1
|
Kerestes R, Perry A, Vivash L, O’Brien TJ, Alvim MK, Arienzo D, Aventurato ÍK, Ballerini A, Baltazar GF, Bargalló N, Bender B, Brioschi R, Bürkle E, Caligiuri ME, Cendes F, de Tisi J, Duncan JS, Engel JP, Foley S, Fortunato F, Gambardella A, Giacomini T, Guerrini R, Hall G, Hamandi K, Ives-Deliperi V, João RB, Keller SS, Kleiser B, Labate A, Lenge M, Marotta C, Martin P, Mascalchi M, Meletti S, Owens-Walton C, Parodi CB, Pascual-Diaz S, Powell D, Rao J, Rebsamen M, Reiter J, Riva A, Rüber T, Rummel C, Scheffler F, Severino M, Silva LS, Staba RJ, Stein DJ, Striano P, Taylor PN, Thomopoulos SI, Thompson PM, Tortora D, Vaudano AE, Weber B, Wiest R, Winston GP, Yasuda CL, Zheng H, McDonald CR, Sisodiya SM, Harding IH. Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study. Epilepsia 2024; 65:1072-1091. [PMID: 38411286 PMCID: PMC11120093 DOI: 10.1111/epi.17881] [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: 06/20/2023] [Revised: 12/26/2023] [Accepted: 01/03/2024] [Indexed: 02/28/2024]
Abstract
OBJECTIVE The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current corticocentric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural magnetic resonance imaging in 1602 adults with epilepsy and 1022 healthy controls across 22 sites from the global ENIGMA-Epilepsy working group. METHODS A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in (1) all epilepsies, (2) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS), (3) nonlesional temporal lobe epilepsy, (4) genetic generalized epilepsy, and (5) extratemporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness. RESULTS Across all epilepsies, reduced total cerebellar volume was observed (d = .42). Maximum volume loss was observed in the corpus medullare (dmax = .49) and posterior lobe gray matter regions, including bilateral lobules VIIB (dmax = .47), crus I/II (dmax = .39), VIIIA (dmax = .45), and VIIIB (dmax = .40). Earlier age at seizure onset (η ρ max 2 = .05) and longer epilepsy duration (η ρ max 2 = .06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE, with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls. SIGNIFICANCE We provide robust evidence of deep cerebellar and posterior lobe subregional gray matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in nonmotor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellar subregional damage into neurobiological models of epilepsy.
Collapse
Affiliation(s)
- Rebecca Kerestes
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Andrew Perry
- Monash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Terence J. O’Brien
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
| | - Marina K.M. Alvim
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Donatello Arienzo
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Ítalo K. Aventurato
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Alice Ballerini
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Gabriel F. Baltazar
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Núria Bargalló
- Magnetic Resonance Image Core Facility, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
- Department of Radiology of Center of Image Diagnosis (CDIC), Hospital Clinic de Barcelona, Barcelona, Spain
- CIBERSAM, Madrid, Spain
| | - Benjamin Bender
- Department of Radiology, Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Ricardo Brioschi
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Eva Bürkle
- Department of Radiology, Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Maria Eugenia Caligiuri
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University “Magna Græcia” of Catanzaro, Catanzaro, Italy
| | - Fernando Cendes
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - John S. Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Jerome P. Engel
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
| | - Francesco Fortunato
- Institute of Neurology, Department of Medical and Surgical Sciences, University “Magna Græcia” of Catanzaro, Catanzaro, Italy
| | - Antonio Gambardella
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University “Magna Græcia” of Catanzaro, Catanzaro, Italy
- Institute of Neurology, Department of Medical and Surgical Sciences, University “Magna Græcia” of Catanzaro, Catanzaro, Italy
| | - Thea Giacomini
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Renzo Guerrini
- Meyer Children’s Hospital IRCCS, Florence, Italy
- University of Florence, Florence, Italy
| | - Gerard Hall
- School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
- The Welsh Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, UK
| | | | - Rafael B. João
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Simon S. Keller
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
- The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Benedict Kleiser
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Angelo Labate
- Neurophysiopatology and Movement Disorders Clinic, University of Messina, Messina, Italy
- Regional Epilepsy Center, University of Messina, Messina, Italy
| | - Matteo Lenge
- Meyer Children’s Hospital IRCCS, Florence, Italy
| | | | - Pascal Martin
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Mario Mascalchi
- ‘Mario Serio’ Department of Clinical and Experimental Medical Sciences, University of Florence, Florence, Italy
- Division of Epidemiology and Clinical Governance, Institute for Study, Prevention and network in Oncology of the Tuscany Region, Florence, Italy
| | - Stefano Meletti
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria Modena, Modena, Italy
| | - Conor Owens-Walton
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Saül Pascual-Diaz
- Magnetic Resonance Image Core Facility, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - David Powell
- Monash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia
| | - Jun Rao
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Michael Rebsamen
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Johannes Reiter
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | | | - Theodor Rüber
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Christian Rummel
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Freda Scheffler
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | | | - Lucas S. Silva
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Richard J. Staba
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Dan J. Stein
- SMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Pasquale Striano
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
- IRCCS Istituto ‘Giannina Gaslini’, Genoa, Italy
| | - Peter N. Taylor
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Anna Elisabetta Vaudano
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria Modena, Modena, Italy
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University of Bonn, Bonn, Germany
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Gavin P. Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Epilepsy Society MRI Unit, Chalfont St Peter, UK
- Department of Medicine (Division of Neurology), Queen’s University Kingston, ON, Canada
| | - Clarissa L. Yasuda
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Hong Zheng
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Carrie R. McDonald
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA
| | - Sanjay M. Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Ian H. Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
| | | |
Collapse
|
2
|
Kerestes R, Perry A, Vivash L, O'Brien TJ, Alvim MKM, Arienzo D, Aventurato ÍK, Ballerini A, Baltazar GF, Bargalló N, Bender B, Brioschi R, Bürkle E, Caligiuri ME, Cendes F, de Tisi J, Duncan JS, Engel JP, Foley S, Fortunato F, Gambardella A, Giacomini T, Guerrini R, Hall G, Hamandi K, Ives-Deliperi V, João RB, Keller SS, Kleiser B, Labate A, Lenge M, Marotta C, Martin P, Mascalchi M, Meletti S, Owens-Walton C, Parodi CB, Pascual-Diaz S, Powell D, Rao J, Rebsamen M, Reiter J, Riva A, Rüber T, Rummel C, Scheffler F, Severino M, Silva LS, Staba RJ, Stein DJ, Striano P, Taylor PN, Thomopoulos SI, Thompson PM, Tortora D, Vaudano AE, Weber B, Wiest R, Winston GP, Yasuda CL, Zheng H, McDonald CR, Sisodiya SM, Harding IH. Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.21.562994. [PMID: 37961570 PMCID: PMC10634708 DOI: 10.1101/2023.10.21.562994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Objective The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current cortico-centric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural MRI in 1,602 adults with epilepsy and 1,022 healthy controls across twenty-two sites from the global ENIGMA-Epilepsy working group. Methods A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in i) all epilepsies; ii) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS); iii) non-lesional temporal lobe epilepsy (TLE-NL); iv) genetic generalised epilepsy; and (v) extra-temporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness. Results Across all epilepsies, reduced total cerebellar volume was observed (d=0.42). Maximum volume loss was observed in the corpus medullare (dmax=0.49) and posterior lobe grey matter regions, including bilateral lobules VIIB (dmax= 0.47), Crus I/II (dmax= 0.39), VIIIA (dmax=0.45) and VIIIB (dmax=0.40). Earlier age at seizure onset (ηρ2max=0.05) and longer epilepsy duration (ηρ2max=0.06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls. Significance We provide robust evidence of deep cerebellar and posterior lobe subregional grey matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in non-motor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellum subregions into neurobiological models of epilepsy.
Collapse
Affiliation(s)
- Rebecca Kerestes
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Andrew Perry
- Monash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Terence J O'Brien
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
| | - Marina K M Alvim
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Donatello Arienzo
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Ítalo K Aventurato
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Alice Ballerini
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Gabriel F Baltazar
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Núria Bargalló
- Magnetic Resonance Image Core Facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
- Department of Radiology of Center of Image Diagnosis (CDIC), Hospital Clinic de Barcelona, Barcelona, Spain
- CIBERSAM, Madrid, Spain
| | - Benjamin Bender
- Department of Radiology, Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Ricardo Brioschi
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Eva Bürkle
- Department of Radiology, Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Maria Eugenia Caligiuri
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Græcia" of Catanzaro, Catanzaro, Italy
| | - Fernando Cendes
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Jerome P Engel
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
| | - Francesco Fortunato
- Institute of Neurology, Department of Medical and Surgical Sciences, University "Magna Græcia" of Catanzaro, Catanzaro, Italy
| | - Antonio Gambardella
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Græcia" of Catanzaro, Catanzaro, Italy
- Institute of Neurology, Department of Medical and Surgical Sciences, University "Magna Græcia" of Catanzaro, Catanzaro, Italy
| | - Thea Giacomini
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Renzo Guerrini
- Functional and Epilepsy Neurosurgery Unit, Neurosurgery Department, Children's Hospital A. Meyer-University of Florence, Florence, Italy
| | - Gerard Hall
- School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
- The Welsh Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, UK
| | | | - Rafael B João
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Simon S Keller
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
- The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Benedict Kleiser
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Angelo Labate
- Neurophysiopatology and Movement Disorders Clinic, University of Messina, Messina, Italy
- Regional Epilepsy Center, University of Messina, Messina, Italy
| | - Matteo Lenge
- Functional and Epilepsy Neurosurgery Unit, Neurosurgery Department, Children's Hospital A. Meyer-University of Florence, Florence, Italy
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Children's Hospital A. Meyer-University of Florence, Florence, Italy
| | | | - Pascal Martin
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Mario Mascalchi
- 'Mario Serio' Department of Clinical and Experimental Medical Sciences, University of Florence, Florence, Italy
- Division of Epidemiology and Clinical Governance, Institute for Study, Prevention and network in Oncology of the Tuscany Region, Florence, Italy
| | - Stefano Meletti
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria Modena, Modena, Italy
| | - Conor Owens-Walton
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Saül Pascual-Diaz
- Magnetic Resonance Image Core Facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - David Powell
- Monash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia
| | - Jun Rao
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Michael Rebsamen
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Johannes Reiter
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | | | - Theodor Rüber
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Christian Rummel
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Freda Scheffler
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | | | - Lucas S Silva
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Richard J Staba
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Dan J Stein
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Monash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia
- Department of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Magnetic Resonance Image Core Facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
- Department of Radiology of Center of Image Diagnosis (CDIC), Hospital Clinic de Barcelona, Barcelona, Spain
- CIBERSAM, Madrid, Spain
- Department of Radiology, Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Græcia" of Catanzaro, Catanzaro, Italy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
- Institute of Neurology, Department of Medical and Surgical Sciences, University "Magna Græcia" of Catanzaro, Catanzaro, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
- Functional and Epilepsy Neurosurgery Unit, Neurosurgery Department, Children's Hospital A. Meyer-University of Florence, Florence, Italy
- School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- The Welsh Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, UK
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
- The Walton Centre NHS Foundation Trust, Liverpool, UK
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Neurophysiopatology and Movement Disorders Clinic, University of Messina, Messina, Italy
- Regional Epilepsy Center, University of Messina, Messina, Italy
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Children's Hospital A. Meyer-University of Florence, Florence, Italy
- Department of Neurology, Alfred Health, Melbourne, VIC, Australia
- 'Mario Serio' Department of Clinical and Experimental Medical Sciences, University of Florence, Florence, Italy
- Division of Epidemiology and Clinical Governance, Institute for Study, Prevention and network in Oncology of the Tuscany Region, Florence, Italy
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria Modena, Modena, Italy
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- IRCCS Istituto 'Giannina Gaslini', Genova, Italy
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- Institute of Experimental Epileptology and Cognition Research, University of Bonn, Bonn, Germany
- Epilepsy Society MRI Unit, Chalfont St Peter, UK
- Department of Medicine (Division of Neurology), Queen's University Kingston, ON, Canada
- Chalfont Centre for Epilepsy, Bucks, UK
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
| | - Pasquale Striano
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
- IRCCS Istituto 'Giannina Gaslini', Genova, Italy
| | - Peter N Taylor
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Anna Elisabetta Vaudano
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria Modena, Modena, Italy
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University of Bonn, Bonn, Germany
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Gavin P Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Epilepsy Society MRI Unit, Chalfont St Peter, UK
- Department of Medicine (Division of Neurology), Queen's University Kingston, ON, Canada
| | - Clarissa L Yasuda
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Hong Zheng
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Carrie R McDonald
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
| |
Collapse
|
3
|
Mao X, Zhang X, Song C, Ma K, Wang K, Wang X, Lian Y, Zhang Y, Han S, Cheng J, Zhang Y. Alterations in static and dynamic regional homogeneity in mesial temporal lobe epilepsy with and without initial precipitating injury. Front Neurosci 2023; 17:1226077. [PMID: 37600006 PMCID: PMC10434245 DOI: 10.3389/fnins.2023.1226077] [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: 05/20/2023] [Accepted: 07/19/2023] [Indexed: 08/22/2023] Open
Abstract
Objectives Initial precipitating injury (IPI) such as febrile convulsion and intracranial infection will increase the susceptibility to epilepsy. It is still unknown if the functional deficits differ between mesial temporal lobe epilepsy with IPI (mTLE-IPI) and without IPI (mTLE-NO). Methods We recruited 25 mTLE-IPI patients, 35 mTLE-NO patients and 33 healthy controls (HC). Static regional homogeneity (sReHo) and dynamic regional homogeneity (dReHo) were then adopted to estimate the alterations of local neuronal activity. One-way analysis of variance was used to analyze the differences between the three groups in sReHo and dReHo. Then the results were utilized as masks for further between-group comparisons. Besides, correlation analyses were carried out to detect the potential relationships between abnormal regional homogeneity indicators and clinical characteristics. Results When compared with HC, the bilateral thalamus and the visual cortex in mTLE-IPI patients showed an increase in both sReHo and variability of dReHo. Besides, mTLE-IPI patients exhibited decreased sReHo in the right cerebellum crus1/crus2, inferior parietal lobule and temporal neocortex. mTLE-NO patients showed decreased sReHo and variability of dReHo in the bilateral temporal neocortex compared with HC. Increased sReHo and variability of dReHo were found in the bilateral visual cortex when mTLE-IPI patients was compared with mTLE-NO patients, as well as increased variability of dReHo in the left thalamus and decreased sReHo in the right dorsolateral prefrontal cortex. Additionally, we discovered a negative correlation between the national hospital seizure severity scale testing score and sReHo in the right cerebellum crus1 in mTLE-IPI patients. Conclusion According to the aforementioned findings, both mTLE-IPI and mTLE-NO patients had significant anomalies in local neuronal activity, although the functional deficits were much severer in mTLE-IPI patients. The use of sReHo and dReHo may provide a novel insight into the impact of the presence of IPI on the development of mTLE.
Collapse
Affiliation(s)
- Xinyue Mao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Xiaonan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Chengru Song
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Keran Ma
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Kefan Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Xin Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yajun Lian
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| |
Collapse
|
4
|
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.
Collapse
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.
| |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
Jiang Y, Li W, Qin Y, Zhang L, Tong X, Xiao F, Jiang S, Li Y, Gong Q, Zhou D, An D, Yao D, Luo C. In vivo characterization of magnetic resonance imaging-based T1w/T2w ratios reveals myelin-related changes in temporal lobe epilepsy. Hum Brain Mapp 2023; 44:2323-2335. [PMID: 36692056 PMCID: PMC10028664 DOI: 10.1002/hbm.26212] [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: 03/16/2022] [Revised: 12/12/2022] [Accepted: 01/09/2023] [Indexed: 01/25/2023] Open
Abstract
Temporal lobe epilepsy (TLE) is the most common type of intractable epilepsy in adults. Although brain myelination alterations have been observed in TLE, it remains unclear how the myelination network changes in TLE. This study developed a novel method in characterization of myelination structural covariance network (mSCN) by T1-weighted and T2-weighted magnetic resonance imaging (MRI). The mSCNs were estimated in 42 left TLE (LTLE), 42 right TLE (RTLE) patients, and 41 healthy controls (HCs). The topology of mSCN was analyzed by graph theory. Voxel-wise comparisons of myelination laterality were also examined among the three groups. Compared to HC, both patient groups showed decreased myelination in frontotemporal regions, amygdala, and thalamus; however, the LTLE showed lower myelination in left medial temporal regions than RTLE. Moreover, the LTLE exhibited decreased global efficiency compared with HC and more increased connections than RTLE. The laterality in putamen was differently altered between the two patient groups: higher laterality at posterior putamen in LTLE and higher laterality at anterior putamen in RTLE. The putamen may play a transfer station role in damage spreading induced by epileptic seizures from the hippocampus. This study provided a novel workflow by combination of T1-weighted and T2-weighted MRI to investigate in vivo the myelin-related microstructural feature in epileptic patients first time. Disconnections of mSCN implicate that TLE is a system disorder with widespread disruptions at regional and network levels.
Collapse
Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Yingjie Qin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Le Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Xin Tong
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Fenglai Xiao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Yunfang Li
- Southern Medical District, Chinese People's Liberation Army General Hospital, Beijing, People's Republic of China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, People's Republic of China
- Department of Neurology, First Affiliated Hospital of Hainan Medical University, Haikou, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, People's Republic of China
| |
Collapse
|
7
|
Su TY, Tang Y, Choi JY, Hu S, Sakaie K, Murakami H, Jones S, Blümcke I, Najm I, Ma D, Wang ZI. Evaluating whole-brain tissue-property changes in MRI-negative pharmacoresistant focal epilepsies using MR fingerprinting. Epilepsia 2023; 64:430-442. [PMID: 36507762 PMCID: PMC10107443 DOI: 10.1111/epi.17488] [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: 06/30/2022] [Revised: 12/09/2022] [Accepted: 12/09/2022] [Indexed: 12/15/2022]
Abstract
OBJECTIVE We aim to quantify whole-brain tissue-property changes in patients with magnetic resonance imaging (MRI)-negative pharmacoresistant focal epilepsy by three-dimensional (3D) magnetic resonance fingerprinting (MRF). METHODS We included 30 patients with pharmacoresistant focal epilepsy and negative MRI by official radiology report, as well as 40 age- and gender-matched healthy controls (HCs). MRF scans were obtained with 1 mm3 isotropic resolution. Quantitative T1 and T2 relaxometry maps were reconstructed from MRF and registered to the Montreal Neurological Institute (MNI) space. A two-sample t test was performed in Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) to evaluate significant abnormalities in patients comparing to HCs, with correction by the threshold-free cluster enhancement (TFCE) method. Subgroups analyses were performed for extra-temporal epilepsy/temporal epilepsy (ETLE/TLE), and for those with/without subtle abnormalities detected by morphometric analysis program (MAP), to investigate each subgroup's pattern of MRF changes. Correlation analyses were performed between the mean MRF values in each significant cluster and seizure-related clinical variables. RESULTS Compared to HCs, patients exhibited significant group-level T1 increase ipsilateral to the epileptic origin, in the mesial temporal gray matter (GM) and white matter (WM), temporal pole GM, orbitofrontal GM, hippocampus, and amygdala, with scattered clusters in the neocortical temporal and insular GM. No significant T2 changes were detected. The ETLE subgroup showed a T1-increase pattern similar to the overall cohort, with additional involvement of the ipsilateral anterior cingulate GM. The subgroup of MAP+ patients also showed a T1-increase pattern similar to the overall cohort, with additional cluster in the ipsilateral lateral orbitofrontal GM. Higher T1 was associated with younger seizure-onset age, longer epilepsy duration, and higher seizure frequency. SIGNIFICANCE MRF revealed group-level T1 increase in limbic/paralimbic structures ipsilateral to the epileptic origin, in patients with pharmacoresistant focal epilepsy and no apparent lesions on MRI, suggesting that these regions may be commonly affected by seizures in the epileptic brain. The significant association between T1 increase and higher seizure burden may reflect progressive tissue damage.
Collapse
Affiliation(s)
- Ting-Yu Su
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
- Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yingying Tang
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Joon Yul Choi
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Siyuan Hu
- Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Ken Sakaie
- Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | | | - Stephen Jones
- Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Ingmar Blümcke
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
- Neuropathology, University of Erlangen, Erlangen, Germany
| | - Imad Najm
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Dan Ma
- Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | | |
Collapse
|
8
|
Buchin A, de Frates R, Nandi A, Mann R, Chong P, Ng L, Miller J, Hodge R, Kalmbach B, Bose S, Rutishauser U, McConoughey S, Lein E, Berg J, Sorensen S, Gwinn R, Koch C, Ting J, Anastassiou CA. Multi-modal characterization and simulation of human epileptic circuitry. Cell Rep 2022; 41:111873. [PMID: 36577383 PMCID: PMC9841067 DOI: 10.1016/j.celrep.2022.111873] [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: 12/22/2020] [Revised: 06/16/2022] [Accepted: 12/02/2022] [Indexed: 12/28/2022] Open
Abstract
Temporal lobe epilepsy is the fourth most common neurological disorder, with about 40% of patients not responding to pharmacological treatment. Increased cellular loss is linked to disease severity and pathological phenotypes such as heightened seizure propensity. While the hippocampus is the target of therapeutic interventions, the impact of the disease at the cellular level remains unclear. Here, we show that hippocampal granule cells change with disease progression as measured in living, resected hippocampal tissue excised from patients with epilepsy. We show that granule cells increase excitability and shorten response latency while also enlarging in cellular volume and spine density. Single-nucleus RNA sequencing combined with simulations ascribes the changes to three conductances: BK, Cav2.2, and Kir2.1. In a network model, we show that these changes related to disease progression bring the circuit into a more excitable state, while reversing them produces a less excitable, "early-disease-like" state.
Collapse
Affiliation(s)
- Anatoly Buchin
- Allen Institute for Brain Science, Seattle, WA, USA,Present address: Cajal Neuroscience, Inc., Seattle, WA, USA,Correspondence: (A.B.), (C.A.A.)
| | - Rebecca de Frates
- Allen Institute for Brain Science, Seattle, WA, USA,These authors contributed equally
| | - Anirban Nandi
- Allen Institute for Brain Science, Seattle, WA, USA,These authors contributed equally
| | - Rusty Mann
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Peter Chong
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Lindsay Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Brian Kalmbach
- Allen Institute for Brain Science, Seattle, WA, USA,University of Washington, Seattle, WA, USA
| | - Soumita Bose
- Allen Institute for Brain Science, Seattle, WA, USA,CiperHealth, San Francisco, CA, USA
| | - Ueli Rutishauser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA,Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA,Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Stephen McConoughey
- Allen Institute for Brain Science, Seattle, WA, USA,Present address: Institute for Advanced Clinical Trials for Children, 9200 Corporate Blvd, Suite 350, Rockville, MD 20850, USA
| | - Ed Lein
- Allen Institute for Brain Science, Seattle, WA, USA,University of Washington, Seattle, WA, USA
| | - Jim Berg
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Jonathan Ting
- Allen Institute for Brain Science, Seattle, WA, USA,University of Washington, Seattle, WA, USA
| | - Costas A. Anastassiou
- Allen Institute for Brain Science, Seattle, WA, USA,Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA,Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA,Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA,Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA,Lead contact,Correspondence: (A.B.), (C.A.A.)
| |
Collapse
|
9
|
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.
Collapse
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
| |
Collapse
|
10
|
Glutig K, Lange L, Krüger PC, Gräger S, de Vries H, Brandl U, Gaser C, Mentzel HJ. Differences in Cerebellar Volume as a Diagnostic and Prognostic Biomarker in Children and Adolescents With Epilepsy of Unknown Etiology. J Child Neurol 2022; 37:939-948. [PMID: 36113051 PMCID: PMC9703387 DOI: 10.1177/08830738221114241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
INTRODUCTION AND OBJECTIVE Epilepsy is one of the most common brain diseases during childhood and adolescence. Atrophy in different brain areas is possible during epilepsy. This study aimed to verify whether cerebellar volume differences could be detected by volume analysis using magnetic resonance imaging (MRI) in children with epilepsy. METHOD In this retrospective study, 41 children (3.1-18.8 years) with epilepsy of unknown etiology were included (duration of epilepsy 1.9 ± 3 years). A cranial MRI with a volumetric 3-dimensional, T1-weighted sequence was used for volume analysis. The MRIs of 26 patients with headache (5.3-17.1 years) were analyzed for comparison. A volume analysis of the cerebellum was performed using region-based morphometry. Total cerebellar volume, total white and gray matter volume, and 48 regional lobules (L), separated into white and gray matter, were calculated. Cerebellar volumes are presented in relative ratios as the volume fraction of cerebellar volume to total intracranial volume: CV/TIV. RESULTS The ratio of overall white matter volume was significantly lower in the case group (23.93 × 10-3, P = .039). A significantly lower ratio of regional white matter volume was detected in LV right (P = .031) and left (P = .014), in LVIIIB right (P = .011) and left (P = .019), and in LVIIIA left (P = .009). CONCLUSION Our results emphasize that volume analysis of the total cerebellar volume alone is insufficient to characterize cerebellar differences in children with epilepsy. Rather, in specific cerebellar region volume analysis using region-based morphometry, children with epilepsy showed significantly lower regional volumes of lobules, which are important for sensorimotor function (LV, LVIII) and higher cognitive function (crus I).
Collapse
Affiliation(s)
- Katja Glutig
- Department of Radiology, Section of Pediatric Radiology, University Hospital, Jena, Germany,Katja Glutig, Jena University Hospital, Department of Radiology, Section of Pediatric Radiology, Am Klinikum 1, 07747 Jena, Germany.
| | - Luisa Lange
- Department of Radiology, Section of Pediatric Radiology, University Hospital, Jena, Germany
| | - Paul-Christian Krüger
- Department of Radiology, Section of Pediatric Radiology, University Hospital, Jena, Germany
| | - Stephanie Gräger
- Department of Radiology, Section of Pediatric Radiology, University Hospital, Jena, Germany
| | - Heike de Vries
- Department of Neuropediatrics, University Children’s Hospital, Jena, Germany
| | - Ulrich Brandl
- Department of Neuropediatrics, University Children’s Hospital, Jena, Germany
| | - Christian Gaser
- Structural Brain Mapping Group, Departments of Psychiatry and Neurology, University Hospital, Jena, Germany
| | - Hans-Joachim Mentzel
- Department of Radiology, Section of Pediatric Radiology, University Hospital, Jena, Germany
| |
Collapse
|
11
|
Epilepsy in Pediatric Patients—Evaluation of Brain Structures’ Volume Using VolBrain Software. J Clin Med 2022; 11:jcm11164657. [PMID: 36012894 PMCID: PMC9409991 DOI: 10.3390/jcm11164657] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/19/2022] [Accepted: 08/05/2022] [Indexed: 11/17/2022] Open
Abstract
Epilepsy is one of the most frequent serious brain disorders. Approximately 30,000 of the 150,000 children and adolescents who experience unprovoked seizures are diagnosed with epilepsy each year. Magnetic resonance imaging is the method of choice in diagnosing and monitoring patients with this condition. However, one very effective tool using MR images is volBrain software, which automatically generates information about the volume of brain structures. A total of 57 consecutive patients (study group) suffering from epilepsy and 34 healthy patients (control group) who underwent MR examination qualified for the study. Images were then evaluated by volBrain. Results showed atrophy of the brain and particular structures—GM, cerebrum, cerebellum, brainstem, putamen, thalamus, hippocampus and nucleus accumbens volume. Moreover, the statistically significant difference in the volume between the study and the control group was found for brain, lateral ventricle and putamen. A volumetric analysis of the CNS in children with epilepsy confirms a decrease in the volume of brain tissue. A volumetric assessment of brain structures based on MR data has the potential to be a useful diagnostic tool in children with epilepsy and can be implemented in clinical work; however, further studies are necessary to enhance the effectiveness of this software.
Collapse
|
12
|
Luckett PH, Maccotta L, Lee JJ, Park KY, Dosenbach NU, Ances BM, Hogan RE, Shimony JS, Leuthardt EC. Deep learning resting state fMRI lateralization of temporal lobe epilepsy. Epilepsia 2022; 63:1542-1552. [PMID: 35320587 DOI: 10.1111/epi.17233] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 03/21/2022] [Accepted: 03/21/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Localization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for non-invasive techniques to localize seizures for surgical decision-making. We investigate the use of deep learning using resting state functional MRI (RS-fMRI) to identify the hemisphere of seizure onset in temporal lobe epilepsy (TLE) patients. METHODS 2132 healthy controls and 32 pre-operative TLE patients were studied. All participants underwent structural MRI and RS-fMRI. Healthy control data was used to generate training samples for a 3D convolutional neural network (3DCNN). RS-fMRI was synthetically altered in randomly lateralized regions in the healthy control participants. The model was then trained to classify the hemisphere containing synthetic noise. Finally, the model was tested on TLE patients to assess its performance for detecting biological seizure-onset zones, and gradient-weighted class activation mapping (Grad-CAM) identified the strongest predictive regions. RESULTS The 3DCNN classified healthy control hemispheres known to contain synthetic noise with 96% accuracy, and TLE hemispheres clinically identified to be seizure onset zones with 90.6% accuracy. Grad-CAM identified a range of temporal, frontal, parietal, and subcortical regions that were strong anatomical predictors of the seizure onset zone, while the resting state networks which colocalized with Grad-CAM results included default mode, medial temporal, and dorsal attention networks. Lastly, in an analysis of a subset of patients with post-surgical outcomes, the 3DCNN leveraged a more focal set of regions to achieve classification in patients with Engel class > 1 compared to Engel class 1. SIGNIFICANCE Non-invasive techniques capable of localizing the seizure-onset zone could improve pre-surgical planning in patients with intractable epilepsy. We have demonstrated the ability of deep learning to identify the correct hemisphere of the seizure onset zone in TLE patients using RS-fMRI with high accuracy. This approach represents a novel technique of seizure lateralization that could improve preoperative surgical planning.
Collapse
Affiliation(s)
- Patrick H Luckett
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis
| | - Luigi Maccotta
- Department of Neurology, Washington University School of Medicine, St. Louis
| | - John J Lee
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis
| | - Ki Yun Park
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis
| | - Nico Uf Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis
| | - Beau M Ances
- Department of Neurology, Washington University School of Medicine, St. Louis
| | - R Edward Hogan
- Department of Neurology, Washington University School of Medicine, St. Louis
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis
| | - Eric C Leuthardt
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis
| |
Collapse
|
13
|
Fallahi A, Pooyan M, Habibabadi JM, Hashemi-Fesharaki SS, Tabatabaei NH, Ay M, Nazem-Zadeh MR. A novel approach for extracting functional brain networks involved in mesial temporal lobe epilepsy based on self organizing maps. INFORMATICS IN MEDICINE UNLOCKED 2022. [DOI: 10.1016/j.imu.2022.100876] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
|
14
|
Peng SJ, Hsieh KLC, Lin YK, Tsai ML, Wong TT, Chang H. Febrile seizures reduce hippocampal subfield volumes but not cortical thickness in children with focal onset seizures. Epilepsy Res 2022; 179:106848. [PMID: 34992023 DOI: 10.1016/j.eplepsyres.2021.106848] [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: 08/26/2021] [Revised: 12/23/2021] [Accepted: 12/28/2021] [Indexed: 11/20/2022]
Abstract
OBJECTIVES Whether febrile seizures (FS) produce long-term injury to the hippocampus or other brain structures is a critical question concerning focal onset seizures in children. Our aims are to evaluate the effect of FS on subfields of the hippocampus, thalamic nuclei, amygdala, cortical thickness, and surface area quantitatively in children with FS who later developed focal seizures and to identify biomarkers based on MRI structures. METHODS Children who had focal onset seizures with or without previous FS and normal 3-T MRI findings were included retrospectively. The MRI was performed within 2 years after the onset of focal seizures. Age-matched controls were also recruited. Hippocampal subfields and thalamic nuclei, amygdala volumes, cortical thickness, and cortical surface area in individual cortical regions were segmented by FreeSurfer version 7.1.1. Volumetric and morphometric data among children who had focal seizures with or without previous FS, as well as controls, were compared and correlated with clinical parameters. RESULTS Children with a history of FS who had focal seizures exhibited smaller right cornu ammonis (CA) 1 and right molecular cell layer of the hippocampus, compared to those without FS. A larger left hippocampal fissure was also found in FS with focal seizures compared to age-matched controls. There were no statistically significant differences in each nucleus of the thalamus, amygdala, cortical thickness, and surface area of each cortical region among the three groups. A smaller whole hippocampal volume was found for the right hippocampus in children with FS and focal seizures compared to those without FS. A trend of negative correlation was found between the frequency of FS and the left and right CA1 subfield volume ratios of the hippocampus. CONCLUSIONS We concluded that multiple episodes of FS may be associated with a trivial difference in volume reduction in the CA1 and molecular layer of the right hippocampus and an enlarged hippocampal fissure of the left hippocampus, but not with individual cortical thicknesses, surface area, thalamic nuclei, or amygdala in children with focal onset seizures.The hippocampal subfield CA1 and molecular layer of the right hippocampus may be more vulnerable than the cortices in children with focal seizures who experienced multiple FS episodes. This study highlights the minimal differences in brain volumes among children with recent onset focal seizures with or without FS history and controls, suggesting that the brain injurious aspects of the FS and recent onset focal seizures may have been previously overstated. This suggests that physicians can be reassuring about brain injury associated with these seizure types when discussing outcomes with parents and patients.
Collapse
Affiliation(s)
- Syu-Jyun Peng
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Kevin Li-Chun Hsieh
- Department of Medical Imaging, Taipei Medical University Hospital, Taipei, Taiwan; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Yen-Kuang Lin
- Graduate Institute of Athletics and Coaching Science, National Taiwan Sport University, Taoyuan, Taiwan
| | - Min-Lan Tsai
- Division of Pediatric Neurology, Department of Pediatrics, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan; Department of Pediatrics, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
| | - Tai-Tong Wong
- Division of Pediatric Neurosurgery, Department of Neurosurgery, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan; Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Hsi Chang
- Division of Pediatric Neurology, Department of Pediatrics, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan; Department of Pediatrics, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| |
Collapse
|
15
|
Owen TW, de Tisi J, Vos SB, Winston GP, Duncan JS, Wang Y, Taylor PN. Multivariate white matter alterations are associated with epilepsy duration. Eur J Neurosci 2021; 53:2788-2803. [PMID: 33222308 PMCID: PMC8246988 DOI: 10.1111/ejn.15055] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 11/12/2020] [Accepted: 11/15/2020] [Indexed: 01/08/2023]
Abstract
Previous studies investigating associations between white matter alterations and duration of temporal lobe epilepsy (TLE) have shown differing results, and were typically limited to univariate analyses of tracts in isolation. In this study, we apply a multivariate measure (the Mahalanobis distance), which captures the distinct ways white matter may differ in individual patients, and relate this to epilepsy duration. Diffusion MRI, from a cohort of 94 subjects (28 healthy controls, 33 left-TLE and 33 right-TLE), was used to assess the association between tract fractional anisotropy (FA) and epilepsy duration. Using ten white matter tracts, we analysed associations using the traditional univariate analysis (z-scores) and a complementary multivariate approach (Mahalanobis distance), incorporating multiple white matter tracts into a single unified analysis. For patients with right-TLE, FA was not significantly associated with epilepsy duration for any tract studied in isolation. For patients with left-TLE, the FA of two limbic tracts (ipsilateral fornix, contralateral cingulum gyrus) were significantly negatively associated with epilepsy duration (Bonferonni corrected p < .05). Using a multivariate approach we found significant ipsilateral positive associations with duration in both left, and right-TLE cohorts (left-TLE: Spearman's ρ = 0.487, right-TLE: Spearman's ρ = 0.422). Extrapolating our multivariate results to duration equals zero (i.e., at onset) we found no significant difference between patients and controls. Associations using the multivariate approach were more robust than univariate methods. The multivariate Mahalanobis distance measure provides non-overlapping and more robust results than traditional univariate analyses. Future studies should consider adopting both frameworks into their analysis in order to ascertain a more complete understanding of epilepsy progression, regardless of laterality.
Collapse
Affiliation(s)
- Thomas W. Owen
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems GroupSchool of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Jane de Tisi
- NIHR University College London Hospitals Biomedical Research CentreUCL Institute of NeurologyQueen SquareLondonUK
| | - Sjoerd B. Vos
- Centre for Medical Image ComputingUniversity College LondonLondonUK
- Epilepsy Society MRI UnitChalfont St PeterUK
- Neuroradiological Academic UnitUCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
| | - Gavin P. Winston
- NIHR University College London Hospitals Biomedical Research CentreUCL Institute of NeurologyQueen SquareLondonUK
- Epilepsy Society MRI UnitChalfont St PeterUK
- Department of MedicineDivision of NeurologyQueen's UniversityKingstonCanada
| | - John S Duncan
- NIHR University College London Hospitals Biomedical Research CentreUCL Institute of NeurologyQueen SquareLondonUK
- Epilepsy Society MRI UnitChalfont St PeterUK
| | - Yujiang Wang
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems GroupSchool of ComputingNewcastle UniversityNewcastle upon TyneUK
- NIHR University College London Hospitals Biomedical Research CentreUCL Institute of NeurologyQueen SquareLondonUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Peter N. Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems GroupSchool of ComputingNewcastle UniversityNewcastle upon TyneUK
- NIHR University College London Hospitals Biomedical Research CentreUCL Institute of NeurologyQueen SquareLondonUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| |
Collapse
|
16
|
Scott RC. Brains, complex systems and therapeutic opportunities in epilepsy. Seizure 2021; 90:155-159. [PMID: 33582003 DOI: 10.1016/j.seizure.2021.02.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2021] [Revised: 01/27/2021] [Accepted: 02/01/2021] [Indexed: 12/16/2022] Open
Abstract
The treatment of epilepsy remains extremely challenging for the thirty percent of people that do not become seizure free. This is despite the introduction of multiple new drugs over that last several decades, highlighting the need for new approaches to identifying novel therapeutic strategies. Conceptualizing the brain as a complex adaptive system and applying the tools that are used in addressing such systems provides an opportunity for expanding the space in which to search for new therapies. Epilepsy has long been considered a network disease at the level of whole brain connectivity, but the application of the concepts to gene and protein expression networks as well as to the dynamic behaviors of microcircuits has been underexplored. These levels of the brain complex adaptive system will be reviewed and a case made for the epilepsy community to embrace these concepts in order to reap to enormous potential rewards.
Collapse
Affiliation(s)
- Rod C Scott
- University of Vermont, 95 Carrigan Drive, Burlington, VT, 05405, United States; University of Vermont Medical Center, United States; Great Ormond Street Hospital for Children NHS Trust, United Kingdom.
| |
Collapse
|
17
|
Cerebellar Degeneration in Epilepsy: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18020473. [PMID: 33435567 PMCID: PMC7827978 DOI: 10.3390/ijerph18020473] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 12/17/2020] [Accepted: 12/31/2020] [Indexed: 01/03/2023]
Abstract
Introduction: Cerebellar degeneration has been associated in patients with epilepsy, though the exact pathogenic mechanisms are not understood. The aim of this systematic review was to identify the prevalence of cerebellar degeneration in patients with epilepsy and identify any pathogenic mechanisms. Methodology: A systematic computer-based literature search was conducted using the PubMed database. Data extracted included prevalence, clinical, neuroradiological, and neuropathological characteristics of patients with epilepsy and cerebellar degeneration. Results: We identified three consistent predictors of cerebellar degeneration in the context of epilepsy in our review: temporal lobe epilepsy, poor seizure control, and phenytoin as the treatment modality. Whole brain and hippocampal atrophy were also identified in patients with epilepsy. Conclusions: Cerebellar degeneration is prevalent in patients with epilepsy. Further prospective studies are required to confirm if the predictors identified in this review are indeed linked to cerebellar degeneration and to establish the pathogenic mechanisms that result in cerebellar insult.
Collapse
|
18
|
Jber M, Habibabadi JM, Sharifpour R, Marzbani H, Hassanpour M, Seyfi M, Mobarakeh NM, Keihani A, Hashemi-Fesharaki SS, Ay M, Nazem-Zadeh MR. Temporal and extratemporal atrophic manifestation of temporal lobe epilepsy using voxel-based morphometry and corticometry: clinical application in lateralization of epileptogenic zone. Neurol Sci 2021; 42:3305-3325. [PMID: 33389247 DOI: 10.1007/s10072-020-05003-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Accepted: 12/14/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND Advances in MRI acquisition and data processing have become important for revealing brain structural changes. Previous studies have reported widespread structural brain abnormalities and cortical thinning in patients with temporal lobe epilepsy (TLE), as the most common form of focal epilepsy. METHODS In this research, healthy control cases (n = 20) and patients with left TLE (n = 19) and right TLE (n = 14) were recruited, all underwent 3.0 T MRI with magnetization-prepared rapid gradient echo sequence to acquire T1-weighted images. Morphometric alterations in gray matter were identified using voxel-based morphometry (VBM). Volumetric alterations in subcortical structures and cortical thinning were also determined. RESULTS Patients with left TLE demonstrated more prevailing and widespread changes in subcortical volumes and cortical thickness than right TLE, mainly in the left hemisphere, compared to the healthy group. Both VBM analysis and subcortical volumetry detected significant hippocampal atrophy in ipsilateral compared to contralateral side in TLE group. In addition to hippocampus, subcortical volumetry found the thalamus and pallidum bilaterally vulnerable to the TLE. Furthermore, the TLE patients underwent cortical thinning beyond the temporal lobe, affecting gray matter cortices in frontal, parietal, and occipital lobes in the majority of patients, more prevalently for left TLE cases. Exploiting volume changes in individual patients in the hippocampus alone led to 63.6% sensitivity and 100% specificity for lateralization of TLE. CONCLUSION Alteration of gray matter volumes in subcortical regions and neocortical temporal structures and also cortical gray matter thickness were evidenced as common effects of epileptogenicity, as manifested by the majority of cases in this study.
Collapse
Affiliation(s)
- Majdi Jber
- Medical School, International Campus, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Roya Sharifpour
- Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran
- Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences, Tehran, Iran
| | - Hengameh Marzbani
- Department of Biomedical Engineering, Amirkabir University of Technology (AUT), Tehran, Iran
| | - Masoud Hassanpour
- Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences, Tehran, Iran
| | - Milad Seyfi
- Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran
- Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences, Tehran, Iran
| | - Neda Mohammadi Mobarakeh
- Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmedreza Keihani
- Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Mohammadreza Ay
- Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran
- Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad-Reza Nazem-Zadeh
- Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran.
- Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences, Tehran, Iran.
| |
Collapse
|
19
|
Sanjari Moghaddam H, Rahmani F, Aarabi MH, Nazem-Zadeh MR, Davoodi-Bojd E, Soltanian-Zadeh H. White matter microstructural differences between right and left mesial temporal lobe epilepsy. Acta Neurol Belg 2020; 120:1323-1331. [PMID: 30635771 DOI: 10.1007/s13760-019-01074-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Accepted: 01/05/2019] [Indexed: 01/20/2023]
Abstract
PURPOSE Mesial temporal lobe epilepsy (mTLE) is a chronic focal epileptic disorder characterized by recalcitrant seizures often necessitating surgical intervention. Identifying the laterality of seizure focus is crucial for pre-surgical planning. We implemented diffusion MRI (DMRI) connectometry to identify differences in white matter connectivity in patients with left and right mTLE relative to healthy control subjects. METHOD We enrolled 12 patients with right mTLE, 12 patients with left mTLE, and 12 age/sex matched healthy controls (HCs). We used DMRI connectometry to identify local connectivity patterns of white matter tracts, based on quantitative anisotropy (QA). We compared QA of white matter to reconstruct tracts with significant difference in connectivity between patients and HCs and then between patients with left and right mTLE. RESULTS Right mTLE patients show higher anisotropy in left inferior longitudinal fasciculus (ILF) and forceps minor and lower QA in genu of corpus callosum (CC), bilateral corticospinal tracts (CSTs), and bilateral middle cerebellar peduncles (MCPs) compared to HCs. Left mTLE patients show higher anisotropy in genu of CC, bilateral CSTs, and right MCP and decreased anisotropy in forceps minor compared to HCs. Compared to patients with right mTLE, left mTLE patients showed increased and decreased connectivity in some major tracts. CONCLUSIONS Our study showed the pattern of microstructural disintegrity in mTLE patients relative to HCs. We demonstrated that left and right mTLE patients have discrepant alternations in their white matter microstructure. These results may indicate that left and right mTLE have different underlying pathologic mechanisms.
Collapse
Affiliation(s)
| | - Farzaneh Rahmani
- NeuroImaging Network (NIN), Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Student's Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
| | | | - Mohammad-Reza Nazem-Zadeh
- Research Center for Science and Technology in Medicine (RCSTIM), Tehran University of Medical Sciences, Tehran, Iran
| | - Esmaeil Davoodi-Bojd
- Image Analysis Laboratory, Departments of Radiology and Research Administration, Henry Ford Health System, One Ford Place, 2F, Detroit, MI, 48202, USA
| | - Hamid Soltanian-Zadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, North Kargar Ave., Tehran, Iran.
- Image Analysis Laboratory, Departments of Radiology and Research Administration, Henry Ford Health System, One Ford Place, 2F, Detroit, MI, 48202, USA.
| |
Collapse
|
20
|
Leek NJ, Neason M, Kreilkamp BAK, de Bezenac C, Ziso B, Elkommos S, Das K, Marson AG, Keller SS. Thalamohippocampal atrophy in focal epilepsy of unknown cause at the time of diagnosis. Eur J Neurol 2020; 28:367-376. [PMID: 33012040 DOI: 10.1111/ene.14565] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Accepted: 09/24/2020] [Indexed: 01/02/2023]
Abstract
BACKGROUND AND PURPOSE Patients with chronic focal epilepsy may have atrophy of brain structures important for the generation and maintenance of seizures. However, little research has been conducted in patients with newly diagnosed focal epilepsy (NDfE), despite it being a crucial point in time for understanding the underlying biology of the disorder. We aimed to determine whether patients with NDfE show evidence of volumetric abnormalities of subcortical structures. METHODS Eighty-two patients with NDfE and 40 healthy controls underwent magnetic resonance imaging scanning using a standard clinical protocol. Volume estimation of the left and right hippocampus, thalamus, caudate nucleus, putamen and cerebral hemisphere was performed for all participants and normalised to whole brain volume. Volumes lower than two standard deviations below the control mean were considered abnormal. Volumes were analysed with respect to patient clinical characteristics, including treatment outcome 12 months after diagnosis. RESULTS Volume of the left hippocampus (p(FDR-corr) = 0.04) and left (p(FDR-corr) = 0.002) and right (p(FDR-corr) = 0.04) thalamus was significantly smaller in patients relative to controls. Relative to the normal volume limits in controls, 11% patients had left hippocampal atrophy, 17% had left thalamic atrophy and 9% had right thalamic atrophy. We did not find evidence of a relationship between volumes and future seizure control or with other clinical characteristics of epilepsy. CONCLUSIONS Volumetric abnormalities of structures known to be important for the generation and maintenance of focal seizures are established at the time of epilepsy diagnosis and are not necessarily a result of the chronicity of the disorder.
Collapse
Affiliation(s)
- N J Leek
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - M Neason
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - B A K Kreilkamp
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - C de Bezenac
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - B Ziso
- The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - S Elkommos
- St. George's University Hospitals NHS Foundation Trust, London, UK
| | - K Das
- The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - A G Marson
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - S S Keller
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,The Walton Centre NHS Foundation Trust, Liverpool, UK
| |
Collapse
|
21
|
Zhi D, Wu W, Xiao B, Qi S, Jiang R, Yang X, Yang J, Xiao W, Liu C, Long H, Calhoun VD, Long L, Sui J. NR4A1 Methylation Associated Multimodal Neuroimaging Patterns Impaired in Temporal Lobe Epilepsy. Front Neurosci 2020; 14:727. [PMID: 32760244 PMCID: PMC7372187 DOI: 10.3389/fnins.2020.00727] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Accepted: 06/18/2020] [Indexed: 11/25/2022] Open
Abstract
DNA hypermethylation has been widely observed in temporal lobe epilepsy (TLE), in which NR4A1 knockdown has been reported to be able to alleviate seizure severity in mouse model, while the underlying methylation-imaging pathway modulated by aberrant methylation levels of NR4A1 remains to be clarified in patients with TLE. Here, using multi-site canonical correlation analysis with reference, methylation levels of NR4A1 in blood were used as priori to guide fusion of three MRI features: functional connectivity (FC), fractional anisotropy (FA), and gray matter volume (GMV) for 56 TLE patients and 65 healthy controls. Post-hoc correlations were further evaluated between the identified NR4A1-associated brain components and disease onset. Results suggested that higher NR4A1 methylation levels in TLE were related with impaired temporal-cerebellar and occipital-cerebellar FC strength, lower FA in cingulum (hippocampus), and reduced GMV in putamen, temporal pole, and cerebellum. Moreover, findings were also replicated well in both patient subsets with either right TLE or left TLE only. Particularly, right TLE patients showed poorer cognitive abilities and more severe brain impairment than left TLE patients, especially more reduced GMV in thalamus. In summary, this work revealed a potential imaging-methylation pathway modulated by higher NR4A1 methylation in TLE via data mining, which may impact the above-mentioned multimodal brain circuits and was also associated with earlier disease onset and more cognitive deficits.
Collapse
Affiliation(s)
- Dongmei Zhi
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Wenyue Wu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.,Department of Neurology, The Second Affiliated Hospital, Nanchang University, Nanchang, China
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Shile Qi
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University - Emory University, Atlanta, GA, United States
| | - Rongtao Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Xingdong Yang
- Department of Neurology, Beijing Haidian Hospital, Beijing, China
| | - Jian Yang
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, China
| | - Wenbiao Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Chaorong Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Hongyu Long
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University - Emory University, Atlanta, GA, United States
| | - Lili Long
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Jing Sui
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China.,Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University - Emory University, Atlanta, GA, United States.,CAS Centre for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
22
|
Diagnosis of Alzheimer's disease using universum support vector machine based recursive feature elimination (USVM-RFE). Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2020.101903] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
|
23
|
Schnellbächer GJ, Hoffstaedter F, Eickhoff SB, Caspers S, Nickl-Jockschat T, Fox PT, Laird AR, Schulz JB, Reetz K, Dogan I. Functional Characterization of Atrophy Patterns Related to Cognitive Impairment. Front Neurol 2020; 11:18. [PMID: 32038473 PMCID: PMC6993791 DOI: 10.3389/fneur.2020.00018] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Accepted: 01/08/2020] [Indexed: 12/12/2022] Open
Abstract
Introduction: Mild cognitive impairment (MCI) is a heterogenous syndrome considered as a risk factor for developing dementia. Previous work examining morphological brain changes in MCI has identified a temporo-parietal atrophy pattern that suggests a common neuroanatomical denominator of cognitive impairment. Using functional connectivity analyses of structurally affected regions in MCI, we aimed to investigate and characterize functional networks formed by these regions that appear to be particularly vulnerable to disease-related disruptions. Methods: Areas of convergent atrophy in MCI were derived from a quantitative meta-analysis and encompassed left and right medial temporal (i.e., hippocampus, amygdala), as well as parietal regions (precuneus), which were defined as seed regions for connectivity analyses. Both task-based meta-analytical connectivity modeling (MACM) based on the BrainMap database and task-free resting-state functional MRI in a large cohort of older adults from the 1000BRAINS study were applied. We additionally assessed behavioral characteristics associated with the seed regions using BrainMap meta-data and investigated correlations of resting-state connectivity with age. Results: The left temporal seed showed stronger associations with a fronto-temporal network, whereas the right temporal atrophy cluster was more linked to cortico-striatal regions. In accordance with this, behavioral analysis indicated an emphasis of the left temporal seed on language generation, and the right temporal seed was associated with the domains of emotion and attention. Task-independent co-activation was more pronounced in the parietal seed, which demonstrated stronger connectivity with a frontoparietal network and associations with introspection and social cognition. Correlation analysis revealed both decreasing and increasing functional connectivity with higher age that may add to pathological processes but also indicates compensatory mechanisms of functional reorganization with increasing age. Conclusion: Our findings provide an important pathophysiological link between morphological changes and the clinical relevance of major structural damage in MCI. Multimodal analysis of functional networks related to areas of MCI-typical atrophy may help to explain cognitive decline and behavioral alterations not tractable by a mere anatomical interpretation and therefore contribute to prognostic evaluations.
Collapse
Affiliation(s)
| | - Felix Hoffstaedter
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Simon B Eickhoff
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Svenja Caspers
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,Institute for Anatomy I, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.,JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, Germany
| | - Thomas Nickl-Jockschat
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, United States.,Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, United States
| | - Peter T Fox
- Research Imaging Center, University of Texas Health Science Center, San Antonio, TX, United States.,Research Service, South Texas Veterans Administration Medical Center, San Antonio, TX, United States
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, United States
| | - Jörg B Schulz
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, Germany
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, Germany
| | - Imis Dogan
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1, INM-7, INM-11), Jülich, Germany.,JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, Germany
| |
Collapse
|
24
|
A comparative evaluation of bilateral hippocampus and amygdala volumes with ADC values in pediatric primary idiopathic partial epilepsy patients. JOURNAL OF SURGERY AND MEDICINE 2019. [DOI: 10.28982/josam.630645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
|
25
|
Kreilkamp BAK, Lisanti L, Glenn GR, Wieshmann UC, Das K, Marson AG, Keller SS. Comparison of manual and automated fiber quantification tractography in patients with temporal lobe epilepsy. NEUROIMAGE-CLINICAL 2019; 24:102024. [PMID: 31670154 PMCID: PMC6831895 DOI: 10.1016/j.nicl.2019.102024] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 09/05/2019] [Accepted: 09/27/2019] [Indexed: 11/25/2022]
Abstract
Tractography approaches showed moderate to good agreement for tract morphology. Along- and whole-tract diffusivity was significantly correlated across approaches. Whole-tract AFQ but not manual tract diffusivity correlated with clinical variables. Absence of excellent agreement between approaches warrants caution.
Objective To investigate the agreement between manually and automatically generated tracts from diffusion tensor imaging (DTI) in patients with temporal lobe epilepsy (TLE). Whole and along-the-tract diffusivity metrics and correlations with patient clinical characteristics were analyzed with respect to tractography approach. Methods We recruited 40 healthy controls and 24 patients with TLE who underwent conventional T1-weighted imaging and 60-direction DTI. An automated (Automated Fiber Quantification, AFQ) and manual (TrackVis) deterministic tractography approach was used to identify the uncinate fasciculus (UF) and parahippocampal white matter bundle (PHWM). Tract diffusion scalar metrics were analyzed with respect to agreement across automated and manual approaches (Dice Coefficient and Spearman correlations), to side of onset of epilepsy and patient clinical characteristics, including duration of epilepsy, age of onset and presence of hippocampal sclerosis. Results Across approaches the analysis of tract morphology similarity revealed Dice coefficients at moderate to good agreement (0.54 - 0.6) and significant correlations between diffusion values (Spearman's Rho=0.4–0.9). However, within bilateral PHWM, AFQ yielded significantly lower FA (left: Z = 4.4, p<0.001; right: Z = 5.1, p<0.001) and higher MD values (left: Z=-4.7, p<0.001; right: Z=-3.7, p<0.001) compared to the manual approach. Whole tract DTI metrics determined using AFQ were significantly correlated with patient characteristics, including age of epilepsy onset in FA (R = 0.6, p = 0.02) and MD of the ipsilateral PHWM (R=-0.6, p = 0.02), while duration of epilepsy corrected for age correlated with MD in ipsilateral PHWM (R = 0.7, p<0.01). Correlations between clinical metrics and diffusion values extracted using the manual whole tract technique did not survive correction for multiple comparisons. Both manual and automated along-the-tract analyses demonstrated significant correlations with patient clinical characteristics such as age of onset and epilepsy duration. The strongest and most widespread localized ipsi- and contralateral diffusivity alterations were observed in patients with left TLE and patients with HS compared to controls, while patients with right TLE and patients without HS did not show these strong effects. Conclusions Manual and AFQ tractography approaches revealed significant correlations in the reconstruction of tract morphology and extracted whole and along-tract diffusivity values. However, as non-identical methods they differed in the respective yield of significant results across clinical correlations and group-wise statistics. Given the absence of excellent agreement between manual and AFQ techniques as demonstrated in the present study, caution should be considered when using AFQ particularly when used without reference to benchmark manual measures.
Collapse
Affiliation(s)
- Barbara A K Kreilkamp
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom; Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom.
| | - Lucy Lisanti
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom; Royal Society, London, United Kingdom
| | - G Russell Glenn
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States
| | - Udo C Wieshmann
- Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Kumar Das
- Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Anthony G Marson
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom; Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Simon S Keller
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom; Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| |
Collapse
|
26
|
Klugah-Brown B, Luo C, Peng R, He H, Li J, Dong L, Yao D. Altered structural and causal connectivity in frontal lobe epilepsy. BMC Neurol 2019; 19:70. [PMID: 31023252 PMCID: PMC6485093 DOI: 10.1186/s12883-019-1300-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 04/11/2019] [Indexed: 01/09/2023] Open
Abstract
Background Albeit the few resting-state fMRI neuroimaging studies in frontal lobe epilepsy (FLE) patients, these studies focused on functional connectivity. The aim of this current study was to examine the effective connectivity based on voxel-based morphometry in FLE patients. Methods Resting-state structural and functional magnetic resonance imaging (fMRI) data were acquired from 19 FLE patients and 19 age and gender-matched healthy controls using the 3.0 Tesla magnetic resonance imaging (3.0 T MRI). The investigations were done by acquiring the structural information through voxel-based morphometry, then based on the seed obtained, Granger causality analysis was used to evaluate the causal flow of the designated seed to and from other significant voxels. Results Our results showed altered structural and effective connectivity. Compared with healthy controls, FLE patients showed reduced grey matter volume in bilateral putamen and right caudate as well as altered causality with increased, and decreased causal outflow from the right caudate (seed region) to inferior frontal gyrus-triangular, from bilateral putamen (seed regions) to right middle frontal gyrus and frontal gyrus medial-orbital representing the frontal executive areas, respectively. Also, significantly increased and decreased inflow from left calcarine to right caudate and from cerebellum_6 and vermis_6 to bilateral putamen, respectively. Moreover, we found that the causal alterations to and from the seed regions (from vermis_6 to right putamen and from left putamen to right middle frontal gyrus) negatively correlated with clinical scores (duration of epilepsy). Conclusions The findings point to the impairment within the executive and motor-controlled system including the cerebellum, frontal, caudate and putamen regions in FLE patients. These results would therefore enhance our understanding of structural and effective mechanisms in FLE.
Collapse
Affiliation(s)
- Benjamin Klugah-Brown
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, People's Republic of China.
| | - Rui Peng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, People's Republic of China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, People's Republic of China
| | - Jianfu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, People's Republic of China
| | - Li Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, People's Republic of China
| |
Collapse
|
27
|
Allen LA, Harper RM, Lhatoo S, Lemieux L, Diehl B. Neuroimaging of Sudden Unexpected Death in Epilepsy (SUDEP): Insights From Structural and Resting-State Functional MRI Studies. Front Neurol 2019; 10:185. [PMID: 30891003 PMCID: PMC6413533 DOI: 10.3389/fneur.2019.00185] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 02/13/2019] [Indexed: 01/31/2023] Open
Abstract
The elusive nature of sudden unexpected death in epilepsy (SUDEP) has led to investigations of mechanisms and identification of biomarkers of this fatal scenario that constitutes the leading cause of premature death in epilepsy. In this short review, we compile evidence from structural and functional neuroimaging that demonstrates alterations to brain structures and networks involved in central autonomic and respiratory control in SUDEP and those at elevated risk. These findings suggest that compromised central control of vital regulatory processes may contribute to SUDEP. Both structural changes and dysfunctional interactions indicate potential mechanisms underlying the fatal event; contributions to individual risk prediction will require further study. The nature and sites of functional disruptions suggest potential non-invasive interventions to overcome failing processes.
Collapse
Affiliation(s)
- Luke A. Allen
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- Epilepsy Society MRI Unit, Chalfont St Peter, London, United Kingdom
- The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
| | - Ronald M. Harper
- The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
- Department of Neurobiology, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, United States
- Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, United States
| | - Samden Lhatoo
- The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
- Department of Neurology, University of Texas Health Sciences Center at Houston, Houston, TX, United States
| | - Louis Lemieux
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- Epilepsy Society MRI Unit, Chalfont St Peter, London, United Kingdom
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- Epilepsy Society MRI Unit, Chalfont St Peter, London, United Kingdom
- The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
| |
Collapse
|
28
|
Chen X, Qian T, Kober T, Zhang G, Ren Z, Yu T, Piao Y, Chen N, Li K. Gray-matter-specific MR imaging improves the detection of epileptogenic zones in focal cortical dysplasia: A new sequence called fluid and white matter suppression (FLAWS). NEUROIMAGE-CLINICAL 2018; 20:388-397. [PMID: 30128277 PMCID: PMC6095948 DOI: 10.1016/j.nicl.2018.08.010] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2018] [Revised: 06/09/2018] [Accepted: 08/07/2018] [Indexed: 11/25/2022]
Abstract
Objectives To evaluate the diagnostic value and characteristic features of FCD epileptogenic zones using a novel sequence called fluid and white matter suppression (FLAWS). Materials and methods Thirty-nine patients with pathologically confirmed FCD and good surgery outcomes (class I or II, according to the Engel Epilepsy Surgery Outcome Scale) were retrospectively included in the study. All the patients underwent a preoperative whole-brain MRI examination that included conventional sequences (T2WI, T1WI, two-dimensional (2D) axial, coronal fluid-attenuated inversion recovery [FLAIR]) and FLAWS. An additional 3D-FLAIR MRI sequence was performed in 17 patients. To evaluate the sensitivity and specificity of FLAWS and investigate the cause of false-positives, 36 healthy volunteers were recruited as normal controls. Two radiologists evaluated all the image data. The detection rates of the FCD epileptogenic zone on different sequences were compared based on five criteria: abnormal cortical morphology (thickening, thinning, or abnormally deep sulcus); abnormal cortical signal intensity; blurred gray-white matter junction; abnormal signal intensity of the subcortical white matter, and the transmantle sign. The sensitivity and specificity of FLAWS for detecting the FCD lesions were calculated with the reviewers blinded to all the clinical information, i.e. to the patient identity and the location of the resected regions. To explore how many features were sufficient for the diagnosis of the epileptogenic zones, the frequency of each criterion in the resected regions and their combinations were assessed on FLAWS, according to the results of the assessment when the reviewers were aware of the location of the resected regions. Based on the findings of the 17 patients with an additional 3D-FLAIR scan when the reviewers were aware of the location of the resected regions, quantitative analysis of the regions of interest was used to compare the tissue contrast among 2D-axial FLAIR, 3D-FLAIR, and the FLAWS sequence. Visualization score analysis was used to evaluate the visualization of the five features on conventional, 3D-FLAIR, and FLAWS images. Finally, to explore the reason for false-positive results, a further evaluation of the whole brain FLAWS images was conducted for all the subjects. Results The sensitivity and specificity for detecting the FCD lesions on the FLAWS sequence were 71.9% and 71.1%, respectively. When the reviewers were blinded to the location of the resected regions, the detection rate of the FLAWS sequence was significantly higher than that of the conventional sequences (P = 0.00). In the 17 patients who underwent an additional 3D FLAIR scan, no statistically significant difference was found between the FLAWS and the 3D-FLAIR (P = 0.25). All the patients had at least two imaging features, one of which was “the blurred junction of the gray-white matter.” The transmantle sign, which is widely believed to be a specific feature of FCD type II, could also be observed in type I on the FLAWS sequence. The relative tissue contrast of FLAWS was higher than that of the 2D-FLAIR with respect to lesion/white matter (WM), deep gray matter (GM)/WM, and cortex/WM (P = 0.00 for all three measures) and higher than that of the 3D-FLAIR with respect to the lesion/WM (P = 0.01). The visualization score analysis showed that the visualization of FLAWS was more enhanced than that of the conventional and 3D-FLAIR images with respect to the blurred junction (P = 0.00 for both comparisons) and the abnormal signal intensity of the subcortical white matter (P = 0.01 for both comparisons). The thin-threadlike signal and individual FCD features outside the epileptogenic regions were considered the primary cause of the false-positive results of FLAWS. Conclusions FLAWS can help in the detection of FCD epileptogenic zones. It is recommended that epileptogenic zone on FLAWS be diagnosed based on a combination of two features, one of which should be the “blurred junction of the gray-white matter” in types I and II. In type III, the combination of “the blurred junction of the gray-white matter” with “abnormal signal intensity of subcortical white matter” is recommended. FLAWS can help in the detection of FCD epileptogenic zones. Diagnosis of FCD lesions should be based on a combination of two features. The transmantle sign is not specific for FCD type II on FLAWS.
Collapse
Affiliation(s)
- Xin Chen
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, PR China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China
| | - Tianyi Qian
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China; MR Collaborations NE Asia, Siemens Healthcare, Beijing, PR China
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare HC CEMEA SUI DI PI, Lausanne, Switzerland; Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland; LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Guojun Zhang
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, PR China
| | - Zhiwei Ren
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, PR China
| | - Tao Yu
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, PR China
| | - Yueshan Piao
- Department of Pathology, Xuanwu Hospital, Capital Medical University, Beijing, PR China
| | - Nan Chen
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, PR China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China.
| | - Kuncheng Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, PR China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China
| |
Collapse
|
29
|
Raj A, Powell F. Models of Network Spread and Network Degeneration in Brain Disorders. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 3:788-797. [PMID: 30170711 DOI: 10.1016/j.bpsc.2018.07.012] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 07/11/2018] [Accepted: 07/11/2018] [Indexed: 01/01/2023]
Abstract
Network analysis can provide insight into key organizational principles of brain structure and help identify structural changes associated with brain disease. Though static differences between diseased and healthy networks are well characterized, the study of network dynamics, or how brain networks change over time, is increasingly central to understanding ongoing brain changes throughout disease. Accordingly, we present a short review of network models of spread, network dynamics, and network degeneration. Borrowing from recent suggestions, we divide this review into two processes by which brain networks can change: dynamics on networks, which are functional and pathological consequences taking place atop a static structural brain network; and dynamics of networks, which constitutes a changing structural brain network. We focus on diffusion magnetic resonance imaging-based structural or anatomic connectivity graphs. We address psychiatric disorders like schizophrenia; developmental disorders like epilepsy; stroke; and Alzheimer's disease and other neurodegenerative diseases.
Collapse
Affiliation(s)
- Ashish Raj
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California.
| | - Fon Powell
- Department of Radiology, Weill Cornell Medicine, New York, New York
| |
Collapse
|
30
|
Quantitative volume-based morphometry in focal cortical dysplasia: A pilot study for lesion localization at the individual level. Eur J Radiol 2018; 105:240-245. [DOI: 10.1016/j.ejrad.2018.06.019] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 06/16/2018] [Accepted: 06/21/2018] [Indexed: 12/27/2022]
|
31
|
Brain morphological and microstructural features in cryptogenic late-onset temporal lobe epilepsy: a structural and diffusion MRI study. Neuroradiology 2018; 60:635-641. [DOI: 10.1007/s00234-018-2019-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 03/27/2018] [Indexed: 10/17/2022]
|
32
|
Frank L, Lüpke M, Kostic D, Löscher W, Tipold A. Grey matter volume in healthy and epileptic beagles using voxel-based morphometry - a pilot study. BMC Vet Res 2018; 14:50. [PMID: 29463250 PMCID: PMC5819682 DOI: 10.1186/s12917-018-1373-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2017] [Accepted: 02/14/2018] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND One of the most common chronic neurological disorders in dogs is idiopathic epilepsy (IE) diagnosed as epilepsy without structural changes in the brain. In the current study the hypothesis should be proven that subtle grey matter changes occur in epileptic dogs. Therefore, magnetic resonance (MR) images of one dog breed (Beagles) were used to obtain an approximately uniform brain shape. Local differences in grey matter volume (GMV) were compared between 5 healthy Beagles and 10 Beagles with spontaneously recurrent seizures (5 dogs with IE and 5 dogs with structural epilepsy (SE)), using voxel-based morphometry (VBM). T1W images of all dogs were prepared using Amira 6.3.0 for brain extraction, FSL 4.1.8 for registration and SPM12 for realignment. After creation of tissue probability maps of cerebrospinal fluid, grey and white matter from control images to segment all extracted brains, GM templates for each group were constructed to normalize brain images for parametric statistical analysis, which was achieved using SPM12. RESULTS Epileptic Beagles (IE and SE Beagles) displayed statistically significant reduced GMV in olfactory bulb, cingulate gyrus, hippocampus and cortex, especially in temporal and occipital lobes. Beagles with IE showed statistically significant decreased GMV in olfactory bulb, cortex of parietal and temporal lobe, hippocampus and cingulate gyrus, Beagles with SE mild statistically significant GMV reduction in temporal lobe (p < 0.05; family- wise error correction). CONCLUSION These results suggest that, as reported in epileptic humans, focal reduction in GMV also occurs in epileptic dogs. Furthermore, the current study shows that VBM analysis represents an excellent method to detect GMV differences of the brain between a healthy dog group and dogs with epileptic syndrome, when MR images of one breed are used.
Collapse
Affiliation(s)
- Lisa Frank
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine, Hannover, Germany.
| | - Matthias Lüpke
- Department of General Radiology and Medical Physics, University of Veterinary Medicine, Hannover, Germany
| | - Draginja Kostic
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine, Hannover, Germany
| | - Wolfgang Löscher
- Department of Pharmacology, Toxicology and Pharmacy, University of Veterinary Medicine, Hannover, Germany
| | - Andrea Tipold
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine, Hannover, Germany
| |
Collapse
|
33
|
Marcián V, Mareček R, Koriťáková E, Pail M, Bareš M, Brázdil M. Morphological changes of cerebellar substructures in temporal lobe epilepsy: A complex phenomenon, not mere atrophy. Seizure 2018; 54:51-57. [DOI: 10.1016/j.seizure.2017.12.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2017] [Revised: 12/11/2017] [Accepted: 12/13/2017] [Indexed: 01/10/2023] Open
|
34
|
Allen LA, Harper RM, Kumar R, Guye M, Ogren JA, Lhatoo SD, Lemieux L, Scott CA, Vos SB, Rani S, Diehl B. Dysfunctional Brain Networking among Autonomic Regulatory Structures in Temporal Lobe Epilepsy Patients at High Risk of Sudden Unexpected Death in Epilepsy. Front Neurol 2017; 8:544. [PMID: 29085330 PMCID: PMC5650686 DOI: 10.3389/fneur.2017.00544] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Accepted: 09/27/2017] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Sudden unexpected death in epilepsy (SUDEP) is common among young people with epilepsy. Individuals who are at high risk of SUDEP exhibit regional brain structural and functional connectivity (FC) alterations compared with low-risk patients. However, less is known about network-based FC differences among critical cortical and subcortical autonomic regulatory brain structures in temporal lobe epilepsy (TLE) patients at high risk of SUDEP. METHODS 32 TLE patients were risk-stratified according to the following clinical criteria: age of epilepsy onset, duration of epilepsy, frequency of generalized tonic-clonic seizures, and presence of nocturnal seizures, resulting in 14 high-risk and 18 low-risk cases. Resting-state functional magnetic resonance imaging (rs-fMRI) signal time courses were extracted from 11 bilateral cortical and subcortical brain regions involved in autonomic and other regulatory processes. After computing all pairwise correlations, FC matrices were analyzed using the network-based statistic. FC strength among the 11 brain regions was compared between the high- and low-risk patients. Increases and decreases in FC were sought, using high-risk > low-risk and low-risk > high-risk contrasts (with covariates age, gender, lateralization of epilepsy, and presence of hippocampal sclerosis). RESULTS High-risk TLE patients showed a subnetwork with significantly reduced FC (t = 2.5, p = 0.029) involving the thalamus, brain stem, anterior cingulate, putamen and amygdala, and a second subnetwork with significantly elevated FC (t = 2.1, p = 0.031), which extended to medial/orbital frontal cortex, insula, hippocampus, amygdala, subcallosal cortex, brain stem, thalamus, caudate, and putamen. CONCLUSION TLE patients at high risk of SUDEP showed widespread FC differences between key autonomic regulatory brain regions compared to those at low risk. The altered FC revealed here may help to shed light on the functional correlates of autonomic disturbances in epilepsy and mechanisms involved in SUDEP. Furthermore, these findings represent possible objective biomarkers which could help to identify high-risk patients and enhance SUDEP risk stratification via the use of non-invasive neuroimaging, which would require validation in larger cohorts, with extension to patients with other epilepsies and subjects who succumb to SUDEP.
Collapse
Affiliation(s)
- Luke A Allen
- Institute of Neurology, University College London, London, United Kingdom.,Epilepsy Society, Chalfont St. Peter, United Kingdom.,The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
| | - Ronald M Harper
- The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States.,Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.,UCLA Brain Research Institute, Los Angeles, CA, United States
| | - Rajesh Kumar
- The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States.,UCLA Brain Research Institute, Los Angeles, CA, United States.,Department of Anaesthesiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.,Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.,Department of Bioengineering, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Maxime Guye
- Aix Marseille University, CNRS, CRMBM UMR 7339, Marseille, France
| | - Jennifer A Ogren
- The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States.,Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Samden D Lhatoo
- The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States.,Epilepsy Centre, Neurological Institute, University Hospitals Case Medical Centre, Cleveland, OH, United States
| | - Louis Lemieux
- Institute of Neurology, University College London, London, United Kingdom.,Epilepsy Society, Chalfont St. Peter, United Kingdom
| | - Catherine A Scott
- Institute of Neurology, University College London, London, United Kingdom.,The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
| | - Sjoerd B Vos
- Epilepsy Society, Chalfont St. Peter, United Kingdom.,The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States.,Translational Imaging Group, University College London, London, United Kingdom
| | - Sandhya Rani
- The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States.,Epilepsy Centre, Neurological Institute, University Hospitals Case Medical Centre, Cleveland, OH, United States
| | - Beate Diehl
- Institute of Neurology, University College London, London, United Kingdom.,Epilepsy Society, Chalfont St. Peter, United Kingdom.,The Center for SUDEP Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States
| |
Collapse
|
35
|
Caciagli L, Bernasconi A, Wiebe S, Koepp MJ, Bernasconi N, Bernhardt BC. A meta-analysis on progressive atrophy in intractable temporal lobe epilepsy: Time is brain? Neurology 2017; 89:506-516. [PMID: 28687722 DOI: 10.1212/wnl.0000000000004176] [Citation(s) in RCA: 99] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Accepted: 04/21/2017] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE It remains unclear whether drug-resistant temporal lobe epilepsy (TLE) is associated with cumulative brain damage, with no expert consensus and no quantitative syntheses of the available evidence. METHODS We conducted a systematic review and meta-analysis of MRI studies on progressive atrophy, searching PubMed and Ovid MEDLINE databases for cross-sectional and longitudinal quantitative MRI studies on drug-resistant TLE. RESULTS We screened 2,976 records and assessed eligibility of 248 full-text articles. Forty-two articles met the inclusion criteria for quantitative evaluation. We observed a predominance of cross-sectional studies, use of different clinical indices of progression, and high heterogeneity in age-control procedures. Meta-analysis of 18/1 cross-sectional/longitudinal studies on hippocampal atrophy (n = 979 patients) yielded a pooled effect size of r = -0.42 for ipsilateral atrophy related to epilepsy duration (95% confidence interval [CI] -0.51 to -0.32; p < 0.0001; I2 = 65.22%) and r = -0.35 related to seizure frequency (95% CI -0.47 to -0.22; p < 0.0001; I2 = 61.97%). Sensitivity analyses did not change the results. Narrative synthesis of 25/3 cross-sectional/longitudinal studies on whole brain atrophy (n = 1,504 patients) indicated that >80% of articles reported duration-related progression in extratemporal cortical and subcortical regions. Detailed analysis of study design features yielded low to moderate levels of evidence for progressive atrophy across studies, mainly due to dominance of cross-sectional over longitudinal investigations, use of diverse measures of seizure estimates, and absence of consistent age control procedures. CONCLUSIONS While the neuroimaging literature is overall suggestive of progressive atrophy in drug-resistant TLE, published studies have employed rather weak designs to directly demonstrate it. Longitudinal multicohort studies are needed to unequivocally differentiate aging from disease progression.
Collapse
Affiliation(s)
- Lorenzo Caciagli
- From the Neuroimaging of Epilepsy Laboratory (L.C., A.B., N.B., B.C.B.) and Multimodal Imaging and Connectome Analysis Laboratory (B.C.B.), Montreal Neurological Institute and Hospital, McGill University; Department of Clinical Neurosciences (S.W.), University of Calgary, Canada; and Department of Clinical and Experimental Epilepsy (L.C., M.J.K.), UCL Institute of Neurology, London, UK
| | - Andrea Bernasconi
- From the Neuroimaging of Epilepsy Laboratory (L.C., A.B., N.B., B.C.B.) and Multimodal Imaging and Connectome Analysis Laboratory (B.C.B.), Montreal Neurological Institute and Hospital, McGill University; Department of Clinical Neurosciences (S.W.), University of Calgary, Canada; and Department of Clinical and Experimental Epilepsy (L.C., M.J.K.), UCL Institute of Neurology, London, UK
| | - Samuel Wiebe
- From the Neuroimaging of Epilepsy Laboratory (L.C., A.B., N.B., B.C.B.) and Multimodal Imaging and Connectome Analysis Laboratory (B.C.B.), Montreal Neurological Institute and Hospital, McGill University; Department of Clinical Neurosciences (S.W.), University of Calgary, Canada; and Department of Clinical and Experimental Epilepsy (L.C., M.J.K.), UCL Institute of Neurology, London, UK
| | - Matthias J Koepp
- From the Neuroimaging of Epilepsy Laboratory (L.C., A.B., N.B., B.C.B.) and Multimodal Imaging and Connectome Analysis Laboratory (B.C.B.), Montreal Neurological Institute and Hospital, McGill University; Department of Clinical Neurosciences (S.W.), University of Calgary, Canada; and Department of Clinical and Experimental Epilepsy (L.C., M.J.K.), UCL Institute of Neurology, London, UK
| | - Neda Bernasconi
- From the Neuroimaging of Epilepsy Laboratory (L.C., A.B., N.B., B.C.B.) and Multimodal Imaging and Connectome Analysis Laboratory (B.C.B.), Montreal Neurological Institute and Hospital, McGill University; Department of Clinical Neurosciences (S.W.), University of Calgary, Canada; and Department of Clinical and Experimental Epilepsy (L.C., M.J.K.), UCL Institute of Neurology, London, UK
| | - Boris C Bernhardt
- From the Neuroimaging of Epilepsy Laboratory (L.C., A.B., N.B., B.C.B.) and Multimodal Imaging and Connectome Analysis Laboratory (B.C.B.), Montreal Neurological Institute and Hospital, McGill University; Department of Clinical Neurosciences (S.W.), University of Calgary, Canada; and Department of Clinical and Experimental Epilepsy (L.C., M.J.K.), UCL Institute of Neurology, London, UK.
| |
Collapse
|
36
|
Garcia MTFC, Gaça LB, Sandim GB, Assunção Leme IB, Carrete H, Centeno RS, Sato JR, Yacubian EMT. Morphometric MRI features are associated with surgical outcome in mesial temporal lobe epilepsy with hippocampal sclerosis. Epilepsy Res 2017; 132:78-83. [DOI: 10.1016/j.eplepsyres.2017.02.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Revised: 02/22/2017] [Accepted: 02/28/2017] [Indexed: 11/29/2022]
|
37
|
Kreilkamp BA, Weber B, Richardson MP, Keller SS. Automated tractography in patients with temporal lobe epilepsy using TRActs Constrained by UnderLying Anatomy (TRACULA). Neuroimage Clin 2017; 14:67-76. [PMID: 28138428 PMCID: PMC5257189 DOI: 10.1016/j.nicl.2017.01.003] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2016] [Revised: 12/06/2016] [Accepted: 01/04/2017] [Indexed: 12/19/2022]
Abstract
PURPOSE A detailed understanding of white matter tract alterations in patients with temporal lobe epilepsy (TLE) is important as it may provide useful information for likely side of seizure onset, cognitive impairment and postoperative prognosis. However, most diffusion-tensor imaging (DTI) studies have relied on manual reconstruction of tract bundles, despite the recent development of automated techniques. In the present study, we used an automated white matter tractography analysis approach to quantify temporal lobe white matter tract alterations in TLE and determine the relationships between tract alterations, the extent of hippocampal atrophy and the chronicity and severity of the disorder. METHODS We acquired preoperative T1-weighted and DTI data in 64 patients with well-characterized TLE, with imaging and histopathological evidence of hippocampal sclerosis. Identical acquisitions were collected for 44 age- and sex-matched healthy controls. We employed automatic probabilistic tractography DTI analysis using TRActs Constrained by UnderLying Anatomy (TRACULA) available in context of Freesurfer software for the reconstruction of major temporal lobe tract bundles. We determined the factors influencing probabilistic tract reconstruction and investigated alterations of DTI scalar metrics along white matter tracts with respect to hippocampal volume, which was automatically estimated using Freesurfer's morphometric pipelines. We also explored the relationships between white matter tract alterations and duration of epilepsy, age of onset of epilepsy and seizure burden (defined as a function of seizure frequency and duration of epilepsy). RESULTS Whole-tract diffusion characteristics of patients with TLE differed according to side of epilepsy and were significantly different between patients and controls. Waypoint comparisons along each tract revealed that patients had significantly altered tissue characteristics of the ipsilateral inferior-longitudinal, uncinate fasciculus, superior longitudinal fasciculus and cingulum relative to controls. Changes were more widespread (ipsilaterally and contralaterally) in patients with left TLE while patients with right TLE showed changes that remained spatially confined in ipsilateral tract regions. We found no relationship between DTI alterations and volume of the epileptogenic hippocampus. DTI alterations of anterior ipsilateral uncinate and inferior-longitudinal fasciculus correlated with duration of epilepsy (over and above effects of age) and age at onset of epilepsy. Seizure burden correlated with tissue characteristics of the uncinate fasciculus. CONCLUSION This study shows that TRACULA permits the detection of alterations of DTI tract scalar metrics in patients with TLE. It also provides the opportunity to explore relationships with structural volume measurements and clinical variables along white matter tracts. Our data suggests that the anterior temporal lobe portions of the uncinate and inferior-longitudinal fasciculus may be particularly vulnerable to pathological alterations in patients with TLE. These alterations are unrelated to the extent of hippocampal atrophy (and therefore potentially mediated by independent mechanisms) but influenced by chronicity and severity of the disorder.
Collapse
Affiliation(s)
- Barbara A.K. Kreilkamp
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, UK
- Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Bernd Weber
- Department of Epileptology, University of Bonn, Germany
- Department of NeuroCognition/Imaging, Life&Brain Research Center, Bonn, Germany
| | - Mark P. Richardson
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Simon S. Keller
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, UK
- Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, UK
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| |
Collapse
|
38
|
Dinkelacker V, Dupont S, Samson S. The new approach to classification of focal epilepsies: Epileptic discharge and disconnectivity in relation to cognition. Epilepsy Behav 2016; 64:322-328. [PMID: 27765519 DOI: 10.1016/j.yebeh.2016.08.028] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Revised: 08/30/2016] [Accepted: 08/31/2016] [Indexed: 12/23/2022]
Abstract
The new classification of epilepsy stratifies the disease into an acute level, based on seizures, and an overarching chronic level of epileptic syndromes (Berg et al., 2010). In this new approach, seizures are considered either to originate and evolve in unilateral networks or to rapidly encompass both hemispheres. This concept extends the former vision of focal and generalized epilepsies to a genuine pathology of underlying networks. These key aspects of the new classification can be linked to the concept of cognitive curtailing in focal epilepsy. The present review will discuss the conceptual implications for acute and chronic cognitive deficits with special emphasis on transient and structural disconnectivity. Acute transient disruption of brain function is the hallmark of focal seizures. Beyond seizures, however, interictal epileptic discharges (IEDs) are increasingly recognized to interfere with physiological brain circuitry. Both concomitant EEG and high-precision neuropsychological testing are necessary to detect these subtle effects, which may concern task-specific or default-mode networks. More recent data suggest that longstanding IEDs may affect brain maturation and eventually be considered as a biomarker of pathological wiring. This brings us to the overarching level of chronic cognitive and behavioral comorbidity. We will discuss alterations in structural connectivity measured with diffusion-weighted imaging and tractography. Among focal epilepsies, much of our current insights are derived from temporal lobe epilepsy and its impact on neuropsychological and psychiatric functioning. Structural disconnectivity is maximal in the temporal lobe but also concerns widespread language circuitry. Eventually, pathological wiring may contribute to the clinical picture of cognitive dysfunction. We conclude with the extrapolation of these concepts to current research topics and to the necessity of establishing individual patient profiles of network pathology with EEG, high-precision neuropsychological testing, and state-of-the-art neuroimaging. This article is part of a Special Issue entitled "The new approach to classification: Rethinking cognition and behavior in epilepsy".
Collapse
Affiliation(s)
- Vera Dinkelacker
- Neurology Unit, Rothschild Foundation, 25 Rue Manin, 75019, Paris, France; Centre de Recherche de l'Institut du Cerveau et de la Moëlle Épinière (CRICM), UPMC-UMR 7225 CNRS-UMRS 975 INSERM, Paris, France.
| | - Sophie Dupont
- Centre de Recherche de l'Institut du Cerveau et de la Moëlle Épinière (CRICM), UPMC-UMR 7225 CNRS-UMRS 975 INSERM, Paris, France; Epilepsy Unit, Pitié-Salpêtrière Hospital, 47-83 boulevard de l'Hôpital, 75013, Paris, France
| | - Séverine Samson
- Epilepsy Unit, Pitié-Salpêtrière Hospital, 47-83 boulevard de l'Hôpital, 75013, Paris, France; Laboratoire PSITEC (EA 4072), Université de Lille 3, France
| |
Collapse
|
39
|
Zhang Z, Liao W, Xu Q, Wei W, Zhou HJ, Sun K, Yang F, Mantini D, Ji X, Lu G. Hippocampus-associated causal network of structural covariance measuring structural damage progression in temporal lobe epilepsy. Hum Brain Mapp 2016; 38:753-766. [PMID: 27677885 DOI: 10.1002/hbm.23415] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2015] [Revised: 08/24/2016] [Accepted: 09/21/2016] [Indexed: 01/06/2023] Open
Abstract
In mesial temporal lobe epilepsy (mTLE), the causal relationship of morphometric alterations between hippocampus and the other regions, that is, how the hippocampal atrophy leads to progressive morphometric alterations in the epileptic network regions remains largely unclear. In this study, a causal network of structural covariance (CaSCN) was proposed to map the causal effects of hippocampal atrophy on the network-based morphometric alterations in mTLE. It was hypothesized that if cross-sectional morphometric MRI data could be attributed temporal information, for example, by sequencing the data according to disease progression information, GCA would be a feasible approach for constructing a CaSCN. Based on a large cohort of mTLE patients (n = 108), the hippocampus-associated CaSCN revealed that the hippocampus and the thalamus were prominent nodes exerting causal effects (i.e., GM reduction) on other regions and that the prefrontal cortex and cerebellum were prominent nodes being subject to causal effects. Intriguingly, compensatory increased gray matter volume in the contralateral temporal region and post cingulate cortex were also detected. The method unraveled richer information for mapping network atrophy in mTLE relative to the traditional methods of stage-specific comparisons and structured covariance network. This study provided new evidence on the network spread mechanism in terms of the causal influence of hippocampal atrophy on progressive brain structural alterations in mTLE. Hum Brain Mapp 38:753-766, 2017. © 2016 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China.,State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210093, China
| | - Wei Liao
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China.,Center for Cognition and Brain Disorders, Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, China
| | - Qiang Xu
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Wei Wei
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Helen Juan Zhou
- Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorder Program, Duke-NUS Graduate Medical School, National University of Singapore, Singapore, Singapore
| | - Kangjian Sun
- Department of Neurosurgery, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Fang Yang
- Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Dante Mantini
- Faculty of Kinesiology and Rehabilitation Sciences, KU Leuven, Belgium
| | - Xueman Ji
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China.,State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210093, China
| |
Collapse
|
40
|
Elliott CA, Gross DW, Wheatley BM, Beaulieu C, Sankar T. Progressive contralateral hippocampal atrophy following surgery for medically refractory temporal lobe epilepsy. Epilepsy Res 2016; 125:62-71. [DOI: 10.1016/j.eplepsyres.2016.06.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2015] [Revised: 06/02/2016] [Accepted: 06/24/2016] [Indexed: 11/26/2022]
|
41
|
Conrad BN, Rogers BP, Abou-Khalil B, Morgan VL. Increased MRI volumetric correlation contralateral to seizure focus in temporal lobe epilepsy. Epilepsy Res 2016; 126:53-61. [PMID: 27429056 DOI: 10.1016/j.eplepsyres.2016.07.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2016] [Revised: 06/17/2016] [Accepted: 07/01/2016] [Indexed: 10/21/2022]
Abstract
Quantification of volumetric correlation may be sensitive to disease alterations undetected by standard voxel based morphometry (VBM) such as subtle, synchronous alterations in regional volumes, and may provide complementary evidence of the structural impact of temporal lobe epilepsy (TLE) on the brain. The purpose of this study was to quantify differences of regional volumetric correlation in right (RTLE) and left (LTLE) TLE patients compared to healthy controls. A T1 weighted 3T MRI was acquired (1mm(3)) in 44 drug resistant unilateral TLE patients (n=26 RTLE, n=18 LTLE) and 44 individually age and gender matched healthy controls. Images were processed using a standard VBM framework and volumetric correlation was calculated across subjects in 90 regions and compared between patients and controls. Results were summarized across hemispheres and region groups. There was increased correlation involving the contralateral homologues of the seizure foci/network in the limbic, subcortical and temporal regions in both RTLE and LTLE. Outside these regions, results implied widespread correlated alterations across several contralateral lobes in LTLE, with more focal changes in RTLE. These findings complement previous volumetric studies in TLE describing more ipsilateral atrophy, by revealing subtle coordinated volumetric changes to identify a more widespread effect of TLE across the brain.
Collapse
Affiliation(s)
- Benjamin N Conrad
- Vanderbilt University Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA
| | - Baxter P Rogers
- Vanderbilt University Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA
| | | | - Victoria L Morgan
- Vanderbilt University Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA.
| |
Collapse
|
42
|
Doucet GE, He X, Sperling M, Sharan A, Tracy JI. Gray Matter Abnormalities in Temporal Lobe Epilepsy: Relationships with Resting-State Functional Connectivity and Episodic Memory Performance. PLoS One 2016; 11:e0154660. [PMID: 27171178 PMCID: PMC4865085 DOI: 10.1371/journal.pone.0154660] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Accepted: 04/15/2016] [Indexed: 11/19/2022] Open
Abstract
Temporal lobe epilepsy (TLE) affects multiple brain regions through evidence from both structural (gray matter; GM) and functional connectivity (FC) studies. We tested whether these structural abnormalities were associated with FC abnormalities, and assessed the ability of these measures to explain episodic memory impairments in this population. A resting-state and T1 sequences were acquired on 94 (45 with mesial temporal pathology) TLE patients and 50 controls, using magnetic resonance imaging (MRI) technique. A voxel-based morphometry analysis was computed to determine the GM volume differences between groups (right, left TLE, controls). Resting-state FC between the abnormal GM volume regions was computed, and compared between groups. Finally, we investigated the relation between EM, GM and FC findings. Patients with and without temporal pathology were analyzed separately. The results revealed reduced GM volume in multiple regions in the patients relative to the controls. Using FC, we found the abnormal GM regions did not display abnormal functional connectivity. Lastly, we found in left TLE patients, verbal episodic memory was associated with abnormal left posterior hippocampus volume, while in right TLE, non-verbal episodic memory was better predicted by resting-state FC measures. This study investigated TLE abnormalities using a multi-modal approach combining GM, FC and neurocognitive measures. We did not find that the GM abnormalities were functionally or abnormally connected during an inter-ictal resting state, which may reflect a weak sensitivity of functional connectivity to the epileptic network. We provided evidence that verbal and non-verbal episodic memory in left and right TLE patients may have distinct relationships with structural and functional measures. Lastly, we provide data suggesting that in the setting of occult, non-lesional right TLE pathology, a coupling of structural and functional abnormalities in extra-temporal/non-ictal regions is necessary to produce reductions in episodic memory recall. The latter, in particular, demonstrates the complex structure/function interactions at work when trying to understand cognition in TLE, suggesting that subtle network effects can emerge bearing specific relationships to hemisphere and the type of pathology.
Collapse
Affiliation(s)
- Gaelle E. Doucet
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, United States of America
| | - Xiaosong He
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, United States of America
| | - Michael Sperling
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, United States of America
| | - Ashwini Sharan
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States of America
| | - Joseph I. Tracy
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, United States of America
- * E-mail:
| |
Collapse
|
43
|
Chassoux F, Artiges E, Semah F, Desarnaud S, Laurent A, Landre E, Gervais P, Devaux B, Helal OB. Determinants of brain metabolism changes in mesial temporal lobe epilepsy. Epilepsia 2016; 57:907-19. [DOI: 10.1111/epi.13377] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/07/2016] [Indexed: 01/01/2023]
Affiliation(s)
- Francine Chassoux
- Department of Neurosurgery; Sainte-Anne Hospital; Paris France
- Paris Descartes University; Paris France
- INSERM U 1129; Paris France
- Department of Nuclear Medicine; SHFJ; CEA; Orsay France
| | - Eric Artiges
- INSERM U 1000; Paris France
- Psychiatry Department 91G16; Orsay Hospital; Paris Descartes University; Orsay France
| | - Franck Semah
- Department of Nuclear Medicine; INSERM U 1171; University Hospital of Lille; Lille France
| | - Serge Desarnaud
- Department of Nuclear Medicine; SHFJ; CEA; Orsay France
- INSERM U 1023 IMIV; CEA; Paris-Sud University; Orsay France
| | - Agathe Laurent
- Department of Neurosurgery; Sainte-Anne Hospital; Paris France
- Paris Descartes University; Paris France
- INSERM U 1129; Paris France
| | - Elisabeth Landre
- Department of Neurosurgery; Sainte-Anne Hospital; Paris France
- Paris Descartes University; Paris France
| | - Philippe Gervais
- Department of Nuclear Medicine; SHFJ; CEA; Orsay France
- INSERM U 1023 IMIV; CEA; Paris-Sud University; Orsay France
| | - Bertrand Devaux
- Department of Neurosurgery; Sainte-Anne Hospital; Paris France
- Paris Descartes University; Paris France
| | - Ourkia Badia Helal
- Department of Nuclear Medicine; SHFJ; CEA; Orsay France
- INSERM U 1023 IMIV; CEA; Paris-Sud University; Orsay France
| |
Collapse
|
44
|
Wei W, Zhang Z, Xu Q, Yang F, Sun K, Lu G. More Severe Extratemporal Damages in Mesial Temporal Lobe Epilepsy With Hippocampal Sclerosis Than That With Other Lesions: A Multimodality MRI Study. Medicine (Baltimore) 2016; 95:e3020. [PMID: 26962820 PMCID: PMC4998901 DOI: 10.1097/md.0000000000003020] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Mesial temporal lobe epilepsy with hippocampal sclerosis (mTLE-HS) presents different clinical presentations from that with other lesions (OL). It is significant to investigate the neural mechanism underlying the different clinical presentations using neuroimaging study.Thirty mTLE patients with mTLE-HS, 30 mTLE patients with other lesions (mTLE-OL), and 30 age- and sex-matched healthy controls were involved. Amplitude of low-frequency fluctuation (ALFF) analysis-based resting-state functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM) based morphometric MRI were employed to describing functional and structural imaging alterations in mTLE. Imaging parameters of ALFF and gray matter volume (GMV) were compared among groups and correlated with clinical variables and cognitive scores.For parameter of ALFF, both patient groups of mTLE-HS and mTLE-OL showed decrease in the frontal cortices relative to the healthy controls; mTLE-HS showed more decrease in the prefrontal and brain default regions relative to mTLE-OL. For GMV, both patient groups showed decrease in the frontal cortex, thalamus, and cerebellum; mTLE-HS showed more GMV decrease relative to the mTLE-OL, also mainly in the prefrontal and brain default regions. In both patient groups, the prefrontal regions showed negative correlation between GMV and epilepsy duration.This work revealed distinct alteration patterns of functional and structural brain organizations in mTLEs with different forms. MTLE-HS, despite with smaller lesion size of the pathological focus, presented more severe functional and structural damages in the extratemporal regions than mTLE-OL. The findings provided imaging evidence to support the proposal that mTLE-HS is a special epilepsy syndrome.
Collapse
Affiliation(s)
- Wei Wei
- From the Department of Medical Imaging (WW, ZZ, QX, GL), Department of Neurology (QX), Department of Neurosurgery (FY), Jinling Hospital, Nanjing University School of Medicine, and State Key Laboratory of Analytical Chemistry for Life Science (ZZ, GL), Nanjing University, Nanjing, China
| | | | | | | | | | | |
Collapse
|
45
|
Alvim MKM, Coan AC, Campos BM, Yasuda CL, Oliveira MC, Morita ME, Cendes F. Progression of gray matter atrophy in seizure-free patients with temporal lobe epilepsy. Epilepsia 2016; 57:621-9. [PMID: 26865066 DOI: 10.1111/epi.13334] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2016] [Indexed: 02/01/2023]
Abstract
OBJECTIVES To investigate the presence and progression of gray matter (GM) reduction in seizure-free patients with temporal lobe epilepsy (TLE). METHODS We enrolled 39 consecutive TLE patients, seizure-free for at least 2 years--20 with magnetic resonance imaging (MRI) signs of hippocampal sclerosis (TLE-HS), 19 with normal MRI (TLE-NL), and 74 healthy controls. For longitudinal analysis, we included individuals who had a second MRI with minimum interval of 18 months: 21 patients (10 TLE-HS, 11 TLE-NL) and 11 controls. Three-dimensional (3D) T1 -weighted images acquired in 3 Tesla MRI were analyzed with voxel-based morphometry (VBM). The images of patients with right-sided interictal epileptogenic zone (EZ) were right-left flipped, as well as a comparable proportion of controls. Cross-sectional analysis: The patients' images from each group were compared to controls to investigate differences in GM volumes. Longitudinal analysis: The first and second images were compared in each group to look for decreased GM volume. RESULTS Cross-sectional analysis: Patients with TLE-HS had diffuse GM atrophy, including hippocampus and parahippocampal gyrus, insula, frontal, and occipital lobes ipsilateral to EZ, bilateral thalamus and contralateral orbitofrontal gyrus, and caudate. In contrast, TLE-NL group did not present significant differences compared to controls. Longitudinal analysis: TLE-HS presented progressive GM reduction in ipsilateral insula and occipital lobe, contralateral motor area, and bilateral temporal and frontal lobes. TLE-NL had GM progression in ipsilateral hypothalamus and parietal lobe, contralateral cerebellum, and bilateral temporal lobe. Controls did not show changes in GM volume between MRIs. SIGNIFICANCE Diffuse extrahippocampal GM atrophy is present in seizure-free patients with TLE-HS. In addition, there is progressive GM atrophy in patients with and without HS. These results demonstrate that not only ongoing seizures are involved in the progression of GM atrophy. An underlying pathologic mechanism could be responsible for progressive brain volume loss in TLE patients even in seizure-free periods.
Collapse
Affiliation(s)
- Marina K M Alvim
- Department of Neurology, Neuroimaging Laboratory, State University of Campinas, Campinas, São Paulo, Brazil
| | - Ana C Coan
- Department of Neurology, Neuroimaging Laboratory, State University of Campinas, Campinas, São Paulo, Brazil
| | - Brunno M Campos
- Department of Neurology, Neuroimaging Laboratory, State University of Campinas, Campinas, São Paulo, Brazil
| | - Clarissa L Yasuda
- Department of Neurology, Neuroimaging Laboratory, State University of Campinas, Campinas, São Paulo, Brazil
| | - Mariana C Oliveira
- Department of Neurology, Neuroimaging Laboratory, State University of Campinas, Campinas, São Paulo, Brazil
| | - Marcia E Morita
- Department of Neurology, Neuroimaging Laboratory, State University of Campinas, Campinas, São Paulo, Brazil
| | - Fernando Cendes
- Department of Neurology, Neuroimaging Laboratory, State University of Campinas, Campinas, São Paulo, Brazil
| |
Collapse
|
46
|
Elkommos S, Weber B, Niehusmann P, Volmering E, Richardson MP, Goh YY, Marson AG, Elger C, Keller SS. Hippocampal internal architecture and postoperative seizure outcome in temporal lobe epilepsy due to hippocampal sclerosis. Seizure 2016; 35:65-71. [PMID: 26803053 PMCID: PMC4773400 DOI: 10.1016/j.seizure.2016.01.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Revised: 12/11/2015] [Accepted: 01/05/2016] [Indexed: 10/31/2022] Open
Abstract
PURPOSE Semi-quantitative analysis of hippocampal internal architecture (HIA) on MRI has been shown to be a reliable predictor of the side of seizure onset in patients with temporal lobe epilepsy (TLE). In the present study, we investigated the relationship between postoperative seizure outcome and preoperative semi-quantitative measures of HIA. METHODS We determined HIA on high in-plane resolution preoperative T2 short tau inversion recovery MR images in 79 patients with presumed unilateral mesial TLE (mTLE) due to hippocampal sclerosis (HS) who underwent amygdalohippocampectomy and postoperative follow up. HIA was investigated with respect to postoperative seizure freedom, neuronal density determined from resected hippocampal specimens, and conventionally acquired hippocampal volume. RESULTS HIA ratings were significantly related to some neuropathological features of the resected hippocampus (e.g. neuronal density of selective CA regions, Wyler grades), and bilaterally with preoperative hippocampal volume. However, there were no significant differences in HIA ratings of the to-be-resected or contralateral hippocampus between patients rendered seizure free (ILAE 1) compared to those continuing to experience seizures (ILAE 2-5). CONCLUSIONS This work indicates that semi-quantitative assessment of HIA on high-resolution MRI provides a surrogate marker of underlying histopathology, but cannot prospectively distinguish between patients who will continue to experience postoperative seizures and those who will be rendered seizure free. The predictive power of HIA for postoperative seizure outcome in non-lesional patients with TLE should be explored.
Collapse
Affiliation(s)
- Samia Elkommos
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, UK
| | - Bernd Weber
- Department of Epileptology, University of Bonn, Germany; Department of Neurocognition/Imaging, Life&Brain Research Centre, Bonn, Germany
| | - Pitt Niehusmann
- Department of Neuropathology, University of Bonn, Germany; Department of Neuropathology, Oslo University Hospital, Norway
| | | | - Mark P Richardson
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Yen Y Goh
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, UK
| | - Anthony G Marson
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, UK
| | | | - Simon S Keller
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, UK; Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, UK; Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| |
Collapse
|
47
|
Kim JB, Suh SI, Kim JH. Volumetric and shape analysis of hippocampal subfields in unilateral mesial temporal lobe epilepsy with hippocampal atrophy. Epilepsy Res 2015; 117:74-81. [DOI: 10.1016/j.eplepsyres.2015.09.004] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2015] [Revised: 08/11/2015] [Accepted: 09/07/2015] [Indexed: 11/30/2022]
|
48
|
Park KM, Han YH, Kim TH, Mun CW, Shin KJ, Ha SY, Park J, Hur YJ, Kim HY, Park SH, Kim SE. Cerebellar white matter changes in patients with newly diagnosed partial epilepsy of unknown etiology. Clin Neurol Neurosurg 2015; 138:25-30. [DOI: 10.1016/j.clineuro.2015.07.017] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2014] [Revised: 07/10/2015] [Accepted: 07/24/2015] [Indexed: 10/23/2022]
|
49
|
Abdelnour F, Mueller S, Raj A. Relating Cortical Atrophy in Temporal Lobe Epilepsy with Graph Diffusion-Based Network Models. PLoS Comput Biol 2015; 11:e1004564. [PMID: 26513579 PMCID: PMC4626097 DOI: 10.1371/journal.pcbi.1004564] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2015] [Accepted: 09/21/2015] [Indexed: 12/20/2022] Open
Abstract
Mesial temporal lobe epilepsy (TLE) is characterized by stereotyped origination and spread pattern of epileptogenic activity, which is reflected in stereotyped topographic distribution of neuronal atrophy on magnetic resonance imaging (MRI). Both epileptogenic activity and atrophy spread appear to follow white matter connections. We model the networked spread of activity and atrophy in TLE from first principles via two simple first order network diffusion models. Atrophy distribution is modeled as a simple consequence of the propagation of epileptogenic activity in one model, and as a progressive degenerative process in the other. We show that the network models closely reproduce the regional volumetric gray matter atrophy distribution of two epilepsy cohorts: 29 TLE subjects with medial temporal sclerosis (TLE-MTS), and 50 TLE subjects with normal appearance on MRI (TLE-no). Statistical validation at the group level suggests high correlation with measured atrophy (R = 0.586 for TLE-MTS, R = 0.283 for TLE-no). We conclude that atrophy spread model out-performs the hyperactivity spread model. These results pave the way for future clinical application of the proposed model on individual patients, including estimating future spread of atrophy, identification of seizure onset zones and surgical planning.
Collapse
Affiliation(s)
- Farras Abdelnour
- Radiology, Weill Cornell Medical College, New York, New York, United States of America
- * E-mail:
| | - Susanne Mueller
- Radiology, University of California San Francisco, San Francisco, California, United States of America
| | - Ashish Raj
- Radiology, Weill Cornell Medical College, New York, New York, United States of America
| |
Collapse
|
50
|
Jin SH, Chung CK. Functional substrate for memory function differences between patients with left and right mesial temporal lobe epilepsy associated with hippocampal sclerosis. Epilepsy Behav 2015; 51:251-8. [PMID: 26300534 DOI: 10.1016/j.yebeh.2015.07.032] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2015] [Revised: 07/24/2015] [Accepted: 07/24/2015] [Indexed: 10/23/2022]
Abstract
OBJECTIVE Little is known about the functional substrate for memory function differences in patients with left or right mesial temporal lobe epilepsy (mTLE) associated with hippocampal sclerosis (HS) from an electrophysiological perspective. To characterize these differences, we hypothesized that hippocampal theta connectivity in the resting-state might be different between patients with left and right mTLE with HS and be correlated with memory performance. METHODS Resting-state hippocampal theta connectivity, identified via whole-brain magnetoencephalography, was evaluated. Connectivity and memory function in 41 patients with mTLE with HS (left mTLE=22; right mTLE=19) were compared with those in 46 age-matched healthy controls and 28 patients with focal cortical dysplasia (FCD) but without HS. RESULTS Connectivity between the right hippocampus and the left middle frontal gyrus was significantly stronger in patients with right mTLE than in patients with left mTLE. Moreover, this connectivity was positively correlated with delayed verbal recall and recognition scores in patients with mTLE. Patients with left mTLE had greater delayed recall impairment than patients with right mTLE and FCD. Similarly, delayed recognition performance was worse in patients with left mTLE than in patients with right mTLE and FCD. No significant differences in memory function between patients with right mTLE and FCD were detected. Patients with right mTLE showed significantly stronger hippocampal theta connectivity between the right hippocampus and left middle frontal gyrus than patients with FCD and left mTLE. CONCLUSION Our results suggest that right hippocampal-left middle frontal theta connectivity could be a functional substrate that can account for differences in memory function between patients with left and right mTLE. This functional substrate might be related to different compensatory mechanisms against the structural hippocampal lesions in left and right mTLE groups. Given the positive correlation between connectivity and delayed verbal memory function, hemispheric-specific hippocampal-frontal theta connectivity assessment could be useful as an electrophysiological indicator of delayed verbal memory function in patients with mTLE with HS.
Collapse
Affiliation(s)
- Seung-Hyun Jin
- Neuroscience Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Chun Kee Chung
- Neuroscience Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea; Department of Neurosurgery, Seoul National University Hospital, Seoul, Republic of Korea; Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Republic of Korea; Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea.
| |
Collapse
|