegliano (TV), Italy
| | - Alice Ballerini
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Anna Elisabetta Vaudano
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria, Modena, Italy
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Stefano Meletti
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria, Modena, Italy
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Manuela Tondelli
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
- Primary Care Department, Azienda Sanitaria Locale di Modena, Modena, Italy
| | - Saud Alhusaini
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Neurology, Alpert Medical School of Brown University, Providence, RI, USA
| | - Colin P. Doherty
- Department of Neurology, St James’ Hospital, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Gianpiero L. Cavalleri
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Norman Delanty
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Reetta Kälviäinen
- Epilepsy Center, Neuro Center, Kuopio University Hospital, Member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Kuopio, Finland
- Faculty of Health Sciences, School of Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Graeme D. Jackson
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne VIC 3010, Australia
| | - Magdalena Kowalczyk
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne VIC 3010, Australia
| | - Mario Mascalchi
- Neuroradiology Research Program, Meyer Children Hospital of Florence, University of Florence, Florence, Italy
| | - Mira Semmelroch
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne VIC 3010, Australia
| | - Rhys H. Thomas
- Transitional and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Hamid Soltanian-Zadeh
- Contol and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
- Departments of Research Administration and Radiology, Henry Ford Health System, Detroit, MI, USA
| | | | - Junsong Zhang
- Cognitive Science Department, Xiamen University, Xiamen, China
| | - Matteo Lenge
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children’s Hospital IRCCS, Florence, Italy
| | - Renzo Guerrini
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children’s Hospital IRCCS, Florence, Italy
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Italy
| | | | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
- The Welsh Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, UK
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
| | - Theodor Rüber
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Tobias Bauer
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Chantal Depondt
- Department of Neurology, Hôpital Erasme, Hôpital Universitaire de Bruxelles (HUB), Université Libre de Bruxelles, Brussels, Belgium
| | - Julie Absil
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Sarah J. A. Carr
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Eugenio Abela
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Mark P. Richardson
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Orrin Devinsky
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, United States
| | - Heath Pardoe
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, United States
| | | | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Domenico Tortora
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Erik Kaestner
- Department of Radiation Medicine and Applied Sciences; Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Sean N. Hatton
- Department of Neurosciences, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Donatello Arienzo
- Department of Radiation Medicine and Applied Sciences; Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Sjoerd B. Vos
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - Mina Ryten
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Bucks, UK
| | - Peter N. Taylor
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- CNNP Lab, ICOS group, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - John S. Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Christopher D. Whelan
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Marian Galovic
- Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zürich, Zürich, Switzerland
| | - Gavin P. Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
- Department of Medicine, Division of Neurology, Queen’s University, Kingston, ON, Canada
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Sanjay M. Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Angelo Labate
- Neurophysiopathology and Movement Disorders Clinic, Regional Epilepsy Center, University of Messina, Italy
| | - Carrie R. McDonald
- Department of Radiation Medicine and Applied Sciences; Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Bucks, UK
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Harvard University, Boston, MA, USA
| | - Dewi Schrader
- BC Children’s Hospital, University of British Columbia, Vancouver, BC, Canada
| | - Boris C. Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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17
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Janson A, Sainburg L, Akbarian B, Johnson GW, Rogers BP, Chang C, Englot DJ, Morgan VL. Indirect structural changes and reduced controllability after temporal lobe epilepsy resection. Epilepsia 2024; 65:675-686. [PMID: 38240699 PMCID: PMC10948308 DOI: 10.1111/epi.17889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 12/08/2023] [Accepted: 01/08/2024] [Indexed: 03/06/2024]
Abstract
OBJECTIVE To understand the potential behavioral and cognitive effects of mesial temporal resection for temporal lobe epilepsy (TLE) a method is required to characterize network-wide functional alterations caused by a discrete structural disconnection. The objective of this study was to investigate network-wide alterations in brain dynamics of patients with TLE before and after surgical resection of the seizure focus using average regional controllability (ARC), a measure of the ability of a node to influence network dynamics. METHODS Diffusion-weighted imaging (DWI) data were acquired in 27 patients with drug-resistant unilateral mesial TLE who underwent selective amygdalohippocampectomy. Imaging data were acquired before and after surgery and a presurgical and postsurgical structural connectome was generated from whole-brain tractography. Edge-wise strength, node strength, and node ARC were compared before and after surgery. Direct and indirect edge-wise strength changes were identified using patient-specific simulated resections. Direct edges were defined as primary edges disconnected by the resection zone itself. Indirect edges were secondary measured edge strength changes. Changes in node strength and ARC were then related to both direct and indirect edge changes. RESULTS We found nodes with significant postsurgical changes in both node strength and ARC surrounding the resection zone (paired t tests, p < .05, Bonferroni corrected). ARC identified additional postsurgical changes in nodes outside of the resection zone within the ipsilateral occipital lobe, which were associated with indirect edge-wise strength changes of the postsurgical network (Fisher's exact test, p < .001). These indirect edge-wise changes were facilitated through the "hub" nodes including the thalamus, putamen, insula, and precuneus. SIGNIFICANCE Discrete network disconnection from TLE resection results in widespread structural and functional changes not predicted by disconnection alone. These can be well characterized by dynamic controllability measures such as ARC and may be useful for investigating changes in brain function that may contribute to seizure recurrence and behavioral or cognitive changes after surgery.
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Affiliation(s)
- Andrew Janson
- Department of Radiology and Radiological Sciences, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Lucas Sainburg
- Department of Radiology and Radiological Sciences, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Behnaz Akbarian
- Department of Radiology and Radiological Sciences, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Graham W Johnson
- Department of Radiology and Radiological Sciences, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Baxter P Rogers
- Department of Radiology and Radiological Sciences, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Catie Chang
- Department of Radiology and Radiological Sciences, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Dario J Englot
- Department of Radiology and Radiological Sciences, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Victoria L Morgan
- Department of Radiology and Radiological Sciences, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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18
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Gugger JJ, Walter AE, Diaz‐Arrastia R, Huang J, Jack CR, Reid R, Kucharska‐Newton AM, Gottesman RF, Schneider ALC, Johnson EL. Association between structural brain MRI abnormalities and epilepsy in older adults. Ann Clin Transl Neurol 2024; 11:342-354. [PMID: 38155477 PMCID: PMC10863905 DOI: 10.1002/acn3.51955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/21/2023] [Accepted: 11/11/2023] [Indexed: 12/30/2023] Open
Abstract
OBJECTIVE To determine the association between brain MRI abnormalities and incident epilepsy in older adults. METHODS Men and women (ages 45-64 years) from the Atherosclerosis Risk in Communities study were followed up from 1987 to 2018 with brain MRI performed between 2011 and 2013. We identified cases of incident late-onset epilepsy (LOE) with onset of seizures occurring after the acquisition of brain MRI. We evaluated the relative pattern of cortical thickness, subcortical volume, and white matter integrity among participants with incident LOE after MRI in comparison with participants without seizures. We examined the association between MRI abnormalities and incident LOE using Cox proportional hazards regression. Models were adjusted for demographics, hypertension, diabetes, smoking, stroke, and dementia status. RESULTS Among 1251 participants with brain MRI data, 27 (2.2%) developed LOE after MRI over a median of 6.4 years (25-75 percentile 5.8-6.9) of follow-up. Participants with incident LOE after MRI had higher levels of cortical thinning and white matter microstructural abnormalities before seizure onset compared to those without seizures. In longitudinal analyses, greater number of abnormalities was associated with incident LOE after controlling for demographic factors, risk factors for cardiovascular disease, stroke, and dementia (gray matter: hazard ratio [HR]: 2.3, 95% confidence interval [CI]: 1.0-4.9; white matter diffusivity: HR: 3.0, 95% CI: 1.2-7.3). INTERPRETATION This study demonstrates considerable gray and white matter pathology among individuals with LOE, which is present prior to the onset of seizures and provides important insights into the role of neurodegeneration, both of gray and white matter, and the risk of LOE.
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Affiliation(s)
- James J. Gugger
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Alexa E. Walter
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Ramon Diaz‐Arrastia
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Juebin Huang
- Department of NeurologyUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | | | - Robert Reid
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | - Anna M. Kucharska‐Newton
- Department of EpidemiologyUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research ProgramBethesdaMarylandUSA
| | - Andrea L. C. Schneider
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
- Department of Biostatistics, Epidemiology, and InformaticsUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Emily L. Johnson
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
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19
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Yapici O, Uzunhan TA. The role of cranial magnetic resonance imaging findings in pediatric epilepsy: A single-center experience. North Clin Istanb 2024; 11:72-80. [PMID: 38357315 PMCID: PMC10861434 DOI: 10.14744/nci.2023.39581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 07/12/2023] [Accepted: 08/30/2023] [Indexed: 02/16/2024] Open
Abstract
OBJECTIVE The aim of this study was to investigate cranial magnetic resonance imaging (MRI) findings in different age groups and genders in pediatric epilepsy, to determine the percentages of etiologic factors, and to evaluate the association between MRI positivity and treatment resistance. METHODS Cranial MRIs of 359 patients with epilepsy aged 1 month to 18 years were retrospectively evaluated. Etiologic factors as an underlying cause of epilepsy were classified as previous parenchymal damage, hippocampal sclerosis, malformations of cortical development, tumor, neurocutaneous syndrome, myelination disorder, vascular anomaly, metabolic/genetic/neurodegenerative diseases, encephalitis, and an uncategorized "other" group. Data were transferred to IBM SPSS Statistics 25.0 (SPSS Inc., Chicago, IL, USA), and descriptive statistics, correlation analyses, chi-square, and t-tests were performed. RESULTS Among the patients included in the study, 141 (39.3%) had pathological findings on MRI related to the etiology. Previous parenchymal damage (39.7%) was the most common etiologic cause in all age groups. Regarding the relationship between drug resistance and MRI positivity, MRI positivity was observed in 72% of drug-resistant cases, while a complete response to therapy was found in 67.6% of MRI-negative cases. CONCLUSION MRI guides clinicians to determine the presence of an etiologic factor as the underlying cause of childhood epilepsy before treatment planning. MRI positivity is a remarkable indicator of response to antiseizure drug treatment and drug resistance.
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Affiliation(s)
- Ozge Yapici
- Department of Radiology, Marmara University Faculty of Medicine, Pendik Training and Research Hospital, Istanbul, Turkiye
| | - Tugce Aksu Uzunhan
- Department of Child Neurology, Prof. Dr. Cemil Tascioglu City Hospital, Istanbul, Turkiye
- The current affiliation of the author: Department of Pediatrics, Atlas University Faculty of Medicine, Istanbul, Turkiye
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20
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Granovetter MC, Maallo AMS, Patterson C, Glen D, Behrmann M. Morphometrics of the preserved post-surgical hemisphere in pediatric drug-resistant epilepsy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.24.559189. [PMID: 37808659 PMCID: PMC10557613 DOI: 10.1101/2023.09.24.559189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Importance Structural integrity of cortex following cortical resection for epilepsy management has been previously characterized, but only in adult patients. Objective This study sought to determine whether morphometrics of the preserved hemisphere in pediatric cortical resection patients differ from non-neurological controls. Design This was a case-control study, from 2013-2022. Setting This was a single-site study. Participants 32 patients with childhood epilepsy surgery and 51 age- and gender-matched controls participated. Main Measures We quantified morphometrics of the preserved hemisphere at the level of gross anatomy (lateral ventricle size, volume of gray and white matter). Additionally, cortical thickness, volume, and surface area were measured for 34 cortical regions segmented with the Desikan-Killiany atlas, and, last, volumes of nine subcortical regions were also quantified. Results 13 patients with left hemisphere (LH) surgery and a preserved right hemisphere (RH) (median age/median absolute deviation of age: 15.7/1.7 yr; 6 females, 7 males) and 19 patients with RH surgery and a preserved LH (15.4/3.7 yr; 11 females, 8 males) were compared to 51 controls (14.8/4.9 yr; 24 females, 27 males). Patient groups had larger ventricles and reduced total white matter volume relative to controls, and only patients with a preserved RH, but not patients with a preserved LH, had reduced total gray matter volume relative to controls. Furthermore, patients with a preserved RH had lower cortical thickness and volume and greater surface area of several cortical regions, relative to controls. Patients with a preserved LH had no differences in thickness, volume, or area, of any of the 34 cortical regions, relative to controls. Moreover, both LH and RH patients showed reduced volumes in select subcortical structures, relative to controls. Conclusions and Relevance That left-sided, but not right-sided, resection is associated with more pronounced reduction in cortical thickness and volume and increased cortical surface area relative to typically developing, age-matched controls suggests that the preserved RH undergoes structural plasticity to an extent not observed in cases of right-sided pediatric resection. Future work probing the association of the current findings with neuropsychological outcomes will be necessary to understand the implications of these structural findings for clinical practice.
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Affiliation(s)
- Michael C. Granovetter
- Department of Psychology and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA 15213
- School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA 15213
| | - Anne Margarette S. Maallo
- Department of Psychology and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA 15213
| | - Christina Patterson
- Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA 15213
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, MD, USA 20892
| | - Marlene Behrmann
- Department of Psychology and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA 15213
- Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA, USA 15213
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Duma GM, Pellegrino G, Rabuffo G, Danieli A, Antoniazzi L, Vitale V, Scotto Opipari R, Bonanni P, Sorrentino P. Altered spread of waves of activities at large scale is influenced by cortical thickness organization in temporal lobe epilepsy: a magnetic resonance imaging-high-density electroencephalography study. Brain Commun 2023; 6:fcad348. [PMID: 38162897 PMCID: PMC10754317 DOI: 10.1093/braincomms/fcad348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/11/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024] Open
Abstract
Temporal lobe epilepsy is a brain network disorder characterized by alterations at both the structural and the functional levels. It remains unclear how structure and function are related and whether this has any clinical relevance. In the present work, we adopted a novel methodological approach investigating how network structural features influence the large-scale dynamics. The functional network was defined by the spatio-temporal spreading of aperiodic bursts of activations (neuronal avalanches), as observed utilizing high-density electroencephalography in patients with temporal lobe epilepsy. The structural network was modelled as the region-based thickness covariance. Loosely speaking, we quantified the similarity of the cortical thickness of any two brain regions, both across groups and at the individual level, the latter utilizing a novel approach to define the subject-wise structural covariance network. In order to compare the structural and functional networks (at the nodal level), we studied the correlation between the probability that a wave of activity would propagate from a source to a target region and the similarity of the source region thickness as compared with other target brain regions. Building on the recent evidence that large-waves of activities pathologically spread through the epileptogenic network in temporal lobe epilepsy, also during resting state, we hypothesize that the structural cortical organization might influence such altered spatio-temporal dynamics. We observed a stable cluster of structure-function correlation in the bilateral limbic areas across subjects, highlighting group-specific features for left, right and bilateral temporal epilepsy. The involvement of contralateral areas was observed in unilateral temporal lobe epilepsy. We showed that in temporal lobe epilepsy, alterations of structural and functional networks pair in the regions where seizures propagate and are linked to disease severity. In this study, we leveraged on a well-defined model of neurological disease and pushed forward personalization approaches potentially useful in clinical practice. Finally, the methods developed here could be exploited to investigate the relationship between structure-function networks at subject level in other neurological conditions.
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Affiliation(s)
- Gian Marco Duma
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Giovanni Pellegrino
- Epilepsy Program, Schulich School of Medicine and Dentistry, Western University, London N6A5C1, Canada
| | - Giovanni Rabuffo
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille 13005, France
| | - Alberto Danieli
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Lisa Antoniazzi
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Valerio Vitale
- Department of Neuroscience, Neuroradiology Unit, San Bortolo Hospital, Vicenza 36100, Italy
| | | | - Paolo Bonanni
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille 13005, France
- Department of Biomedical Sciences, University of Sassari, Sassari 07100, Italy
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22
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Antoine LH, Tanner JJ, Mickle AM, Gonzalez CE, Kusko DA, Watts KA, Rumble DD, Buchanan TL, Sims AM, Staud R, Lai S, Deshpande H, Phillips B, Buford TW, Aroke EN, Redden DT, Fillingim RB, Goodin BR, Sibille KT. Greater socioenvironmental risk factors and higher chronic pain stage are associated with thinner bilateral temporal lobes. Brain Behav 2023; 13:e3330. [PMID: 37984835 PMCID: PMC10726852 DOI: 10.1002/brb3.3330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 10/31/2023] [Accepted: 11/02/2023] [Indexed: 11/22/2023] Open
Abstract
INTRODUCTION Previous research indicates ethnic/race group differences in pain and neurodegenerative diseases. Accounting for socioenvironmental factors reduces ethnic/race group differences in clinical and experimental pain. In the current study sample, we previously reported that in individuals with knee pain, ethnic/race group differences were observed in bilateral temporal lobe thickness, areas of the brain associated with risk for Alzheimer's disease, and related dementias. The purpose of the study was to determine if socioenvironmental factors reduce or account for previously observed ethnic/race group differences and explore if a combined effect of socioenvironmental risk and chronic pain severity on temporal lobe cortices is evident. METHODS Consistent with the prior study, the sample was comprised of 147 adults (95 women, 52 men), 45-85 years of age, who self-identified as non-Hispanic Black (n = 72) and non-Hispanic White (n = 75), with knee pain with/at risk for osteoarthritis. Measures included demographics, health history, pain questionnaires, cognitive screening, body mass index, individual- and community-level socioenvironmental factors (education, income, household size, marital and insurance status, and area deprivation index), and brain imaging. We computed a summative socioenvironmental risk index. RESULTS Regression analyses showed that with the inclusion of socioenvironmental factors, the model was significant (p < .001), and sociodemographic (ethnic/race) group differences were not significant (p = .118). Additionally, findings revealed an additive stress load pattern indicating thinner temporal lobe cortices with greater socioenvironmental risk and chronic pain severity (p = .048). IMPLICATIONS Although individual socioenvironmental factors were not independent predictors, when collectively combined in models, ethnic/race group differences in bilateral temporal lobe structures were not replicated. Further, combined socioenvironmental risk factors and higher chronic pain severity were associated with thinner bilateral temporal lobes.
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Affiliation(s)
- Lisa H. Antoine
- Department of PsychologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Jared J. Tanner
- Department of Clinical and Health PsychologyUniversity of FloridaGainesvilleFloridaUSA
| | - Angela M. Mickle
- Pain Research & Intervention Center of ExcellenceUniversity of FloridaGainesvilleFloridaUSA
- Department of Physical Medicine & RehabilitationUniversity of FloridaGainesvilleFloridaUSA
| | - Cesar E. Gonzalez
- Department of PsychologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Daniel A. Kusko
- Department of PsychologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Kristen Allen Watts
- Heersink School of MedicineUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Deanna D. Rumble
- Department of Psychology and CounselingUniversity of Central ArkansasConwayArkansasUSA
| | - Taylor L. Buchanan
- Center for Exercise MedicineUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Andrew M. Sims
- Department of BiostatisticsUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Roland Staud
- Department of MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Song Lai
- Department of Radiation OncologyUniversity of FloridaGainesvilleFloridaUSA
| | | | - Brandis Phillips
- Department of Accounting & FinanceNorth Carolina A&T State UniversityGreensboroNorth CarolinaUSA
| | - Thomas W. Buford
- Department of Medicine − Division of Gerontology, Geriatrics, and Palliative CareUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- Birmingham/Atlanta Geriatric Research, Education, and Clinical CenterBirmingham VA Medical CenterBirminghamAlabamaUSA
| | - Edwin N. Aroke
- School of NursingUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - David T. Redden
- Department of BiostatisticsUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Roger B. Fillingim
- Pain Research & Intervention Center of ExcellenceUniversity of FloridaGainesvilleFloridaUSA
- Department of Community of Dentistry and Behavioral SciencesUniversity of FloridaGainesvilleFloridaUSA
| | - Burel R. Goodin
- Department of PsychologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- Department of AnesthesiologyWashington University, Washington University Pain CenterSt. LouisMissouriUSA
| | - Kimberly T. Sibille
- Pain Research & Intervention Center of ExcellenceUniversity of FloridaGainesvilleFloridaUSA
- Department of Physical Medicine & RehabilitationUniversity of FloridaGainesvilleFloridaUSA
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23
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Xiao F, Caciagli L, Wandschneider B, Sone D, Young AL, Vos SB, Winston GP, Zhang Y, Liu W, An D, Kanber B, Zhou D, Sander JW, Thom M, Duncan JS, Alexander DC, Galovic M, Koepp MJ. Identification of different MRI atrophy progression trajectories in epilepsy by subtype and stage inference. Brain 2023; 146:4702-4716. [PMID: 37807084 PMCID: PMC10629797 DOI: 10.1093/brain/awad284] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 06/30/2023] [Accepted: 08/02/2023] [Indexed: 10/10/2023] Open
Abstract
Artificial intelligence (AI)-based tools are widely employed, but their use for diagnosis and prognosis of neurological disorders is still evolving. Here we analyse a cross-sectional multicentre structural MRI dataset of 696 people with epilepsy and 118 control subjects. We use an innovative machine-learning algorithm, Subtype and Stage Inference, to develop a novel data-driven disease taxonomy, whereby epilepsy subtypes correspond to distinct patterns of spatiotemporal progression of brain atrophy.In a discovery cohort of 814 individuals, we identify two subtypes common to focal and idiopathic generalized epilepsies, characterized by progression of grey matter atrophy driven by the cortex or the basal ganglia. A third subtype, only detected in focal epilepsies, was characterized by hippocampal atrophy. We corroborate external validity via an independent cohort of 254 people and confirm that the basal ganglia subtype is associated with the most severe epilepsy.Our findings suggest fundamental processes underlying the progression of epilepsy-related brain atrophy. We deliver a novel MRI- and AI-guided epilepsy taxonomy, which could be used for individualized prognostics and targeted therapeutics.
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Affiliation(s)
- Fenglai Xiao
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
- Department of Neurology, Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Britta Wandschneider
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
| | - Daichi Sone
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
- Department of Psychiatry, The Jikei University School of Medicine, Tokyo, 105-8461, Japan
| | - Alexandra L Young
- Centre for Medical Image Computing, Departments of Computer Science, Medical Physics, and Biomedical Engineering, UCL, London, WC1E 6BT, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Sjoerd B Vos
- Centre for Medical Image Computing, Departments of Computer Science, Medical Physics, and Biomedical Engineering, UCL, London, WC1E 6BT, UK
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- Centre for Microscopy, Characterisation, and Analysis, University of Western Australia, Perth, WA 6009, Australia
| | - Gavin P Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
- Department of Medicine, Division of Neurology, Queen’s University, Kingston, K7L 3N6, Canada
- Centre for Neuroscience Studies, Queen’s University, Kingston, K7L 3N6, Canada
| | - Yingying Zhang
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Wenyu Liu
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Dongmei An
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Baris Kanber
- Centre for Medical Image Computing, Departments of Computer Science, Medical Physics, and Biomedical Engineering, UCL, London, WC1E 6BT, UK
| | - Dong Zhou
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Josemir W Sander
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
- Stichting Epilepsie Instellingen Nederland – (SEIN), Heemstede, 2103SW, The Netherlands
| | - Maria Thom
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Departments of Computer Science, Medical Physics, and Biomedical Engineering, UCL, London, WC1E 6BT, UK
| | - Marian Galovic
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, CH-8091, Switzerland
| | - Matthias J Koepp
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UCL-Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, SL9 0RJ, UK
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Denis C, Dabbs K, Nair VA, Mathis J, Almane DN, Lakshmanan A, Nencka A, Birn RM, Conant L, Humphries C, Felton E, Raghavan M, DeYoe EA, Binder JR, Hermann B, Prabhakaran V, Bendlin BB, Meyerand ME, Boly M, Struck AF. T1-/T2-weighted ratio reveals no alterations to gray matter myelination in temporal lobe epilepsy. Ann Clin Transl Neurol 2023; 10:2149-2154. [PMID: 37872734 PMCID: PMC10647008 DOI: 10.1002/acn3.51653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 05/29/2022] [Accepted: 06/09/2022] [Indexed: 10/25/2023] Open
Abstract
Short-range functional connectivity in the limbic network is increased in patients with temporal lobe epilepsy (TLE), and recent studies have shown that cortical myelin content correlates with fMRI connectivity. We thus hypothesized that myelin may increase progressively in the epileptic network. We compared T1w/T2w gray matter myelin maps between TLE patients and age-matched controls and assessed relationships between myelin and aging. While both TLE patients and healthy controls exhibited increased T1w/T2w intensity with age, we found no evidence for significant group-level aberrations in overall myelin content or myelin changes through time in TLE.
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Affiliation(s)
- Colin Denis
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Kevin Dabbs
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Veena A. Nair
- Department of RadiologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Jedidiah Mathis
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Dace N. Almane
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | | | - Andrew Nencka
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Rasmus M. Birn
- Department of RadiologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of PsychiatryUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Lisa Conant
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Colin Humphries
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Elizabeth Felton
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Manoj Raghavan
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Edgar A. DeYoe
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
- Department of BiophysicsMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Jeffrey R. Binder
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
- Department of BiophysicsMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Bruce Hermann
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Vivek Prabhakaran
- Department of RadiologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Barbara B. Bendlin
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Mary E. Meyerand
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of Biomedical EngineeringUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Mélanie Boly
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of PsychiatryUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Aaron F. Struck
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- William S. Middleton Veterans Administration HospitalMadisonWisconsinUSA
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25
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Huang X, Du Y, Guo D, Xie F, Zhou C. Structural-functional coupling abnormalities in temporal lobe epilepsy. Front Neurosci 2023; 17:1272514. [PMID: 37928725 PMCID: PMC10620528 DOI: 10.3389/fnins.2023.1272514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 10/04/2023] [Indexed: 11/07/2023] Open
Abstract
Background Nowadays, researchers are using advanced multimodal neuroimaging techniques to construct the brain network connectome to elucidate the complex relationship among the networks of brain functions and structure. The objective of this study was to evaluate the coupling of structural connectivity (SC) and functional connectivity (FC) in the entire brain of healthy controls (HCs), and to investigate modifications in SC-FC coupling in individuals suffering from temporal lobe epilepsy (TLE). Methods We evaluated 65 patients with TLE matched for age and gender with 48 healthy controls. The SC-FC coupling between regions was determined, based on which whole-brain nodes were clustered. Differences in the coupling among the three groups of nodes were compared. To further validate the results obtained, the within-cluster coupling indices of the three groups were compared to determine the inter-group differences. Results Nodes were divided into five clusters. Cluster 1 was primarily located in the limbic system (n = 9/27), whereas cluster 5 was mainly within the visual network (n = 12/29). By comparing average cluster SC-FC coupling in each cluster of the three groups, we identified marked discrepancies within the three cohorts in Cluster 3 (p = 0.001), Cluster 4 (p < 0.001), and Cluster 5 (p < 0.001). Post-hoc analysis revealed that the SC-FC coupling strengths in LTLE and RTLE were significantly lower than that in HCs in Cluster 3 (PL = 0.001/PR = 0.003), Cluster 4 (PL = 0.001/PR < 0.001), and Cluster 5 (PL < 0.001/PR < 0.001). We also observed that the within-cluster SC-FC coupling in cluster 5 of left- and right TLE was significantly lower than in HCs (PL = 0.0001, PR = 0.0005). Conclusion The SC and FC are inconsistently coupled across the brain with spatial heterogeneity. In the fifth cluster with the highest degree of coupling in HCs, the average SC-FC coupling index of individuals with TLE was notably less than that of HCs, manifesting that brain regions with high coupling may be more delicate and prone to pathological disruption.
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Affiliation(s)
- Xiaoting Huang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yangsa Du
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Danni Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Fangfang Xie
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Chunyao Zhou
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
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Kiersnowski OC, Winston GP, Caciagli L, Biondetti E, Elbadri M, Buck S, Duncan JS, Thornton JS, Shmueli K, Vos SB. Quantitative susceptibility mapping identifies hippocampal and other subcortical grey matter tissue composition changes in temporal lobe epilepsy. Hum Brain Mapp 2023; 44:5047-5064. [PMID: 37493334 PMCID: PMC10502681 DOI: 10.1002/hbm.26432] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 07/04/2023] [Accepted: 07/07/2023] [Indexed: 07/27/2023] Open
Abstract
Temporal lobe epilepsy (TLE) is associated with widespread brain alterations. Using quantitative susceptibility mapping (QSM) alongside transverse relaxation rate (R 2 * ), we investigated regional brain susceptibility changes in 36 patients with left-sided (LTLE) or right-sided TLE (RTLE) secondary to hippocampal sclerosis, and 27 healthy controls (HC). We compared three susceptibility calculation methods to ensure image quality. Correlations of susceptibility andR 2 * with age of epilepsy onset, frequency of focal-to-bilateral tonic-clonic seizures (FBTCS), and neuropsychological test scores were examined. Weak-harmonic QSM (WH-QSM) successfully reduced noise and removed residual background field artefacts. Significant susceptibility increases were identified in the left putamen in the RTLE group compared to the LTLE group, the right putamen and right thalamus in the RTLE group compared to HC, and a significant susceptibility decrease in the left hippocampus in LTLE versus HC. LTLE patients who underwent epilepsy surgery showed significantly lower left-versus-right hippocampal susceptibility. SignificantR 2 * changes were found between TLE and HC groups in the amygdala, putamen, thalamus, and in the hippocampus. Specifically, decreased R2 * was found in the left and right hippocampus in LTLE and RTLE, respectively, compared to HC. Susceptibility andR 2 * were significantly correlated with cognitive test scores in the hippocampus, globus pallidus, and thalamus. FBTCS frequency correlated positively with ipsilateral thalamic and contralateral putamen susceptibility and withR 2 * in bilateral globi pallidi. Age of onset was correlated with susceptibility in the hippocampus and putamen, and withR 2 * in the caudate. Susceptibility andR 2 * changes observed in TLE groups suggest selective loss of low-myelinated neurons alongside iron redistribution in the hippocampi, predominantly ipsilaterally, indicating QSM's sensitivity to local pathology. Increased susceptibility andR 2 * in the thalamus and putamen suggest increased iron content and reflect disease severity.
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Affiliation(s)
- Oliver C. Kiersnowski
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Gavin P. Winston
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
- Department of Medicine, Division of NeurologyQueen's UniversityKingstonCanada
| | - Lorenzo Caciagli
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Emma Biondetti
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Department of Neuroscience, Imaging and Clinical SciencesInstitute for Advanced Biomedical Technologies, “D'Annunzio” University of Chieti‐PescaraChietiItaly
| | - Maha Elbadri
- Department of NeurologyQueen Elizabeth HospitalBirminghamUK
| | - Sarah Buck
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
| | - John S. Duncan
- Department of Clinical and Experimental EpilepsyUniversity College LondonLondonUK
| | - John S. Thornton
- Neuroradiological Academic UnitUCL Queen Square Institute of Neurology, University College LondonLondonUK
| | - Karin Shmueli
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Sjoerd B. Vos
- Neuroradiological Academic UnitUCL Queen Square Institute of Neurology, University College LondonLondonUK
- Centre for Microscopy, Characterisation, and AnalysisThe University of Western AustraliaNedlandsAustralia
- Centre for Medical Image Computing, Computer Science departmentUniversity College LondonLondonUK
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27
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Pellinen J, Pardoe H, Sillau S, Barnard S, French J, Knowlton R, Lowenstein D, Cascino GD, Glynn S, Jackson G, Szaflarski J, Morrison C, Meador KJ, Kuzniecky R. Later onset focal epilepsy with roots in childhood: Evidence from early learning difficulty and brain volumes in the Human Epilepsy Project. Epilepsia 2023; 64:2761-2770. [PMID: 37517050 DOI: 10.1111/epi.17727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/26/2023] [Accepted: 07/26/2023] [Indexed: 08/01/2023]
Abstract
OBJECTIVE Visual assessment of magnetic resonance imaging (MRI) from the Human Epilepsy Project 1 (HEP1) found 18% of participants had atrophic brain changes relative to age without known etiology. Here, we identify the underlying factors related to brain volume differences in people with focal epilepsy enrolled in HEP1. METHODS Enrollment data for participants with complete records and brain MRIs were analyzed, including 391 participants aged 12-60 years. HEP1 excluded developmental or cognitive delay with intelligence quotient <70, and participants reported any formal learning disability diagnoses, repeated grades, and remediation. Prediagnostic seizures were quantified by semiology, frequency, and duration. T1-weighted brain MRIs were analyzed using Sequence Adaptive Multimodal Segmentation (FreeSurfer v7.2), from which a brain tissue volume to intracranial volume ratio was derived and compared to clinically relevant participant characteristics. RESULTS Brain tissue volume changes observable on visual analyses were quantified, and a brain tissue volume to intracranial volume ratio was derived to compare with clinically relevant variables. Learning difficulties were associated with decreased brain tissue volume to intracranial volume, with a ratio reduction of .005 for each learning difficulty reported (95% confidence interval [CI] = -.007 to -.002, p = .0003). Each 10-year increase in age at MRI was associated with a ratio reduction of .006 (95% CI = -.007 to -.005, p < .0001). For male participants, the ratio was .011 less than for female participants (95% CI = -.014 to -.007, p < .0001). There were no effects from seizures, employment, education, seizure semiology, or temporal lobe electroencephalographic abnormalities. SIGNIFICANCE This study shows lower brain tissue volume to intracranial volume in people with newly treated focal epilepsy and learning difficulties, suggesting developmental factors are an important marker of brain pathology related to neuroanatomical changes in focal epilepsy. Like the general population, there were also independent associations between brain volume, age, and sex in the study population.
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Affiliation(s)
- Jacob Pellinen
- University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Heath Pardoe
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
| | - Stefan Sillau
- University of Colorado School of Medicine, Aurora, Colorado, USA
| | | | - Jacqueline French
- New York University Comprehensive Epilepsy Center, New York, New York, USA
| | - Robert Knowlton
- University of California, San Francisco, San Francisco, California, USA
| | - Daniel Lowenstein
- University of California, San Francisco, San Francisco, California, USA
| | | | - Simon Glynn
- University of Michigan, Ann Arbor, Michigan, USA
| | - Graeme Jackson
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
| | | | - Chris Morrison
- New York University Comprehensive Epilepsy Center, New York, New York, USA
| | - Kimford J Meador
- Stanford University Neuroscience Health Center, Palo Alto, California, USA
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28
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Yang MH, Kim EH, Choi ES, Ko H. Comparison of Normative Percentiles of Brain Volume Obtained from NeuroQuant ® vs. DeepBrain ® in the Korean Population: Correlation with Cranial Shape. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2023; 84:1080-1090. [PMID: 37869130 PMCID: PMC10585089 DOI: 10.3348/jksr.2023.0006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 03/13/2023] [Accepted: 04/15/2023] [Indexed: 10/24/2023]
Abstract
Purpose This study aimed to compare the volume and normative percentiles of brain volumetry in the Korean population using quantitative brain volumetric MRI analysis tools NeuroQuant® (NQ) and DeepBrain® (DB), and to evaluate whether the differences in the normative percentiles of brain volumetry between the two tools is related to cranial shape. Materials and Methods In this retrospective study, we analyzed the brain volume reports obtained from NQ and DB in 163 participants without gross structural brain abnormalities. We measured three-dimensional diameters to evaluate the cranial shape on T1-weighted images. Statistical analyses were performed using intra-class correlation coefficients and linear correlations. Results The mean normative percentiles of the thalamus (90.8 vs. 63.3 percentile), putamen (90.0 vs. 60.0 percentile), and parietal lobe (80.1 vs. 74.1 percentile) were larger in the NQ group than in the DB group, whereas that of the occipital lobe (18.4 vs. 68.5 percentile) was smaller in the NQ group than in the DB group. We found a significant correlation between the mean normative percentiles obtained from the NQ and cranial shape: the mean normative percentile of the occipital lobe increased with the anteroposterior diameter and decreased with the craniocaudal diameter. Conclusion The mean normative percentiles obtained from NQ and DB differed significantly for many brain regions, and these differences may be related to cranial shape.
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29
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Pei H, Ma S, Yan W, Liu Z, Wang Y, Yang Z, Li Q, Yao D, Jiang S, Luo C, Yu L. Functional and structural networks decoupling in generalized tonic-clonic seizures and its reorganization by drugs. Epilepsia Open 2023; 8:1038-1048. [PMID: 37394869 PMCID: PMC10472403 DOI: 10.1002/epi4.12781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 06/27/2023] [Indexed: 07/04/2023] Open
Abstract
OBJECTIVE To investigate potential functional and structural large-scale network disturbances in untreated patients with generalized tonic-clonic seizures (GTCS) and the effects of antiseizure drugs. METHODS In this study, 41 patients with GTCS, comprising 21 untreated patients and 20 patients who received antiseizure medications (ASMs), and 29 healthy controls were recruited to construct large-scale brain networks based on resting-state functional magnetic resonance imaging and diffusion tensor imaging. Structural and functional connectivity and network-level weighted correlation probability (NWCP) were further investigated to identify network features that corresponded to response to ASMs. RESULTS Untreated patients showed more extensive enhancement of functional and structural connections than controls. Specifically, we observed abnormally enhanced connections between the default mode network (DMN) and the frontal-parietal network. In addition, treated patients showed similar functional connection strength to that of the control group. However, all patients exhibited similar structural network alterations. Moreover, the NWCP value was lower for connections within the DMN and between the DMN and other networks in the untreated patients; receiving ASMs could reverse this pattern. SIGNIFICANCE Our study identified alterations in structural and functional connectivity in patients with GTCS. The influence of ASMs may be more noticeable within the functional network; moreover, abnormalities in both the functional and structural coupling state may be improved by ASM treatment. Therefore, the coupling state of structural and functional connectivity may be used as an indicator of the efficacy of ASMs.
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Affiliation(s)
- Haonan Pei
- The Clinical Hospital of Chengdu Brain Science InstituteMOE Key Lab for NeuroinformationSchool of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- Research Unit of NeuroInformation (2019RU035)Chinese Academy of Medical SciencesChengduChina
| | - Shuai Ma
- The Clinical Hospital of Chengdu Brain Science InstituteMOE Key Lab for NeuroinformationSchool of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- Research Unit of NeuroInformation (2019RU035)Chinese Academy of Medical SciencesChengduChina
- Neurology DepartmentSichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Wei Yan
- The Clinical Hospital of Chengdu Brain Science InstituteMOE Key Lab for NeuroinformationSchool of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- Research Unit of NeuroInformation (2019RU035)Chinese Academy of Medical SciencesChengduChina
| | - Zetao Liu
- The Clinical Hospital of Chengdu Brain Science InstituteMOE Key Lab for NeuroinformationSchool of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- Research Unit of NeuroInformation (2019RU035)Chinese Academy of Medical SciencesChengduChina
| | - Yuehan Wang
- The Clinical Hospital of Chengdu Brain Science InstituteMOE Key Lab for NeuroinformationSchool of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- Research Unit of NeuroInformation (2019RU035)Chinese Academy of Medical SciencesChengduChina
| | - Zhihuan Yang
- The Clinical Hospital of Chengdu Brain Science InstituteMOE Key Lab for NeuroinformationSchool of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- Research Unit of NeuroInformation (2019RU035)Chinese Academy of Medical SciencesChengduChina
| | - Qifu Li
- Department of NeurologyThe First Affiliated Hospital of Hainan Medical UniversityHaikouChina
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science InstituteMOE Key Lab for NeuroinformationSchool of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- Research Unit of NeuroInformation (2019RU035)Chinese Academy of Medical SciencesChengduChina
- Department of NeurologyThe First Affiliated Hospital of Hainan Medical UniversityHaikouChina
- High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science InstituteMOE Key Lab for NeuroinformationSchool of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- Research Unit of NeuroInformation (2019RU035)Chinese Academy of Medical SciencesChengduChina
- High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science InstituteMOE Key Lab for NeuroinformationSchool of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- Research Unit of NeuroInformation (2019RU035)Chinese Academy of Medical SciencesChengduChina
- High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan ProvinceUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Liang Yu
- Neurology DepartmentSichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of ChinaChengduChina
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Reyes A, Schneider ALC, Kucharska-Newton AM, Gottesman RF, Johnson EL, McDonald CR. Cognitive phenotypes in late-onset epilepsy: results from the atherosclerosis risk in communities study. Front Neurol 2023; 14:1230368. [PMID: 37745655 PMCID: PMC10513940 DOI: 10.3389/fneur.2023.1230368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Accepted: 08/02/2023] [Indexed: 09/26/2023] Open
Abstract
Introduction Cognitive phenotyping is a widely used approach to characterize the heterogeneity of deficits in patients with a range of neurological disorders but has only recently been applied to patients with epilepsy. In this study, we identify cognitive phenotypes in older adults with late-onset epilepsy (LOE) and examine their demographic, clinical, and vascular profiles. Further, we examine whether specific phenotypes pose an increased risk for progressive cognitive decline. Methods Participants were part of the Atherosclerosis Risk in Communities Study (ARIC), a prospective longitudinal community-based cohort study of 15,792 individuals initially enrolled in 1987-1989. LOE was identified from linked Centers for Medicare and Medicaid Services claims data. Ninety-one participants with LOE completed comprehensive testing either prior to or after seizure onset as part of a larger cohort in the ARIC Neurocognitive Study in either 2011-2013 or 2016-2017 (follow-up mean = 4.9 years). Cognitive phenotypes in individuals with LOE were derived by calculating test-level impairments for each participant (i.e., ≤1 SD below cognitively normal participants on measures of language, memory, and executive function/processing speed); and then assigning participants to phenotypes if they were impaired on at least two tests within a domain. The total number of impaired domains was used to determine the cognitive phenotypes (i.e., Minimal/No Impairment, Single Domain, or Multidomain). Results At our baseline (Visit 5), 36.3% met criteria for Minimal/No Impairment, 35% for Single Domain Impairment (with executive functioning/ processing speed impaired in 53.6%), and 28.7% for Multidomain Impairment. The Minimal/No Impairment group had higher education and occupational complexity. There were no differences in clinical or vascular risk factors across phenotypes. Of those participants with longitudinal data (Visit 6; n = 24), 62.5% declined (i.e., progressed to a more impaired phenotype) and 37.5% remained stable. Those who remained stable were more highly educated compared to those that declined. Discussion Our results demonstrate the presence of identifiable cognitive phenotypes in older adults with LOE. These results also highlight the high prevalence of cognitive impairments across domains, with deficits in executive function/processing speed the most common isolated impairment. We also demonstrate that higher education was associated with a Minimal/No Impairment phenotype and lower risk for cognitive decline over time.
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Affiliation(s)
- Anny Reyes
- Department of Radiation Medicine & Applied Sciences, University of California, San Diego, La Jolla, CA, United States
| | - Andrea L. C. Schneider
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Anna M. Kucharska-Newton
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD, United States
| | - Emily L. Johnson
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Carrie R. McDonald
- Department of Radiation Medicine & Applied Sciences, University of California, San Diego, La Jolla, CA, United States
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
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31
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Lenge M, Balestrini S, Mei D, Macconi L, Caligiuri ME, Cuccarini V, Aquino D, Mazzi F, d’Incerti L, Darra F, Bernardina BD, Guerrini R. Morphometry and network-based atrophy patterns in SCN1A-related Dravet syndrome. Cereb Cortex 2023; 33:9532-9541. [PMID: 37344172 PMCID: PMC10431750 DOI: 10.1093/cercor/bhad224] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 06/04/2023] [Accepted: 06/05/2023] [Indexed: 06/23/2023] Open
Abstract
Mutations of the voltage-gated sodium channel SCN1A gene (MIM#182389) are among the most clinically relevant epilepsy-related genetic mutations and present variable phenotypes, from the milder genetic epilepsy with febrile seizures plus to Dravet syndrome, a severe developmental and epileptic encephalopathy. Qualitative neuroimaging studies have identified malformations of cortical development in some patients and mild atrophic changes, partially confirmed by quantitative studies. Precise correlations between MRI findings and clinical variables have not been addressed. We used morphometric methods and network-based models to detect abnormal brain structural patterns in 34 patients with SCN1A-related epilepsy, including 22 with Dravet syndrome. By measuring the morphometric characteristics of the cortical mantle and volume of subcortical structures, we found bilateral atrophic changes in the hippocampus, amygdala, and the temporo-limbic cortex (P-value < 0.05). By correlating atrophic patterns with brain connectivity profiles, we found the region of the hippocampal formation as the epicenter of the structural changes. We also observed that Dravet syndrome was associated with more severe atrophy patterns with respect to the genetic epilepsy with febrile seizures plus phenotype (r = -0.0613, P-value = 0.03), thus suggesting that both the underlying mutation and seizure severity contribute to determine atrophic changes.
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Affiliation(s)
- Matteo Lenge
- Neuroscience Department, Meyer Children’s Hospital IRCCS, 50139, Florence, Italy
| | - Simona Balestrini
- Neuroscience Department, Meyer Children’s Hospital IRCCS, 50139, Florence, Italy
| | - Davide Mei
- Neuroscience Department, Meyer Children’s Hospital IRCCS, 50139, Florence, Italy
| | - Letizia Macconi
- Neuroradiology Unit, Meyer Children’s Hospital IRCCS, 50139, Florence, Italy
| | - Maria Eugenia Caligiuri
- Neuroscience Research Center, Department of Medical and Surgical Sciences, Magna Grecia University, 88100, Catanzaro, Italy
| | - Valeria Cuccarini
- Neuroradiology Unit, Fondazione IRCCS Neurologico Carlo Besta, 20100, Milan, Italy
| | - Domenico Aquino
- Neuroradiology Unit, Fondazione IRCCS Neurologico Carlo Besta, 20100, Milan, Italy
| | - Federica Mazzi
- Neuroradiology Unit, Fondazione IRCCS Neurologico Carlo Besta, 20100, Milan, Italy
| | - Ludovico d’Incerti
- Neuroradiology Unit, Meyer Children’s Hospital IRCCS, 50139, Florence, Italy
| | - Francesca Darra
- Child Neuropsychiatry Unit, Department of Engineering for Innovation Medicine University of Verona, 37100, Verona, Italy
| | - Bernardo Dalla Bernardina
- Child Neuropsychiatry Unit, Department of Engineering for Innovation Medicine University of Verona, 37100, Verona, Italy
- Pediatric Epilepsy Research Center (CREP), Azienda Ospedaliera Universitaria Integrata, 37100, Verona, Italy
| | - Renzo Guerrini
- Neuroscience Department, Meyer Children’s Hospital IRCCS, 50139, Florence, Italy
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Kaestner E, Rao J, Chang AJ, Wang ZI, Busch RM, Keller SS, Rüber T, Drane DL, Stoub T, Gleichgerrcht E, Bonilha L, Hasenstab K, McDonald C. Convolutional Neural Network Algorithm to Determine Lateralization of Seizure Onset in Patients With Epilepsy: A Proof-of-Principle Study. Neurology 2023; 101:e324-e335. [PMID: 37202160 PMCID: PMC10382265 DOI: 10.1212/wnl.0000000000207411] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 03/30/2023] [Indexed: 05/20/2023] Open
Abstract
BACKGROUND AND OBJECTIVES A new frontier in diagnostic radiology is the inclusion of machine-assisted support tools that facilitate the identification of subtle lesions often not visible to the human eye. Structural neuroimaging plays an essential role in the identification of lesions in patients with epilepsy, which often coincide with the seizure focus. In this study, we explored the potential for a convolutional neural network (CNN) to determine lateralization of seizure onset in patients with epilepsy using T1-weighted structural MRI scans as input. METHODS Using a dataset of 359 patients with temporal lobe epilepsy (TLE) from 7 surgical centers, we tested whether a CNN based on T1-weighted images could classify seizure laterality concordant with clinical team consensus. This CNN was compared with a randomized model (comparison with chance) and a hippocampal volume logistic regression (comparison with current clinically available measures). Furthermore, we leveraged a CNN feature visualization technique to identify regions used to classify patients. RESULTS Across 100 runs, the CNN model was concordant with clinician lateralization on average 78% (SD = 5.1%) of runs with the best-performing model achieving 89% concordance. The CNN outperformed the randomized model (average concordance of 51.7%) on 100% of runs with an average improvement of 26.2% and outperformed the hippocampal volume model (average concordance of 71.7%) on 85% of runs with an average improvement of 6.25%. Feature visualization maps revealed that in addition to the medial temporal lobe, regions in the lateral temporal lobe, cingulate, and precentral gyrus aided in classification. DISCUSSION These extratemporal lobe features underscore the importance of whole-brain models to highlight areas worthy of clinician scrutiny during temporal lobe epilepsy lateralization. This proof-of-concept study illustrates that a CNN applied to structural MRI data can visually aid clinician-led localization of epileptogenic zone and identify extrahippocampal regions that may require additional radiologic attention. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in patients with drug-resistant unilateral temporal lobe epilepsy, a convolutional neural network algorithm derived from T1-weighted MRI can correctly classify seizure laterality.
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Affiliation(s)
- Erik Kaestner
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Jun Rao
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Allen J Chang
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Zhong Irene Wang
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Robyn M Busch
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Simon S Keller
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Theodor Rüber
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Daniel L Drane
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Travis Stoub
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Ezequiel Gleichgerrcht
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Leonardo Bonilha
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Kyle Hasenstab
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Carrie McDonald
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA.
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Hamid C, Maiworm M, Wagner M, Knake S, Nöth U, Deichmann R, Gracien RM, Seiler A. Focal epilepsy without overt epileptogenic lesions: no evidence of microstructural brain tissue damage in multi-parametric quantitative MRI. Front Neurol 2023; 14:1175971. [PMID: 37528856 PMCID: PMC10389268 DOI: 10.3389/fneur.2023.1175971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 07/03/2023] [Indexed: 08/03/2023] Open
Abstract
Background and purpose In patients with epilepsies of structural origin, brain atrophy and pathological alterations of the tissue microstructure extending beyond the putative epileptogenic lesion have been reported. However, in patients without any evidence of epileptogenic lesions on diagnostic magnetic resonance imaging (MRI), impairment of the brain microstructure has been scarcely elucidated. Using multiparametric quantitative (q) magnetic resonance imaging MRI, we aimed to investigate diffuse impairment of the microstructural tissue integrity in MRI-negative focal epilepsy patients. Methods 27 MRI-negative patients with focal epilepsy (mean age 33.1 ± 14.2 years) and 27 matched healthy control subjects underwent multiparametric qMRI including T1, T2, and PD mapping at 3 T. After tissue segmentation based on synthetic anatomies, mean qMRI parameter values were extracted from the cerebral cortex, the white matter (WM) and the deep gray matter (GM) and compared between patients and control subjects. Apart from calculating mean values for the qMRI parameters across the respective compartments, voxel-wise analyses were performed for each tissue class. Results There were no significant differences for mean values of quantitative T1, T2, and PD obtained from the cortex, the WM and the deep GM between the groups. Furthermore, the voxel-wise analyses did not reveal any clusters indicating significant differences between patients and control subjects for the qMRI parameters in the respective compartments. Conclusions Based on the employed methodology, no indication for an impairment of the cerebral microstructural tissue integrity in MRI-negative patients with focal epilepsy was found in this study. Further research will be necessary to identify relevant factors and mechanisms contributing to microstructural brain tissue damage in various subgroups of patients with epilepsy.
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Affiliation(s)
- Celona Hamid
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - Michelle Maiworm
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Marlies Wagner
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
- Institute of Neuroradiology, Goethe University Hospital, Frankfurt, Germany
| | - Susanne Knake
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
- Epilepsy Center Hessen and Department of Neurology, Philipps-University Marburg, Marburg, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - Alexander Seiler
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
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Ballerini A, Arienzo D, Stasenko A, Schadler A, Vaudano AE, Meletti S, Kaestner E, McDonald CR. Spatial patterns of gray and white matter compromise relate to age of seizure onset in temporal lobe epilepsy. Neuroimage Clin 2023; 39:103473. [PMID: 37531834 PMCID: PMC10415805 DOI: 10.1016/j.nicl.2023.103473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 06/29/2023] [Accepted: 07/06/2023] [Indexed: 08/04/2023]
Abstract
OBJECTIVE Temporal Lobe Epilepsy (TLE) is frequently a neurodevelopmental disorder, involving subcortical volume loss, cortical atrophy, and white matter (WM) disruption. However, few studies have addressed how these pathological changes in TLE relate to one another. In this study, we investigate spatial patterns of gray and white matter degeneration in TLE and evaluate the hypothesis that the relationship among these patterns varies as a function of the age at which seizures begin. METHODS Eighty-two patients with TLE and 59 healthy controls were enrolled. T1-weighted images were used to obtain hippocampal volumes and cortical thickness estimates. Diffusion-weighted imaging was used to obtain fractional anisotropy (FA) and mean diffusivity (MD) of the superficial WM (SWM) and deep WM tracts. Analysis of covariance was used to examine patterns of WM and gray matter alterations in TLE relative to controls, controlling for age and sex. Sliding window correlations were then performed to examine the relationships between SWM degeneration, cortical thinning, and hippocampal atrophy across ages of seizure onset. RESULTS Cortical thinning in TLE followed a widespread, bilateral pattern that was pronounced in posterior centroparietal regions, whereas SWM and deep WM loss occurred mostly in ipsilateral, temporolimbic regions compared to controls. Window correlations revealed a relationship between hippocampal volume loss and whole brain SWM disruption in patients who developed epilepsy during childhood. On the other hand, in patients with adult-onset TLE, co-occurring cortical and SWM alterations were observed in the medial temporal lobe ipsilateral to the seizure focus. SIGNIFICANCE Our results suggest that although cortical, hippocampal and WM alterations appear spatially discordant at the group level, the relationship among these features depends on the age at which seizures begin. Whereas neurodevelopmental aspects of TLE may result in co-occurring WM and hippocampal degeneration near the epileptogenic zone, the onset of seizures in adulthood may set off a cascade of SWM microstructural loss and cortical atrophy of a neurodegenerative nature.
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Affiliation(s)
- Alice Ballerini
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy; Department of Psychiatry, University of California, San Diego, USA
| | - Donatello Arienzo
- Department of Psychiatry, University of California, San Diego, USA; Center for Multimodal Imaging and Genetics, University of California, San Diego, USA
| | - Alena Stasenko
- Department of Psychiatry, University of California, San Diego, USA; Center for Multimodal Imaging and Genetics, University of California, San Diego, USA
| | - Adam Schadler
- Department of Psychiatry, University of California, San Diego, USA; Center for Multimodal Imaging and Genetics, University of California, San Diego, USA
| | - Anna Elisabetta Vaudano
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy; Neurology Unit, OCB Hospital, AOU Modena, Italy
| | - Stefano Meletti
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy; Neurology Unit, OCB Hospital, AOU Modena, Italy
| | - Erik Kaestner
- Department of Psychiatry, University of California, San Diego, USA; Center for Multimodal Imaging and Genetics, University of California, San Diego, USA
| | - Carrie R McDonald
- Department of Psychiatry, University of California, San Diego, USA; Center for Multimodal Imaging and Genetics, University of California, San Diego, USA; Department of Radiation Medicine & Applied Sciences, University of California, San Diego, USA.
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Harms A, Bauer T, Witt JA, Baumgartner T, von Wrede R, Racz A, Ernst L, Becker AJ, Helmstaedter C, Surges R, Rüber T. Mesiotemporal Volumetry, Cortical Thickness, and Neuropsychological Deficits in the Long-term Course of Limbic Encephalitis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2023; 10:10/4/e200125. [PMID: 37230543 DOI: 10.1212/nxi.0000000000200125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Accepted: 03/30/2023] [Indexed: 05/27/2023]
Abstract
BACKGROUND AND OBJECTIVES Limbic encephalitis (LE) is an autoimmune disease often associated with temporal lobe epilepsy and subacute memory deficits. It is categorized into serologic subgroups, which differ in clinical progress, therapy response, and prognosis. Using longitudinal MRI analysis, we hypothesized that mesiotemporal and cortical atrophy rates would reveal serotype-specific patterns and reflect disease severity. METHODS In this longitudinal case-control study, all individuals with antibody-positive (glutamic acid decarboxylase 65 [GAD], leucine-rich glioma-inactivated protein 1 [LGI1], contactin-associated protein 2 [CASPR2], and N-methyl-d-aspartate receptor [NMDAR]) nonparaneoplastic LE according to Graus' diagnostic criteria treated between 2005 and 2019 at the University Hospital Bonn were enrolled. A longitudinal healthy cohort was included as the control group. Subcortical segmentation and cortical reconstruction of T1-weighted MRI were performed using the longitudinal framework in FreeSurfer. We applied linear mixed models to examine mesiotemporal volumes and cortical thickness longitudinally. RESULTS Two hundred fifty-seven MRI scans from 59 individuals with LE (34 female, age at disease onset [mean ± SD] 42.5 ± 20.4 years; GAD: n = 30, 135 scans; LGI1: n = 15, 55 scans; CASPR2: n = 9, 37 scans; and NMDAR: n = 5, 30 scans) were included. The healthy control group consisted of 128 scans from 41 individuals (22 female, age at first scan [mean ± SD] 37.7 ± 14.6 years). The amygdalar volume at disease onset was significantly higher in individuals with LE (p ≤ 0.048 for all antibody subgroups) compared with that in healthy controls and decreased over time in all antibody subgroups, except in the GAD subgroup. We observed a significantly higher hippocampal atrophy rate in all antibody subgroups compared with that in healthy controls (all p ≤ 0.002), except in the GAD subgroup. Cortical atrophy rates exceeded normal aging in individuals with impaired verbal memory, while those who were not impaired did not differ significantly from healthy controls. DISCUSSION Our data depict higher mesiotemporal volumes in the early disease stage, most likely due to edematous swelling, followed by volume regression and atrophy/hippocampal sclerosis in the late disease stage. Our study reveals a continuous and pathophysiologically meaningful trajectory of mesiotemporal volumetry across all serogroups and provides evidence that LE should be considered a network disorder in which extratemporal involvement is an important determinant of disease severity.
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Affiliation(s)
- Antonia Harms
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany
| | - Tobias Bauer
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany
| | - Juri-Alexander Witt
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany
| | - Tobias Baumgartner
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany
| | - Randi von Wrede
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany
| | - Attila Racz
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany
| | - Leon Ernst
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany
| | - Albert J Becker
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany
| | - Christoph Helmstaedter
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany
| | - Rainer Surges
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany
| | - Theodor Rüber
- From the Department of Epileptology (A.H., T. Bauer, J.-A.W., T. Baumgartner, R.v.W., A.R., L.E., C.H., R.S., T.R.), and Department of Neuropathology (A.J.B.), Section for Translational Epilepsy Research, University Hospital Bonn, Germany.
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Kim JR, Jo H, Park B, Park YH, Chung YH, Shon YM, Seo DW, Hong SB, Hong SC, Seo SW, Joo EY. Identifying important factors for successful surgery in patients with lateral temporal lobe epilepsy. PLoS One 2023; 18:e0288054. [PMID: 37384651 PMCID: PMC10310033 DOI: 10.1371/journal.pone.0288054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 06/18/2023] [Indexed: 07/01/2023] Open
Abstract
OBJECTIVE Lateral temporal lobe epilepsy (LTLE) has been diagnosed in only a small number of patients; therefore, its surgical outcome is not as well-known as that of mesial temporal lobe epilepsy. We aimed to evaluate the long-term (5 years) and short-term (2 years) surgical outcomes and identify possible prognostic factors in patients with LTLE. METHODS This retrospective cohort study was conducted between January 1995 and December 2018 among patients who underwent resective surgery in a university-affiliated hospital. Patients were classified as LTLE if ictal onset zone was in lateral temporal area. Surgical outcomes were evaluated at 2 and 5 years. We subdivided based on outcomes and compared clinical and neuroimaging data including cortical thickness between two groups. RESULTS Sixty-four patients were included in the study. The mean follow-up duration after the surgery was 8.4 years. Five years after surgery, 45 of the 63 (71.4%) patients achieved seizure freedom. Clinically and statistically significant prognostic factors for postsurgical outcomes were the duration of epilepsy before surgery and focal cortical dysplasia on postoperative histopathology at the 5-year follow-up. Optimal cut-off point for epilepsy duration was eight years after the seizure onset (odds ratio 4.375, p-value = 0.0214). Furthermore, we propose a model for predicting seizure outcomes 5 years after surgery using the receiver operating characteristic curve and nomogram (area under the curve = 0.733; 95% confidence interval, 0.588-0.879). Cortical thinning was observed in ipsilateral cingulate gyrus and contralateral parietal lobe in poor surgical group compared to good surgical group (p-value < 0.01, uncorrected). CONCLUSIONS The identified predictors of unfavorable surgical outcomes may help in selecting optimal candidates and identifying the optimal timing for surgery among patients with LTLE. Additionally, cortical thinning was more extensive in the poor surgical group.
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Affiliation(s)
- Jae Rim Kim
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hyunjin Jo
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Boram Park
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, South Korea
| | - Yu Hyun Park
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Yeon Hak Chung
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Young-Min Shon
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Dae-Won Seo
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Seung Bong Hong
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Seung-Chyul Hong
- Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Sang Won Seo
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Eun Yeon Joo
- Department of Neurology, Neuroscience Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
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Zawar I, Kapur J. Does Alzheimer's disease with mesial temporal lobe epilepsy represent a distinct disease subtype? Alzheimers Dement 2023; 19:2697-2706. [PMID: 36648207 PMCID: PMC10272023 DOI: 10.1002/alz.12943] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 12/19/2022] [Accepted: 12/21/2022] [Indexed: 01/18/2023]
Abstract
Alzheimer's disease (AD) patients have a high risk of developing mesial temporal lobe epilepsy (MTLE) and subclinical epileptiform activity. MTLE in AD worsens outcomes. Therefore, we need to understand the overlap between these disease processes. We hypothesize that AD with MTLE represents a distinct subtype of AD, with the interplay between tau and epileptiform activity at its core. We discuss shared pathological features including histopathology, an initial mesial temporal lobe (MTL) hyperexcitability followed by MTL dysfunction and involvement of same networks in memory (AD) and seizures (MTLE). We provide evidence that tau accumulation linearly increases neuronal hyperexcitability, neuronal hyper-excitability increases tau secretion, tau can provoke seizures, and tau reduction protects against seizures. We speculate that AD genetic mutations increase tau, which causes proportionate neuronal loss and/or hyperexcitability, leading to seizures. We discuss that tau burden in MTLE predicts cognitive deficits among (1) AD and (2) MTLE without AD. Finally, we explore the possibility that anti-seizure medications improve cognition by reducing neuronal hyper-excitability, which reduces seizures and tau accumulation and spread. HIGHLIGHTS: We hypothesize that patients with Alzheimer's disease (AD) and mesial temporal lobe epilepsy (MTLE) represents a distinct subtype of AD. AD and MTLE share histopathological features and involve overlapping neuronal and cortical networks. Hyper-phosphorylated tau (pTau) increases neuronal excitability and provoke seizures, neuronal excitability increases pTau, and pTau reduction reduces neuronal excitability and protects against seizures. The pTau burden in MTL predicts cognitive deficits among (1) AD and (2) MTLE without AD. We speculate that anti-seizure medications improve cognition by reducing neuronal excitability, which reduces seizures and pTau.
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Affiliation(s)
- Ifrah Zawar
- Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA 22908
| | - Jaideep Kapur
- Department of Neurology, University of Virginia School of Medicine, Charlottesville, VA 22908
- Department of Neuroscience, University of Virginia, Charlottesville, VA 22908
- Department of UVA brain institute, University of Virginia, Charlottesville, VA 22908
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Arnold TC, Kini LG, Bernabei JM, Revell AY, Das SR, Stein JM, Lucas TH, Englot DJ, Morgan VL, Litt B, Davis KA. Remote effects of temporal lobe epilepsy surgery: Long-term morphological changes after surgical resection. Epilepsia Open 2023; 8:559-570. [PMID: 36944585 PMCID: PMC10235552 DOI: 10.1002/epi4.12733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 03/16/2023] [Indexed: 03/23/2023] Open
Abstract
OBJECTIVE Epilepsy surgery is an effective treatment for drug-resistant patients. However, how different surgical approaches affect long-term brain structure remains poorly characterized. Here, we present a semiautomated method for quantifying structural changes after epilepsy surgery and compare the remote structural effects of two approaches, anterior temporal lobectomy (ATL), and selective amygdalohippocampectomy (SAH). METHODS We studied 36 temporal lobe epilepsy patients who underwent resective surgery (ATL = 22, SAH = 14). All patients received same-scanner MR imaging preoperatively and postoperatively (mean 2 years). To analyze postoperative structural changes, we segmented the resection zone and modified the Advanced Normalization Tools (ANTs) longitudinal cortical pipeline to account for resections. We compared global and regional annualized cortical thinning between surgical treatments. RESULTS Across procedures, there was significant cortical thinning in the ipsilateral insula, fusiform, pericalcarine, and several temporal lobe regions outside the resection zone as well as the contralateral hippocampus. Additionally, increased postoperative cortical thickness was seen in the supramarginal gyrus. Patients treated with ATL exhibited greater annualized cortical thinning compared with SAH cases (ATL: -0.08 ± 0.11 mm per year, SAH: -0.01 ± 0.02 mm per year, t = 2.99, P = 0.006). There were focal postoperative differences between the two treatment groups in the ipsilateral insula (P = 0.039, corrected). Annualized cortical thinning rates correlated with preoperative cortical thickness (r = 0.60, P < 0.001) and had weaker associations with age at surgery (r = -0.33, P = 0.051) and disease duration (r = -0.42, P = 0.058). SIGNIFICANCE Our evidence suggests that selective procedures are associated with less cortical thinning and that earlier surgical intervention may reduce long-term impacts on brain structure.
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Affiliation(s)
- T. Campbell Arnold
- Department of Bioengineering, School of Engineering & Applied ScienceUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Lohith G. Kini
- Department of Bioengineering, School of Engineering & Applied ScienceUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - John M. Bernabei
- Department of Bioengineering, School of Engineering & Applied ScienceUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Andrew Y. Revell
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Neuroscience, School of Engineering & Applied ScienceUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sandhitsu R. Das
- Department of Neurology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Joel M. Stein
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Timothy H. Lucas
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Neurosurgery, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Dario J. Englot
- Department of Neurological SurgeryVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
- Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Victoria L. Morgan
- Department of Neurological SurgeryVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
- Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Brian Litt
- Department of Bioengineering, School of Engineering & Applied ScienceUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Neurology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Kathryn A. Davis
- Center for Neuroengineering and TherapeuticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of Neurology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Xie K, Royer J, Larivière S, Rodriguez-Cruces R, Frässle S, Cabalo DG, Ngo A, DeKraker J, Auer H, Tavakol S, Weng Y, Abdallah C, Horwood L, Frauscher B, Caciagli L, Bernasconi A, Bernasconi N, Zhang Z, Concha L, Bernhardt BC. Atypical connectome topography and signal flow in temporal lobe epilepsy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.23.541934. [PMID: 37292996 PMCID: PMC10245853 DOI: 10.1101/2023.05.23.541934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Temporal lobe epilepsy (TLE) is one of the most common pharmaco-resistant epilepsies in adults. While hippocampal pathology is the hallmark of this condition, emerging evidence indicates that brain alterations extend beyond the mesiotemporal epicenter and affect macroscale brain function and cognition. We studied macroscale functional reorganization in TLE, explored structural substrates, and examined cognitive associations. We investigated a multisite cohort of 95 patients with pharmaco-resistant TLE and 95 healthy controls using state-of-the-art multimodal 3T magnetic resonance imaging (MRI). We quantified macroscale functional topographic organization using connectome dimensionality reduction techniques and estimated directional functional flow using generative models of effective connectivity. We observed atypical functional topographies in patients with TLE relative to controls, manifesting as reduced functional differentiation between sensory/motor networks and transmodal systems such as the default mode network, with peak alterations in bilateral temporal and ventromedial prefrontal cortices. TLE-related topographic changes were consistent in all three included sites and reflected reductions in hierarchical flow patterns between cortical systems. Integration of parallel multimodal MRI data indicated that these findings were independent of TLE-related cortical grey matter atrophy, but mediated by microstructural alterations in the superficial white matter immediately beneath the cortex. The magnitude of functional perturbations was robustly associated with behavioral markers of memory function. Overall, this work provides converging evidence for macroscale functional imbalances, contributing microstructural alterations, and their associations with cognitive dysfunction in TLE.
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Affiliation(s)
- Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Donna Gift Cabalo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Hans Auer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Chifaou Abdallah
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Linda Horwood
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Lorenzo Caciagli
- Department of Biomedical Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Luis Concha
- Brain Connectivity Laboratory, Institute of Neurobiology, Universidad Nacional Autónoma de Mexico (UNAM), Mexico
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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Negi D, Granak S, Shorter S, O'Leary VB, Rektor I, Ovsepian SV. Molecular Biomarkers of Neuronal Injury in Epilepsy Shared with Neurodegenerative Diseases. Neurotherapeutics 2023; 20:767-778. [PMID: 36884195 PMCID: PMC10275849 DOI: 10.1007/s13311-023-01355-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/08/2023] [Indexed: 03/09/2023] Open
Abstract
In neurodegenerative diseases, changes in neuronal proteins in the cerebrospinal fluid and blood are viewed as potential biomarkers of the primary pathology in the central nervous system (CNS). Recent reports suggest, however, that level of neuronal proteins in fluids also alters in several types of epilepsy in various age groups, including children. With increasing evidence supporting clinical and sub-clinical seizures in Alzheimer's disease, Lewy body dementia, Parkinson's disease, and in other less common neurodegenerative conditions, these findings call into question the specificity of neuronal protein response to neurodegenerative process and urge analysis of the effects of concomitant epilepsy and other comorbidities. In this article, we revisit the evidence for alterations in neuronal proteins in the blood and cerebrospinal fluid associated with epilepsy with and without neurodegenerative diseases. We discuss shared and distinctive characteristics of changes in neuronal markers, review their neurobiological mechanisms, and consider the emerging opportunities and challenges for their future research and diagnostic use.
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Affiliation(s)
- Deepika Negi
- Faculty of Engineering and Science, University of Greenwich London, Chatham Maritime, Kent, ME4 4TB, UK
| | - Simon Granak
- National Institute of Mental Health, Topolova 748, Klecany, 25067, Czech Republic
| | - Susan Shorter
- Faculty of Engineering and Science, University of Greenwich London, Chatham Maritime, Kent, ME4 4TB, UK
| | - Valerie B O'Leary
- Department of Medical Genetics, Third Faculty of Medicine, Charles University, Ruská 87, Prague, 10000, Czech Republic
| | - Ivan Rektor
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Saak V Ovsepian
- Faculty of Engineering and Science, University of Greenwich London, Chatham Maritime, Kent, ME4 4TB, UK.
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Brain structural changes in preschool children with MRI-negative epilepsy. Neuroradiology 2023; 65:945-959. [PMID: 36869933 DOI: 10.1007/s00234-023-03137-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 02/23/2023] [Indexed: 03/05/2023]
Abstract
PURPOSE To investigate abnormalities in cortical and subcortical structures of the brain in preschool children with MRI-negative epilepsy. METHODS Cortical thickness, cortical mean curvature, cortical surface area, cortical volume, and volumes of subcortical structures were measured using Freesurfer software in preschool children with epilepsy and age-matched controls. RESULTS Findings showed cortical thickening in the left fusiform gyrus, left middle temporal gyrus, right suborbital sulcus, and right gyrus rectus, and cortical thinning mainly in the parietal lobe of preschool children with epilepsy compared to controls. The difference in cortical thickness in the left superior parietal lobule remained after correction for multiple comparisons and was negatively correlated with duration of epilepsy. Cortical mean curvature, surface area, and volume were mainly altered in the frontal and temporal lobes. Changes in mean curvature in the right pericallosal sulcus were positively correlated with age at seizure onset, and changes in mean curvature in the left intraparietal sulcus and transverse parietal sulcus were positively correlated with frequency of seizures. There were no significant differences in the volumes of the subcortical structures. CONCLUSION Changes in preschool children with epilepsy occur in the cortical rather than subcortical structures of the brain. These findings further our understanding of the effects of epilepsy in preschool children and will inform management of epilepsy in this patient population.
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Xie K, Royer J, Lariviere S, Rodriguez-Cruces R, de Wael RV, Park BY, Auer H, Tavakol S, DeKraker J, Abdallah C, Caciagli L, Bassett DS, Bernasconi A, Bernasconi N, Frauscher B, Concha L, Bernhardt BC. Atypical intrinsic neural timescales in temporal lobe epilepsy. Epilepsia 2023; 64:998-1011. [PMID: 36764677 DOI: 10.1111/epi.17541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 02/06/2023] [Accepted: 02/08/2023] [Indexed: 02/12/2023]
Abstract
OBJECTIVE Temporal lobe epilepsy (TLE) is the most common pharmacoresistant epilepsy in adults. Here we profiled local neural function in TLE in vivo, building on prior evidence that has identified widespread structural alterations. Using resting-state functional magnetic resonance imaging (rs-fMRI), we mapped the whole-brain intrinsic neural timescales (INT), which reflect temporal hierarchies of neural processing. Parallel analysis of structural and diffusion MRI data examined associations with TLE-related structural compromise. Finally, we evaluated the clinical utility of INT. METHODS We studied 46 patients with TLE and 44 healthy controls from two independent sites, and mapped INT changes in patients relative to controls across hippocampal, subcortical, and neocortical regions. We examined region-specific associations to structural alterations and explored the effects of age and epilepsy duration. Supervised machine learning assessed the utility of INT for identifying patients with TLE vs controls and left- vs right-sided seizure onset. RESULTS Relative to controls, TLE showed marked INT reductions across multiple regions bilaterally, indexing faster changing resting activity, with strongest effects in the ipsilateral medial and lateral temporal regions, and bilateral sensorimotor cortices as well as thalamus and hippocampus. Findings were similar, albeit with reduced effect sizes, when correcting for structural alterations. INT reductions in TLE increased with advancing disease duration, yet findings differed from the aging effects seen in controls. INT-derived classifiers discriminated patients vs controls (balanced accuracy, 5-fold: 76% ± 2.65%; cross-site, 72%-83%) and lateralized the focus in TLE (balanced accuracy, 5-fold: 96% ± 2.10%; cross-site, 95%-97%), with high accuracy and cross-site generalizability. Findings were consistent across both acquisition sites and robust when controlling for motion and several methodological confounds. SIGNIFICANCE Our findings demonstrate atypical macroscale function in TLE in a topography that extends beyond mesiotemporal epicenters. INT measurements can assist in TLE diagnosis, seizure focus lateralization, and monitoring of disease progression, which emphasizes promising clinical utility.
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Affiliation(s)
- Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Sara Lariviere
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Bo-Yong Park
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.,Department of Data Science, Inha University, Incheon, Republic of Korea.,Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Hans Auer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Chifaou Abdallah
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Lorenzo Caciagli
- Department of Biomedical Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Dani S Bassett
- Department of Biomedical Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Santa Fe Institute, Santa Fe, New Mexico, USA
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Luis Concha
- Brain Connectivity Laboratory, Institute of Neurobiology, Universidad Nacional Autónoma de Mexico (UNAM), Juriquilla, Mexico
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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Gholipour T, DeMarco A, You X, Englot DJ, Turkeltaub PE, Koubeissi MZ, Gaillard WD, Morgan VL. Functional anomaly mapping lateralizes temporal lobe epilepsy with high accuracy in individual patients. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.05.23285034. [PMID: 36798218 PMCID: PMC9934715 DOI: 10.1101/2023.02.05.23285034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Mesial temporal lobe epilepsy (mTLE) is associated with variable dysfunction beyond the temporal lobe. We used functional anomaly mapping (FAM), a multivariate machine learning approach to resting state fMRI analysis to measure subcortical and cortical functional aberrations in patients with mTLE. We also examined the value of individual FAM in lateralizing the hemisphere of seizure onset in mTLE patients. Methods: Patients and controls were selected from an existing imaging and clinical database. After standard preprocessing of resting state fMRI, time-series were extracted from 400 cortical and 32 subcortical regions of interest (ROIs) defined by atlases derived from functional brain organization. Group-level aberrations were measured by contrasting right (RTLE) and left (LTLE) patient groups to controls in a support vector regression models, and tested for statistical reliability using permutation analysis. Individualized functional anomaly maps (FAMs) were generated by contrasting individual patients to the control group. Half of patients were used for training a classification model, and the other half for estimating the accuracy to lateralize mTLE based on individual FAMs. Results: Thirty-two right and 14 left mTLE patients (33 with evidence of hippocampal sclerosis on MRI) and 94 controls were included. At group levels, cortical regions affiliated with limbic and somatomotor networks were prominent in distinguishing RTLE and LTLE from controls. At individual levels, most TLE patients had high anomaly in bilateral mesial temporal and medial parietooccipital default mode regions. A linear support vector machine trained on 50% of patients could accurately lateralize mTLE in remaining patients (median AUC =1.0 [range 0.97-1.0], median accuracy = 96.87% [85.71-100Significance: Functional anomaly mapping confirms widespread aberrations in function, and accurately lateralizes mTLE from resting state fMRI. Future studies will evaluate FAM as a non-invasive localization method in larger datasets, and explore possible correlations with clinical characteristics and disease course.
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Relationship between visuoperceptual functions and parietal structural abnormalities in temporal lobe epilepsy. Brain Imaging Behav 2023; 17:35-43. [PMID: 36357555 DOI: 10.1007/s11682-022-00738-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/18/2022] [Indexed: 11/12/2022]
Abstract
Progressive gray matter volume reductions beyond the epileptogenic area has been described in temporal lobe epilepsy. There is less evidence regarding correlations between gray and white matter volume changepres and multi-domain cognitive performance in this setting. We aimed to investigate correlations between volume changes in parietal structures and visuospatial performance in temporal lobe epilepsy patients. we performed a cross-sectional study comparing global and regional brain volume data from 34 temporal lobe epilepsy patients and 30 healthy controls. 3D T1-weighted sequences were obtained on a 3.0 T magnet, and data were analyzed using age and sex-adjusted linear regression models. Global and regional brain volumes and cortical thickness in patients were correlated with standardized visual memory, visuoperceptual, visuospatial, and visuoconstructive parameters obtained in a per-protocol neuropsychological assessment. temporal lobe epilepsy patients had smaller volume fractions of the deep gray matter structures, putamen and nucleus accumbens, and larger cerebrospinal fluid volume fraction than controls. Correlations were found between: 1) visual memory and precuneus and inferior parietal cortical thickness; 2) visuoperceptual performance and precuneus and supramarginal white matter volumes; 3) visuospatial skills and precuneus, postcentral, and inferior and superior parietal white matter volumes; 4) visuoconstructive performance and inferior parietal white matter volume. Brain volume loss is widespread in temporal lobe epilepsy. Volumetric reductions in parietal lobe structures were associated with visuoperceptual cognitive performance.
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Li Z, Jiang C, Gao Q, Xiang W, Qi Z, Peng K, Lin J, Wang W, Deng B, Wang W. The relationship between the interictal epileptiform discharge source connectivity and cortical structural couplings in temporal lobe epilepsy. Front Neurol 2023; 14:1029732. [PMID: 36846133 PMCID: PMC9948620 DOI: 10.3389/fneur.2023.1029732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 01/09/2023] [Indexed: 02/05/2023] Open
Abstract
Objective The objective of this study was to explore the relation between interictal epileptiform discharge (IED) source connectivity and cortical structural couplings (SCs) in temporal lobe epilepsy (TLE). Methods High-resolution 3D-MRI and 32-sensor EEG data from 59 patients with TLE were collected. Principal component analysis was performed on the morphological data on MRI to obtain the cortical SCs. IEDs were labeled from EEG data and averaged. The standard low-resolution electromagnetic tomography analysis was performed to locate the source of the average IEDs. Phase-locked value was used to evaluate the IED source connectivity. Finally, correlation analysis was used to compare the IED source connectivity and the cortical SCs. Results The features of the cortical morphology in left and right TLE were similar across four cortical SCs, which could be mainly described as the default mode network, limbic regions, connections bilateral medial temporal, and connections through the ipsilateral insula. The IED source connectivity at the regions of interest was negatively correlated with the corresponding cortical SCs. Significance The cortical SCs were confirmed to be negatively related to IED source connectivity in patients with TLE as detected with MRI and EEG coregistered data. These findings suggest the important role of intervening IEDs in treating TLE.
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Affiliation(s)
- Zhensheng Li
- Department of Neurology, General Hospital of Southern Theater Command, Guangzhou, China
| | - Che Jiang
- Department of Neurosurgery, General Hospital of Southern Theater Command, Guangzhou, China
| | - Quwen Gao
- Department of Neurology, General Hospital of Southern Theater Command, Guangzhou, China
| | - Wei Xiang
- Department of Neurology, General Hospital of Southern Theater Command, Guangzhou, China
| | - Zijuan Qi
- Department of Neurology, General Hospital of Southern Theater Command, Guangzhou, China
| | - Kairun Peng
- Department of Neurology, General Hospital of Southern Theater Command, Guangzhou, China
| | - Jian Lin
- Department of Neurosurgery, General Hospital of Southern Theater Command, Guangzhou, China
| | - Wei Wang
- Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Bingmei Deng
- Department of Neurology, General Hospital of Southern Theater Command, Guangzhou, China,Bingmei Deng ✉
| | - Weimin Wang
- Department of Neurosurgery, General Hospital of Southern Theater Command, Guangzhou, China,*Correspondence: Weimin Wang ✉
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Peplow P, Martinez B. MicroRNAs as potential biomarkers in temporal lobe epilepsy and mesial temporal lobe epilepsy. Neural Regen Res 2023; 18:716-726. [DOI: 10.4103/1673-5374.354510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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Liu Y, Bao S, Englot DJ, Morgan VL, Taylor WD, Wei Y, Oguz I, Landman BA, Lyu I. Hierarchical particle optimization for cortical shape correspondence in temporal lobe resection. Comput Biol Med 2023; 152:106414. [PMID: 36525831 PMCID: PMC9832438 DOI: 10.1016/j.compbiomed.2022.106414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 11/18/2022] [Accepted: 12/03/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Anterior temporal lobe resection is an effective treatment for temporal lobe epilepsy. The post-surgical structural changes could influence the follow-up treatment. Capturing post-surgical changes necessitates a well-established cortical shape correspondence between pre- and post-surgical surfaces. Yet, most cortical surface registration methods are designed for normal neuroanatomy. Surgical changes can introduce wide ranging artifacts in correspondence, for which conventional surface registration methods may not work as intended. METHODS In this paper, we propose a novel particle method for one-to-one dense shape correspondence between pre- and post-surgical surfaces with temporal lobe resection. The proposed method can handle partial structural abnormality involving non-rigid changes. Unlike existing particle methods using implicit particle adjacency, we consider explicit particle adjacency to establish a smooth correspondence. Moreover, we propose hierarchical optimization of particles rather than full optimization of all particles at once to avoid trappings of locally optimal particle update. RESULTS We evaluate the proposed method on 25 pairs of T1-MRI with pre- and post-simulated resection on the anterior temporal lobe and 25 pairs of patients with actual resection. We show improved accuracy over several cortical regions in terms of ROI boundary Hausdorff distance with 4.29 mm and Dice similarity coefficients with average value 0.841, compared to existing surface registration methods on simulated data. In 25 patients with actual resection of the anterior temporal lobe, our method shows an improved shape correspondence in qualitative and quantitative evaluation on parcellation-off ratio with average value 0.061 and cortical thickness changes. We also show better smoothness of the correspondence without self-intersection, compared with point-wise matching methods which show various degrees of self-intersection. CONCLUSION The proposed method establishes a promising one-to-one dense shape correspondence for temporal lobe resection. The resulting correspondence is smooth without self-intersection. The proposed hierarchical optimization strategy could accelerate optimization and improve the optimization accuracy. According to the results on the paired surfaces with temporal lobe resection, the proposed method outperforms the compared methods and is more reliable to capture cortical thickness changes.
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Affiliation(s)
- Yue Liu
- College of Information Science and Engineering, Northeastern University, Shenyang, China; Department of Electrical Engineering and Computer Science, Vanderbilt University, TN, USA
| | - Shunxing Bao
- Department of Electrical Engineering and Computer Science, Vanderbilt University, TN, USA
| | - Dario J Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center, TN, USA
| | - Victoria L Morgan
- Department of Radiology & Radiological Science, Vanderbilt University Medical Center, TN, USA
| | - Warren D Taylor
- Department of Psychiatry & Behavioral Science, Vanderbilt University Medical Center, TN, USA
| | - Ying Wei
- College of Information Science and Engineering, Northeastern University, Shenyang, China; Information Technology R&D Innovation Center of Peking University, Shaoxing, China; Changsha Hisense Intelligent System Research Institute Co., Ltd, China
| | - Ipek Oguz
- Department of Electrical Engineering and Computer Science, Vanderbilt University, TN, USA
| | - Bennett A Landman
- Department of Electrical Engineering and Computer Science, Vanderbilt University, TN, USA
| | - Ilwoo Lyu
- Department of Computer Science and Engineering, UNIST, Ulsan, South Korea.
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48
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Sarbisheh I, Tapak L, Fallahi A, Fardmal J, Sadeghifar M, Nazemzadeh M, Mehvari Habibabadi J. Cortical thickness analysis in temporal lobe epilepsy using fully Bayesian spectral method in magnetic resonance imaging. BMC Med Imaging 2022; 22:222. [PMID: 36544100 PMCID: PMC9768883 DOI: 10.1186/s12880-022-00949-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Temporal lobe epilepsy (TLE) is the most common type of epilepsy associated with changes in the cerebral cortex throughout the brain. Magnetic resonance imaging (MRI) is widely used for detecting such anomalies; nevertheless, it produces spatially correlated data that cannot be considered by the usual statistical models. This study aimed to compare cortical thicknesses between patients with TLE and healthy controls by considering the spatial dependencies across different regions of the cerebral cortex in MRI. METHODS In this study, T1-weighted MRI was performed on 20 healthy controls and 33 TLE patients. Nineteen patients had a left TLE and 14 had a right TLE. Cortical thickness was measured for all individuals in 68 regions of the cerebral cortex based on images. Fully Bayesian spectral method was utilized to compare the cortical thickness of different brain regions between groups. Neural networks model was used to classify the patients using the identified regions. RESULTS For the left TLE patients, cortical thinning was observed in bilateral caudal anterior cingulate, lateral orbitofrontal (ipsilateral), the bilateral rostral anterior cingulate, frontal pole and temporal pole (ipsilateral), caudal middle frontal and rostral middle frontal (contralateral side). For the right TLE patients, cortical thinning was only observed in the entorhinal area (ipsilateral). The AUCs of the neural networks for classification of left and right TLE patients versus healthy controls were 0.939 and 1.000, respectively. CONCLUSION Alteration of cortical gray matter thickness was evidenced as common effect of epileptogenicity, as manifested by the patients in this study using the fully Bayesian spectral method by taking into account the complex structure of the data.
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Affiliation(s)
- Iman Sarbisheh
- grid.411950.80000 0004 0611 9280Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Leili Tapak
- grid.411950.80000 0004 0611 9280Department of Biostatistics, School of Public Health and Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Alireza Fallahi
- grid.411705.60000 0001 0166 0922Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Instruments Institute (AMTII), Tehran University of Medical Sciences, Tehran, Iran ,grid.459564.f0000 0004 0482 9174Biomedical Engineering Department, Hamedan University of Technology, Hamedan, Iran
| | - Javad Fardmal
- grid.411950.80000 0004 0611 9280Department of Biostatistics, School of Public Health and Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Majid Sadeghifar
- grid.411807.b0000 0000 9828 9578Department of Statistics, Faculty of Science, Bu-Ali Sina University, Hamadan, Iran
| | - MohammadReza Nazemzadeh
- grid.411705.60000 0001 0166 0922Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Instruments Institute (AMTII), Tehran University of Medical Sciences, Tehran, Iran ,grid.411705.60000 0001 0166 0922Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran
| | - Jafar Mehvari Habibabadi
- grid.411036.10000 0001 1498 685XDepartment of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
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49
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Gupta S, Razdan R, Hanumanthu R, Tomycz L, Ghesani N, Pak J, Kannurpatti SS. MRI based composite parameter of multiple tissue types for improved patient-level hemispheric and regional level lateralization in pediatric epilepsy. Magn Reson Imaging 2022; 94:174-180. [PMID: 36241030 DOI: 10.1016/j.mri.2022.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 06/16/2023]
Abstract
Although voxel-based morphometry (VBM) of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) changes aid in epileptic seizure lateralization, type of T1 pulse sequence, preprocessing steps and tissue segmentation methods lead to variation in tissue classification. Here, we test the prediction accuracy of individual MRI based tissue types and a novel composite ratio parameter [(GM + WM)/CSF], sensitive to parenchymal changes and independent of tissue classification variations. Pediatric patients with partial seizures (both simple and complex), but normal and lesion-free MRI were considered (33 patients; unilateral EEG; 17 female / 16 male; age mean ± SD = 11.5 ± 5 years). MRI based seizure lateralization was performed for each patient and verified with EEG findings alone or in combination with seizure semiology. T1 weighted MRI from patients and normal control subjects was spatially transformed to the Talairach atlas and automatically segmented into GM, WM and CSF tissue types. 41 age matched normal controls (11 female / 30 male; age mean ± SD = 14.6 ± 3 years) served as the null distribution to test tissue type deviations across each epilepsy patient. When verified with the patient EEG prediction, WM, GM and CSF had a hemispheric match of 76%, 70% and 55% respectively, while the composite ratio [(GM + WM)/CSF)] showed the highest accuracy of 85%. When EEG findings and seizure semiology were combined, MRI predictions using the composite ratio improved further to 88%. To further localize the epileptic focus, regional level (frontal, temporal, parietal and occipital) MRI predictions were obtained. The composite ratio performed at 88-91% accuracy, revealing regional MRI changes, not predictable with EEG. The results show inconsistent changes in GM and WM in majority of the pediatric epilepsy patients and demonstrate the applicability of the composite ratio [(GM + WM)/CSF)] as a superior predictor, independent of tissue classification variations. Clinical EEG findings combined with seizure semiology, can overcome scalp EEG's limitations and lean towards the MRI lateralization in specific cases.
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Affiliation(s)
- Siddharth Gupta
- Department of Neurology, Rutgers Biomedical and Health Sciences-New Jersey Medical School, Newark, NJ, USA
| | - Reena Razdan
- Department of Radiology, Rutgers Biomedical and Health Sciences-New Jersey Medical School, Newark, NJ, USA
| | | | - Luke Tomycz
- Department of Neurosurgery, Rutgers Biomedical and Health Sciences-New Jersey Medical School, Newark, NJ, USA
| | - Nasrin Ghesani
- Department of Radiology, Rutgers Biomedical and Health Sciences-New Jersey Medical School, Newark, NJ, USA
| | - Jayoung Pak
- Department of Neurology, Rutgers Biomedical and Health Sciences-New Jersey Medical School, Newark, NJ, USA
| | - Sridhar S Kannurpatti
- Department of Radiology, Rutgers Biomedical and Health Sciences-New Jersey Medical School, Newark, NJ, USA.
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50
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Kananen J, Järvelä M, Korhonen V, Tuovinen T, Huotari N, Raitamaa L, Helakari H, Väyrynen T, Raatikainen V, Nedergaard M, Ansakorpi H, Jacobs J, LeVan P, Kiviniemi V. Increased interictal synchronicity of respiratory related brain pulsations in epilepsy. J Cereb Blood Flow Metab 2022; 42:1840-1853. [PMID: 35570730 PMCID: PMC9536129 DOI: 10.1177/0271678x221099703] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Respiratory brain pulsations have recently been shown to drive electrophysiological brain activity in patients with epilepsy. Furthermore, functional neuroimaging indicates that respiratory brain pulsations have increased variability and amplitude in patients with epilepsy compared to healthy individuals. To determine whether the respiratory drive is altered in epilepsy, we compared respiratory brain pulsation synchronicity between healthy controls and patients. Whole brain fast functional magnetic resonance imaging was performed on 40 medicated patients with focal epilepsy, 20 drug-naïve patients and 102 healthy controls. Cerebrospinal fluid associated respiratory pulsations were used to generate individual whole brain respiratory synchronization maps, which were compared between groups. Finally, we analyzed the seizure frequency effect and diagnostic accuracy of the respiratory synchronization defect in epilepsy. Respiratory brain pulsations related to the verified fourth ventricle pulsations were significantly more synchronous in patients in frontal, periventricular and mid-temporal regions, while the seizure frequency correlated positively with synchronicity. The respiratory brain synchronicity had a good diagnostic accuracy (ROCAUC = 0.75) in discriminating controls from medicated patients. The elevated respiratory brain synchronicity in focal epilepsy suggests altered physiological effect of cerebrospinal fluid pulsations possibly linked to regional brain water dynamics involved with interictal brain physiology.
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Affiliation(s)
- Janne Kananen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Matti Järvelä
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Lauri Raitamaa
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Heta Helakari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Tommi Väyrynen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Ville Raatikainen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, Department of Neurosurgery, University of Rochester Medical Center, Rochester, NY, USA.,Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hanna Ansakorpi
- Medical Research Center (MRC), Oulu, Finland.,Research Unit of Neuroscience, Neurology, University of Oulu, Oulu, Finland.,Department of Neurology, Oulu University Hospital, Oulu, Finland
| | - Julia Jacobs
- Department of Pediatric Neurology and Muscular Disease, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada
| | - Pierre LeVan
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Canada.,Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Department of Radiology, Medical Physics, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology (MIPT), Faculty of Medicine, University of Oulu, Oulu, Finland.,Medical Research Center (MRC), Oulu, Finland
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