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Paredes-Aragon E, AlKhaldi NA, Ballesteros-Herrera D, Mirsattari SM. Stereo-Encephalographic Presurgical Evaluation of Temporal Lobe Epilepsy: An Evolving Science. Front Neurol 2022; 13:867458. [PMID: 35720095 PMCID: PMC9197919 DOI: 10.3389/fneur.2022.867458] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 04/25/2022] [Indexed: 11/15/2022] Open
Abstract
Drug-resistant epilepsy is present in nearly 30% of patients. Resection of the epileptogenic zone has been found to be the most effective in achieving seizure freedom. The study of temporal lobe epilepsy for surgical treatment is extensive and complex. It involves a multidisciplinary team in decision-making with initial non-invasive studies (Phase I), providing 70% of the required information to elaborate a hypothesis and treatment plans. Select cases present more complexity involving bilateral clinical or electrographic manifestations, have contradicting information, or may involve deeper structures as a part of the epileptogenic zone. These cases are discussed by a multidisciplinary team of experts with a hypothesis for invasive methods of study. Subdural electrodes were once the mainstay of invasive presurgical evaluation and in later years most Comprehensive Epilepsy Centers have shifted to intracranial recordings. The intracranial recording follows original concepts since its development by Bancaud and Talairach, but great advances have been made in the field. Stereo-electroencephalography is a growing field of study, treatment, and establishment of seizure pattern complexities. In this comprehensive review, we explore the indications, usefulness, discoveries in interictal and ictal findings, pitfalls, and advances in the science of presurgical stereo-encephalography for temporal lobe epilepsy.
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Affiliation(s)
- Elma Paredes-Aragon
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Norah A AlKhaldi
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada.,Neurology Department, King Fahad Hospital of the University, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Daniel Ballesteros-Herrera
- Neurosurgery Department, National Institute of Neurology and Neurosurgery "Dr. Manuel Velasco Suárez", Mexico City, Mexico
| | - Seyed M Mirsattari
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada.,Departments of Clinical Neurological Sciences, Diagnostic Imaging, Biomedical Imaging and Psychology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
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Kudo K, Morise H, Ranasinghe KG, Mizuiri D, Bhutada AS, Chen J, Findlay A, Kirsch HE, Nagarajan SS. Magnetoencephalography Imaging Reveals Abnormal Information Flow in Temporal Lobe Epilepsy. Brain Connect 2022; 12:362-373. [PMID: 34210170 PMCID: PMC9131359 DOI: 10.1089/brain.2020.0989] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background/Introduction: Widespread network disruption has been hypothesized to be an important predictor of outcomes in patients with refractory temporal lobe epilepsy (TLE). Most studies examining functional network disruption in epilepsy have largely focused on the symmetric bidirectional metrics of the strength of network connections. However, a more complete description of network dysfunction impacts in epilepsy requires an investigation of the potentially more sensitive directional metrics of information flow. Methods: This study describes a whole-brain magnetoencephalography-imaging approach to examine resting-state directional information flow networks, quantified by phase-transfer entropy (PTE), in patients with TLE compared with healthy controls (HCs). Associations between PTE and clinical characteristics of epilepsy syndrome are also investigated. Results: Deficits of information flow were specific to alpha-band frequencies. In alpha band, while HCs exhibit a clear posterior-to-anterior directionality of information flow, in patients with TLE, this pattern of regional information outflow and inflow was significantly altered in the frontal and occipital regions. The changes in information flow within the alpha band in selected brain regions were correlated with interictal spike frequency and duration of epilepsy. Conclusions: Impaired information flow is an important dimension of network dysfunction associated with the pathophysiological mechanisms of TLE.
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Affiliation(s)
- Kiwamu Kudo
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
- Medical Imaging Business Center, Ricoh Company Ltd., Kanazawa, Japan
| | - Hirofumi Morise
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
- Medical Imaging Business Center, Ricoh Company Ltd., Kanazawa, Japan
| | - Kamalini G. Ranasinghe
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Danielle Mizuiri
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Abhishek S. Bhutada
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Jessie Chen
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Anne Findlay
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Heidi E. Kirsch
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
- Epilepsy Center, Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Srikantan S. Nagarajan
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
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Lisgaras CP, Scharfman HE. Robust chronic convulsive seizures, high frequency oscillations, and human seizure onset patterns in an intrahippocampal kainic acid model in mice. Neurobiol Dis 2022; 166:105637. [PMID: 35091040 PMCID: PMC9034729 DOI: 10.1016/j.nbd.2022.105637] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 01/05/2022] [Accepted: 01/22/2022] [Indexed: 01/21/2023] Open
Abstract
Intrahippocampal kainic acid (IHKA) has been widely implemented to simulate temporal lobe epilepsy (TLE), but evidence of robust seizures is usually limited. To resolve this problem, we slightly modified previous methods and show robust seizures are common and frequent in both male and female mice. We employed continuous wideband video-EEG monitoring from 4 recording sites to best demonstrate the seizures. We found many more convulsive seizures than most studies have reported. Mortality was low. Analysis of convulsive seizures at 2-4 and 10-12 wks post-IHKA showed a robust frequency (2-4 per day on average) and duration (typically 20-30 s) at each time. Comparison of the two timepoints showed that seizure burden became more severe in approximately 50% of the animals. We show that almost all convulsive seizures could be characterized as either low-voltage fast or hypersynchronous onset seizures, which has not been reported in a mouse model of epilepsy and is important because these seizure types are found in humans. In addition, we report that high frequency oscillations (>250 Hz) occur, resembling findings from IHKA in rats and TLE patients. Pathology in the hippocampus at the site of IHKA injection was similar to mesial temporal lobe sclerosis and reduced contralaterally. In summary, our methods produce a model of TLE in mice with robust convulsive seizures, and there is variable progression. HFOs are robust also, and seizures have onset patterns and pathology like human TLE. SIGNIFICANCE: Although the IHKA model has been widely used in mice for epilepsy research, there is variation in outcomes, with many studies showing few robust seizures long-term, especially convulsive seizures. We present an implementation of the IHKA model with frequent convulsive seizures that are robust, meaning they are >10 s and associated with complex high frequency rhythmic activity recorded from 2 hippocampal and 2 cortical sites. Seizure onset patterns usually matched the low-voltage fast and hypersynchronous seizures in TLE. Importantly, there is low mortality, and both sexes can be used. We believe our results will advance the ability to use the IHKA model of TLE in mice. The results also have important implications for our understanding of HFOs, progression, and other topics of broad interest to the epilepsy research community. Finally, the results have implications for preclinical drug screening because seizure frequency increased in approximately half of the mice after a 6 wk interval, suggesting that the typical 2 wk period for monitoring seizure frequency is insufficient.
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Affiliation(s)
- Christos Panagiotis Lisgaras
- Departments of Child & Adolescent Psychiatry, Neuroscience & Physiology, and Psychiatry, and the Neuroscience Institute, New York University Langone Health, 550 First Ave., New York, NY 10016, United States of America,Center for Dementia Research, The Nathan Kline Institute for Psychiatric Research, New York State Office of Mental Health, 140 Old Orangeburg Road, Bldg. 35, Orangeburg, NY 10962, United States of America
| | - Helen E. Scharfman
- Departments of Child & Adolescent Psychiatry, Neuroscience & Physiology, and Psychiatry, and the Neuroscience Institute, New York University Langone Health, 550 First Ave., New York, NY 10016, United States of America,Center for Dementia Research, The Nathan Kline Institute for Psychiatric Research, New York State Office of Mental Health, 140 Old Orangeburg Road, Bldg. 35, Orangeburg, NY 10962, United States of America,Corresponding author at: The Nathan Kline Institute, Center for Dementia Research, 140 Old Orangeburg Rd. Bldg. 35, Orangeburg, NY 10962, United States of America. (H.E. Scharfman)
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Multimodal Presurgical Evaluation of Medically Refractory Focal Epilepsy in Adults: An Update for Radiologists. AJR Am J Roentgenol 2022; 219:488-500. [PMID: 35441531 DOI: 10.2214/ajr.22.27588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Surgery is a potentially curative treatment option for patients with medically refractory focal epilepsy. Advanced neuroimaging modalities often improve surgical outcomes by contributing key information during the highly individualized surgical planning process and intraoperative localization. Hence, neuroradiologists play an integral role as part of the multidisciplinary management team. In this review, we initially present the conceptual background and practical framework of the presurgical evaluation process, including a description of the surgical treatment approaches in medically refractory focal epilepsy in adults. This background is followed by an overview of the advanced modalities commonly used during the presurgical workup at level IV epilepsy centers including diffusion imaging techniques, blood oxygen level dependent (BOLD) functional MRI (fMRI), PET, SPECT, and subtraction ictal SPECT, as well as by introductions to 7-T MRI and electrophysiologic techniques including electroencephalography (EEG) and magnetoencephalography (MEG). We also provide illustrative case examples of multimodal neuroimaging including PET/MRI, PET/MRI-DTI, subtraction ictal SPECT, and image-guided stereotactic planning with fMRI-DTI.
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Weiss SA, Pastore T, Orosz I, Rubinstein D, Gorniak R, Waldman Z, Fried I, Wu C, Sharan A, Slezak D, Worrell G, Engel J, Sperling MR, Staba RJ. Graph theoretical measures of fast ripples support the epileptic network hypothesis. Brain Commun 2022; 4:fcac101. [PMID: 35620169 PMCID: PMC9128387 DOI: 10.1093/braincomms/fcac101] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 02/10/2022] [Accepted: 04/12/2022] [Indexed: 11/16/2022] Open
Abstract
The epileptic network hypothesis and epileptogenic zone hypothesis are two
theories of ictogenesis. The network hypothesis posits that coordinated activity
among interconnected nodes produces seizures. The epileptogenic zone hypothesis
posits that distinct regions are necessary and sufficient for seizure
generation. High-frequency oscillations, and particularly fast ripples, are
thought to be biomarkers of the epileptogenic zone. We sought to test these
theories by comparing high-frequency oscillation rates and networks in surgical
responders and non-responders, with no appreciable change in seizure frequency
or severity, within a retrospective cohort of 48 patients implanted with
stereo-EEG electrodes. We recorded inter-ictal activity during non-rapid eye
movement sleep and semi-automatically detected and quantified high-frequency
oscillations. Each electrode contact was localized in normalized coordinates. We
found that the accuracy of seizure onset zone electrode contact classification
using high-frequency oscillation rates was not significantly different in
surgical responders and non-responders, suggesting that in non-responders the
epileptogenic zone partially encompassed the seizure onset zone(s)
(P > 0.05). We also found that in the
responders, fast ripple on oscillations exhibited a higher spectral content in
the seizure onset zone compared with the non-seizure onset zone
(P < 1 × 10−5).
By contrast, in the non-responders, fast ripple had a lower spectral content in
the seizure onset zone
(P < 1 × 10−5).
We constructed two different networks of fast ripple with a spectral content
>350 Hz. The first was a rate–distance network that
multiplied the Euclidian distance between fast ripple-generating contacts by the
average rate of fast ripple in the two contacts. The radius of the
rate–distance network, which excluded seizure onset zone nodes,
discriminated non-responders, including patients not offered resection or
responsive neurostimulation due to diffuse multifocal onsets, with an accuracy
of 0.77 [95% confidence interval (CI) 0.56–0.98]. The second fast
ripple network was constructed using the mutual information between the timing
of the events to measure functional connectivity. For most non-responders, this
network had a longer characteristic path length, lower mean local efficiency in
the non-seizure onset zone, and a higher nodal strength among non-seizure onset
zone nodes relative to seizure onset zone nodes. The graphical theoretical
measures from the rate–distance and mutual information networks of 22
non- responsive neurostimulation treated patients was used to train a support
vector machine, which when tested on 13 distinct patients classified
non-responders with an accuracy of 0.92 (95% CI 0.75–1). These
results indicate patients who do not respond to surgery or those not selected
for resection or responsive neurostimulation can be explained by the epileptic
network hypothesis that is a decentralized network consisting of widely
distributed, hyperexcitable fast ripple-generating nodes.
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Affiliation(s)
- Shennan A Weiss
- Dept. of Neurology, State University of New York Downstate, Brooklyn, New York, 11203 USA
- Dept. of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, New York, 11203 USA
- Dept. of Neurology, New York City Health + Hospitals/Kings County, Brooklyn, NY, USA
| | - Tomas Pastore
- Dept. of Computer Science, University of Buenos Aires, Buenos Aires, Argentina
| | - Iren Orosz
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | - Daniel Rubinstein
- Depts. of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, 19107, USA
| | - Richard Gorniak
- Dept. of Neuroradiology, Thomas Jefferson University, Philadelphia, Pennsylvania, 19107, USA
| | - Zachary Waldman
- Depts. of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, 19107, USA
| | - Itzhak Fried
- Dept. of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | - Chengyuan Wu
- Dept. of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania, 19107, USA
| | - Ashwini Sharan
- Dept. of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania, 19107, USA
| | - Diego Slezak
- Dept. of Computer Science, University of Buenos Aires, Buenos Aires, Argentina
| | - Gregory Worrell
- Dept. of Neurology, Mayo Systems Electrophysiology Laboratory (MSEL), USA
- Dept. of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA
| | - Jerome Engel
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Dept. of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Dept. of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | - Michael R. Sperling
- Depts. of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, 19107, USA
| | - Richard J Staba
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
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Comparison of Qualitative and Quantitative Analyses of MR-Arterial Spin Labeling Perfusion Data for the Assessment of Pediatric Patients with Focal Epilepsies. Diagnostics (Basel) 2022; 12:diagnostics12040811. [PMID: 35453858 PMCID: PMC9032819 DOI: 10.3390/diagnostics12040811] [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: 02/17/2022] [Revised: 03/17/2022] [Accepted: 03/23/2022] [Indexed: 12/07/2022] Open
Abstract
The role of MR Arterial-Spin-Labeling Cerebral Blood Flow maps (ASL-CBF) in the assessment of pediatric focal epilepsy is still debated. We aim to compare the Seizure Onset Zone (SOZ) detection rate of three methods of evaluation of ASL-CBF: 1) qualitative visual (qCBF), 2) z-score voxel-based quantitative analysis of index of asymmetry (AI-CBF), and 3) z-score voxel-based cluster analysis of the quantitative difference of patient’s CBF from the normative data of an age-matched healthy population (cCBF). Interictal ASL-CBF were acquired in 65 pediatric patients with focal epilepsy: 26 with focal brain lesions and 39 with a normal MRI. All hypoperfusion areas visible in at least 3 contiguous images of qCBF analysis were identified. In the quantitative evaluations, clusters with a significant z-score AI-CBF ≤ −1.64 and areas with a z-score cCBF ≤ −1.64 were considered potentially related to the SOZ. These areas were compared with the SOZ defined by the anatomo-electro-clinical data. In patients with a positive MRI, SOZ was correctly identified in 27% of patients using qCBF, 73% using AI-CBF, and 77% using cCBF. In negative MRI patients, SOZ was identified in 18% of patients using qCBF, in 46% using AI-CBF, and in 64% using cCBF (p < 0.001). Quantitative analyses of ASL-CBF maps increase the detection rate of SOZ compared to the qualitative method, principally in negative MRI patients.
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Lehongre K, Lambrecq V, Whitmarsh S, Frazzini V, Cousyn L, Soleil D, Fernandez-Vidal S, Mathon B, Houot M, Lemarechal JD, Clemenceau S, Hasboun D, Adam C, Navarro V. Long-term deep intracerebral microelectrode recordings in patients with drug-resistant epilepsy: proposed guidelines based on 10-year experience. Neuroimage 2022; 254:119116. [PMID: 35318150 DOI: 10.1016/j.neuroimage.2022.119116] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 02/23/2022] [Accepted: 03/15/2022] [Indexed: 02/08/2023] Open
Abstract
PURPOSE Human neuronal activity, recorded in vivo from microelectrodes, may offer valuable insights into physiological mechanisms underlying human cognition and pathophysiological mechanisms of brain diseases, in particular epilepsy. Continuous and long-term recordings are necessary to monitor non predictable pathological and physiological activities like seizures or sleep. Because of their high impedance, microelectrodes are more sensitive to noise than macroelectrodes. Low noise levels are crucial to detect action potentials from background noise, and to further isolate single neuron activities. Therefore, long-term recordings of multi-unit activity remains a challenge. We shared here our experience with microelectrode recordings and our efforts to reduce noise levels in order to improve signal quality. We also provided detailed technical guidelines for the connection, recording, imaging and signal analysis of microelectrode recordings. RESULTS During the last 10 years, we implanted 122 bundles of Behnke-Fried hybrid macro-microelectrodes, in 56 patients with pharmacoresistant focal epilepsy. Microbundles were implanted in the temporal lobe (74%), as well as frontal (15%), parietal (6%) and occipital (5%) lobes. Low noise levels depended on our technical setup. The noise reduction was mainly obtained after electrical insulation of the patient's recording room and the use of a reinforced microelectrode model, reaching median root mean square values of 5.8 µV. Seventy percent of the bundles could record multi-units activities (MUA), on around 3 out of 8 wires per bundle and for an average of 12 days. Seizures were recorded by microelectrodes in 91% of patients, when recorded continuously, and MUA were recorded during seizures for 75 % of the patients after the insulation of the room. Technical guidelines are proposed for (i) electrode tails manipulation and protection during surgical bandage and connection to both clinical and research amplifiers, (ii) electrical insulation of the patient's recording room and shielding, (iii) data acquisition and storage, and (iv) single-units activities analysis. CONCLUSIONS We progressively improved our recording setup and are now able to record (i) microelectrode signals with low noise level up to 3 weeks duration, and (ii) MUA from an increased number of wires . We built a step by step procedure from electrode trajectory planning to recordings. All these delicate steps are essential for continuous long-term recording of units in order to advance in our understanding of both the pathophysiology of ictogenesis and the neuronal coding of cognitive and physiological functions.
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Affiliation(s)
- Katia Lehongre
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau, ICM, INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, Paris France
| | - Virginie Lambrecq
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau, ICM, INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, Paris France; AP-HP, Département de Neurophysiologie, Hôpital Pitié-Salpêtrière, DMU Neurosciences, Paris, France; AP-HP, Epilepsy Unit, Pitié-Salpêtrière Hospital, DMU Neurosciences, Paris, France
| | - Stephen Whitmarsh
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau, ICM, INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, Paris France
| | - Valerio Frazzini
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau, ICM, INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, Paris France; AP-HP, Département de Neurophysiologie, Hôpital Pitié-Salpêtrière, DMU Neurosciences, Paris, France; AP-HP, Epilepsy Unit, Pitié-Salpêtrière Hospital, DMU Neurosciences, Paris, France
| | - Louis Cousyn
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau, ICM, INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, Paris France; AP-HP, Epilepsy Unit, Pitié-Salpêtrière Hospital, DMU Neurosciences, Paris, France
| | - Daniel Soleil
- Bureau d'Etudes CEMS, 801 Route d'Eyguieres, 13 560 Senas, France
| | - Sara Fernandez-Vidal
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau, ICM, INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, Paris France
| | - Bertrand Mathon
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau, ICM, INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, Paris France; AP-HP, Service de Neurochirurgie, Hôpital Pitié-Salpêtrière, Paris, France
| | - Marion Houot
- Centre of Excellence of Neurodegenerative Disease (CoEN), AP-HP, Pitié-Salpêtrière Hospital, Paris, France; Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, AP-HP, Pitié-Salpêtrière Hospital, Paris, France.; Clinical Investigation Centre, Institut du Cerveau et de la Moelle épinière (ICM), Pitié-Salpêtrière Hospital Paris, France
| | - Jean-Didier Lemarechal
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau, ICM, INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, Paris France; Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
| | | | - Dominique Hasboun
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau, ICM, INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, Paris France; AP-HP, Service de Neuroradiologie, Pitié-Salpêtrière Hospital, Paris, France
| | - Claude Adam
- AP-HP, Epilepsy Unit, Pitié-Salpêtrière Hospital, DMU Neurosciences, Paris, France
| | - Vincent Navarro
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau, ICM, INSERM, CNRS, APHP, Pitié-Salpêtrière Hospital, Paris France; AP-HP, Département de Neurophysiologie, Hôpital Pitié-Salpêtrière, DMU Neurosciences, Paris, France; AP-HP, Epilepsy Unit, Pitié-Salpêtrière Hospital, DMU Neurosciences, Paris, France; AP-HP, Center of Reference for Rare Epilepsies, Pitié-Salpêtrière Hospital, Paris, France.
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Hou J, Zhu H, Xiao L, Zhao CW, Liao G, Tang Y, Feng L. Alterations in Cortical-Subcortical Metabolism in Temporal Lobe Epilepsy With Impaired Awareness Seizures. Front Aging Neurosci 2022; 14:849774. [PMID: 35360210 PMCID: PMC8961434 DOI: 10.3389/fnagi.2022.849774] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 01/26/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveThe features of cerebral metabolism associated with loss of consciousness in patients with temporal lobe epilepsy (TLE) have not been fully elucidated. We aim to investigate the alterations in cortical-subcortical metabolism in temporal lobe epilepsy with impaired awareness seizures (IAS).MethodsRegional cerebral metabolism was measured using fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG PET) in patients with TLE-IAS and healthy controls. All patients had a comprehensive evaluation to confirm their seizure origin and lateralization. Videos of all seizures were viewed and rated by at least two epileptologists to identify the state of consciousness when a seizure occurred. By synthesizing the seizure history, semeiology, and video EEG of all patients, as long as the patients had one seizure with impaired awareness, she/he will be included. 76 patients with TLE-IAS and 60 age-matched healthy controls were enrolled in this study. Regional cerebral metabolic patterns were analyzed for TLE-IAS and healthy control groups using statistical parametric mapping. Besides, we compared the MRI-negative patients and MRI-positive patients with healthy controls, respectively.ResultsThere were no significant differences in the age and sex of TLE-IAS patients and healthy control. TLE-IAS patients showed extensive bilateral hypermetabolism in the frontoparietal regions, cingulate gyrus, corpus callosum, occipital lobes, basal ganglia, thalamus, brainstem, and cerebellum. The region of metabolic change was more extensive in right TLE-IAS than that of the left, including extensive hypometabolism in the ipsilateral temporal, frontal, parietal, and insular lobes. And contralateral temporal lobe, bilateral frontoparietal regions, occipital lobes, the anterior and posterior regions of the cingulate gyrus, bilateral thalamus, bilateral basal ganglia, brainstem, and bilateral cerebellum showed hypermetabolism. The TLE patients with impaired awareness seizure showed hypermetabolism in the cortical-subcortical network including the arousal system. Additionally, 48 MRI-positive and 28 MRI-negative TLE-IAS patients were included in our study. TLE-IAS patients with MRI-negative and MRI-positive were both showed hypermetabolism in the cingulate gyrus. Hypometabolism in the bilateral temporal lobe was showed in the TLE-IAS with MRI-positive.ConclusionThese findings suggested that the repetitive consciousness impairing ictal events may have an accumulative effect on brain metabolism, resulting in abnormal interictal cortical-subcortical metabolic disturbance in TLE patients with impaired awareness seizure. Understanding these metabolic mechanisms may guide future clinical treatments to prevent seizure-related awareness deficits and improve quality of life in people with TLE.
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Affiliation(s)
- Jiale Hou
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Haoyue Zhu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Ling Xiao
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
| | | | - Guang Liao
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
| | - Yongxiang Tang
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Yongxiang Tang,
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders (XIANGYA), Xiangya Hospital, Central South University, Changsha, China
- Li Feng,
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Zhang C, Liu W, Zhang J, Zhang X, Huang P, Sun B, Zhan S, Cao C. Utility of magnetoencephalography combined with stereo-electroencephalography in resective epilepsy surgery: a 2-year follow-up. Seizure 2022; 97:94-101. [DOI: 10.1016/j.seizure.2022.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 03/14/2022] [Accepted: 03/16/2022] [Indexed: 11/25/2022] Open
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Papadelis C, Conrad SE, Song Y, Shandley S, Hansen D, Bosemani M, Malik S, Keator C, Perry MS. Case Report: Laser Ablation Guided by State of the Art Source Imaging Ends an Adolescent's 16-Year Quest for Seizure Freedom. Front Hum Neurosci 2022; 16:826139. [PMID: 35145387 PMCID: PMC8821813 DOI: 10.3389/fnhum.2022.826139] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/03/2022] [Indexed: 01/14/2023] Open
Abstract
Epilepsy surgery is the most effective therapeutic approach for children with drug resistant epilepsy (DRE). Recent advances in neurosurgery, such as the Laser Interstitial Thermal Therapy (LITT), improved the safety and non-invasiveness of this method. Electric and magnetic source imaging (ESI/MSI) plays critical role in the delineation of the epileptogenic focus during the presurgical evaluation of children with DRE. Yet, they are currently underutilized even in tertiary epilepsy centers. Here, we present a case of an adolescent who suffered from DRE for 16 years and underwent surgery at Cook Children's Medical Center (CCMC). The patient was previously evaluated in a level 4 epilepsy center and treated with multiple antiseizure medications for several years. Presurgical evaluation at CCMC included long-term video electroencephalography (EEG), magnetoencephalography (MEG) with simultaneous conventional EEG (19 channels) and high-density EEG (256 channels) in two consecutive sessions, MRI, and fluorodeoxyglucose - positron emission tomography (FDG-PET). Video long-term EEG captured nine focal-onset clinical seizures with a maximal evolution over the right frontal/frontal midline areas. MRI was initially interpreted as non-lesional. FDG-PET revealed a small region of hypometabolism at the anterior right superior temporal gyrus. ESI and MSI performed with dipole clustering showed a tight cluster of dipoles in the right anterior insula. The patient underwent intracranial EEG which indicated the right anterior insular as seizure onset zone. Eventually LITT rendered the patient seizure free (Engel 1; 12 months after surgery). Retrospective analysis of ESI and MSI clustered dipoles found a mean distance of dipoles from the ablated volume ranging from 10 to 25 mm. Our findings highlight the importance of recent technological advances in the presurgical evaluation and surgical treatment of children with DRE, and the underutilization of epilepsy surgery in children with DRE.
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Affiliation(s)
- Christos Papadelis
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
- School of Medicine, Texas Christian University, University of North Texas Health Science Center, Fort Worth, TX, United States
- *Correspondence: Christos Papadelis orcid.org/0000-0001-6125-9217
| | - Shannon E. Conrad
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
| | - Yanlong Song
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
| | - Sabrina Shandley
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
| | - Daniel Hansen
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
| | - Madhan Bosemani
- Department of Radiology, Cook Children's Medical Center, Fort Worth, TX, United States
| | - Saleem Malik
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
| | - Cynthia Keator
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
| | - M. Scott Perry
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
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Kong Y, Cheng N, Dang N, Hu XB, Zhang GQ, Dong YW, Wang X, Gao JY. Application of combined multimodal neuroimaging and video-electroencephalography in intractable epilepsy patients for improved post-surgical outcome prediction. Clin Radiol 2022; 77:e250-e259. [PMID: 35000762 DOI: 10.1016/j.crad.2021.12.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 12/02/2021] [Indexed: 11/25/2022]
Abstract
AIM To investigate the ability of a multidisciplinary approach that combines multimodal neuroimaging with video-electroencephalography (v-EEG) to predict post-surgical outcomes in patients with intractable epilepsy, and explore prognostic predictors for these patients. MATERIALS AND METHODS Fifty-eight patients with intractable epilepsy who underwent surgery between March 2016 and October 2019 were reviewed retrospectively. Demographic, clinical, v-EEG, neuroimaging, surgical, and regular follow-up seizure outcome data were collected. Forty-six patients with a follow-up of at least 12 months were graded by Engel scores. Univariate and multivariate analyses were applied to explore prognostic factors that could predict post-surgical seizure outcomes. RESULTS Of the 58 patients, 28 were males. The median age was 27 years, the median age at first seizure was 11 years, and the median duration of seizures was 10 years. The Kaplan-Meier log-rank test showed that regardless of whether the follow-up duration was considered, epilepsy type, v-EEG, PET/CT, image post-processing methods, and a multidisciplinary approach that combined multimodal imaging with v-EEG were all correlated with seizure outcomes. Multivariate analysis found that the multidisciplinary approach was an independent predictor of post-surgical outcomes in patients with intractable epilepsy (hazard ratio = 11.400, 95% confidence interval = 2.249-57.787, p=0.003). CONCLUSIONS The present study showed that the multidisciplinary approach could provide independent prognostic information for patients with intractable epilepsy undergoing surgery. This approach has strong potential for the easier selection of patients to undergo surgical treatment and accurate prognostication.
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Affiliation(s)
- Y Kong
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China.
| | - N Cheng
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - N Dang
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - X-B Hu
- MRI Unit of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - G-Q Zhang
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - Y-W Dong
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - X Wang
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - J-Y Gao
- PET/CT Center of Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
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Li T, Niu S, Qiu X, Zhai Z, Yang L, Chen L, Zhang XM. Altered Cerebral Blood Flow is Linked to Disease Duration in Patients with Generalized tonic‒clonic Seizures. Neuropsychiatr Dis Treat 2022; 18:2649-2659. [PMID: 36387946 PMCID: PMC9662018 DOI: 10.2147/ndt.s386509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 10/29/2022] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To investigate cerebral blood flow (CBF) characteristics in individuals with generalized tonic‒clonic seizures (GTCS) during the interictal phase using voxel-based analysis of 3D pseudocontinuous arterial spin labeling (PCASL). PATIENTS AND METHODS Patients with GTCS (GTCS group) (during the interictal period) and healthy volunteers (control group) underwent head MR imaging with a 3.0T MR scanner with a 3D PCASL sequence. CBF was compared between the two groups. Spearman correlations of CBF in regions of interest (ROIs) in GTCS patients with the duration of disease and age of onset were analyzed and corrected using the false discovery rate (FDR). RESULTS Twenty patients with GTCS (GTCS group) and twenty healthy volunteers (control group) were recruited for this study. On 3D PCASL, (1) GTCS patients had lower CBF in the brainstem, right cerebellum, right inferior temporal gyrus, parahippocampal gyrus, superior frontal gyrus, middle frontal gyrus, triangular part of inferior frontal gyrus, left temporal pole of superior temporal gyrus and thalamus and had higher CBF in the bilateral superior parietal gyri, precuneus, precentral gyri, postcentral gyri, and left dorsolateral superior frontal gyrus than controls. (2) The CBF of the right temporal pole of the middle temporal gyrus was negatively correlated with the duration of disease (PFDRcorrected<0.05), with a correlation coefficient r of -0.7333 and a PFDRcorrected value of 0.04. CONCLUSION Voxel-based analysis of 3D PCASL imaging can be used to sensitively detect brain perfusion differences in GTCS patients. The decrease in CBF in the right temporal pole of the middle temporal gyrus may be associated with disease onset. These findings may offer new perspectives on the pathogenesis of GTCS and the underlying pathophysiological changes associated with perfusion.
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Affiliation(s)
- Ting Li
- The First Affiliated Hospital, Jinan University, Guangzhou, People's Republic of China.,Medical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
| | - Shaowei Niu
- Department of Infection, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
| | - Xiang Qiu
- Department of Radiology, Integrated TCM & Western Medicine Hospital Affiliated to Chengdu University of TCM, Chengdu First People's Hospital, Chengdu, People's Republic of China
| | - Zhaohua Zhai
- Medical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
| | - Lin Yang
- Medical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
| | - Li Chen
- Medical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
| | - Xiao Ming Zhang
- The First Affiliated Hospital, Jinan University, Guangzhou, People's Republic of China.,Medical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
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63
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Frazzini V, Cousyn L, Navarro V. Semiology, EEG, and neuroimaging findings in temporal lobe epilepsies. HANDBOOK OF CLINICAL NEUROLOGY 2022; 187:489-518. [PMID: 35964989 DOI: 10.1016/b978-0-12-823493-8.00021-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. First descriptions of TLE date back in time and detailed portraits of epileptic seizures of temporal origin can be found in early medical reports as well as in the works of various artists and dramatists. Depending on the seizure onset zone, several subtypes of TLE have been identified, each one associated with peculiar ictal semiology. TLE can result from multiple etiological causes, ranging from genetic to lesional ones. While the diagnosis of TLE relies on detailed analysis of clinical as well as electroencephalographic (EEG) features, the lesions responsible for seizure generation can be highlighted by multiple brain imaging modalities or, in selected cases, by genetic investigations. TLE is the most common cause of refractory epilepsy and despite the great advances in diagnostic tools, no lesion is found in around one-third of patients. Surgical treatment is a safe and effective option, requiring presurgical investigations to accurately identify the seizure onset zone (SOZ). In selected cases, presurgical investigations need intracerebral investigations (such as stereoelectroencephalography) or dedicated metabolic imaging techniques (interictal PET and ictal SPECT) to correctly identify the brain structures to be removed.
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Affiliation(s)
- Valerio Frazzini
- AP-HP, Department of Neurology and Department of Clinical Neurophysiology, Epilepsy and EEG Unit, Reference Center for Rare Epilepsies, Pitié-Salpêtrière Hospital, Paris, France; Sorbonne Université, Paris Brain Institute, Team "Dynamics of Neuronal Networks and Neuronal Excitability", Paris, France
| | - Louis Cousyn
- AP-HP, Department of Neurology and Department of Clinical Neurophysiology, Epilepsy and EEG Unit, Reference Center for Rare Epilepsies, Pitié-Salpêtrière Hospital, Paris, France; Sorbonne Université, Paris Brain Institute, Team "Dynamics of Neuronal Networks and Neuronal Excitability", Paris, France
| | - Vincent Navarro
- AP-HP, Department of Neurology and Department of Clinical Neurophysiology, Epilepsy and EEG Unit, Reference Center for Rare Epilepsies, Pitié-Salpêtrière Hospital, Paris, France; Sorbonne Université, Paris Brain Institute, Team "Dynamics of Neuronal Networks and Neuronal Excitability", Paris, France.
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64
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Fan JM, Lee AT, Kudo K, Ranasinghe KG, Morise H, Findlay AM, Kirsch HE, Chang EF, Nagarajan SS, Rao VR. Network connectivity predicts effectiveness of responsive neurostimulation in focal epilepsy. Brain Commun 2022; 4:fcac104. [PMID: 35611310 PMCID: PMC9123848 DOI: 10.1093/braincomms/fcac104] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/23/2022] [Accepted: 04/21/2022] [Indexed: 11/13/2022] Open
Abstract
Responsive neurostimulation is a promising treatment for drug-resistant focal epilepsy; however, clinical outcomes are highly variable across individuals. The therapeutic mechanism of responsive neurostimulation likely involves modulatory effects on brain networks; however, with no known biomarkers that predict clinical response, patient selection remains empiric. This study aimed to determine whether functional brain connectivity measured non-invasively prior to device implantation predicts clinical response to responsive neurostimulation therapy. Resting-state magnetoencephalography was obtained in 31 participants with subsequent responsive neurostimulation device implantation between 15 August 2014 and 1 October 2020. Functional connectivity was computed across multiple spatial scales (global, hemispheric, and lobar) using pre-implantation magnetoencephalography and normalized to maps of healthy controls. Normalized functional connectivity was investigated as a predictor of clinical response, defined as percent change in self-reported seizure frequency in the most recent year of clinic visits relative to pre-responsive neurostimulation baseline. Area under the receiver operating characteristic curve quantified the performance of functional connectivity in predicting responders (≥50% reduction in seizure frequency) and non-responders (<50%). Leave-one-out cross-validation was furthermore performed to characterize model performance. The relationship between seizure frequency reduction and frequency-specific functional connectivity was further assessed as a continuous measure. Across participants, stimulation was enabled for a median duration of 52.2 (interquartile range, 27.0-62.3) months. Demographics, seizure characteristics, and responsive neurostimulation lead configurations were matched across 22 responders and 9 non-responders. Global functional connectivity in the alpha and beta bands were lower in non-responders as compared with responders (alpha, pfdr < 0.001; beta, pfdr < 0.001). The classification of responsive neurostimulation outcome was improved by combining feature inputs; the best model incorporated four features (i.e. mean and dispersion of alpha and beta bands) and yielded an area under the receiver operating characteristic curve of 0.970 (0.919-1.00). The leave-one-out cross-validation analysis of this four-feature model yielded a sensitivity of 86.3%, specificity of 77.8%, positive predictive value of 90.5%, and negative predictive value of 70%. Global functional connectivity in alpha band correlated with seizure frequency reduction (alpha, P = 0.010). Global functional connectivity predicted responder status more strongly, as compared with hemispheric predictors. Lobar functional connectivity was not a predictor. These findings suggest that non-invasive functional connectivity may be a candidate personalized biomarker that has the potential to predict responsive neurostimulation effectiveness and to identify patients most likely to benefit from responsive neurostimulation therapy. Follow-up large-cohort, prospective studies are required to validate this biomarker. These findings furthermore support an emerging view that the therapeutic mechanism of responsive neurostimulation involves network-level effects in the brain.
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Affiliation(s)
- Joline M Fan
- Department of Neurology and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Anthony T Lee
- Department of Neurosurgery, University of California San Francisco, San Francisco, CA, USA
| | - Kiwamu Kudo
- Medical Imaging Center, Ricoh Company, Ltd., Kanazawa, Japan.,Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Kamalini G Ranasinghe
- Department of Neurology and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Hirofumi Morise
- Medical Imaging Center, Ricoh Company, Ltd., Kanazawa, Japan.,Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Anne M Findlay
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Heidi E Kirsch
- Department of Neurology and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.,Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Edward F Chang
- Department of Neurosurgery, University of California San Francisco, San Francisco, CA, USA
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
| | - Vikram R Rao
- Department of Neurology and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
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65
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Hoogteijling S, Zijlmans M. Deep learning for epileptogenic zone delineation from the invasive EEG: challenges and lookouts. Brain Commun 2021; 4:fcab307. [PMID: 35169704 PMCID: PMC8833315 DOI: 10.1093/braincomms/fcab307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 11/26/2021] [Accepted: 12/24/2021] [Indexed: 11/24/2022] Open
Abstract
This scientific commentary refers to 'Refining epileptogenic high-frequency oscillations using deep learning: a reverse engineering approach' by Zhang et al. (https://doi.org/10.1093/braincomms/fcab267).
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Affiliation(s)
- Sem Hoogteijling
- Department of Neurology and Neurosurgery, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands
- Technical Medicine, University of Twente, Enschede, The Netherlands
| | - Maeike Zijlmans
- Department of Neurology and Neurosurgery, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands
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Yuan J, Ran X, Liu K, Yao C, Yao Y, Wu H, Liu Q. Machine learning applications on neuroimaging for diagnosis and prognosis of epilepsy: A review. J Neurosci Methods 2021; 368:109441. [PMID: 34942271 DOI: 10.1016/j.jneumeth.2021.109441] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 10/23/2021] [Accepted: 12/11/2021] [Indexed: 02/07/2023]
Abstract
Machine learning is playing an increasingly important role in medical image analysis, spawning new advances in the clinical application of neuroimaging. There have been some reviews on machine learning and epilepsy before, and they mainly focused on electrophysiological signals such as electroencephalography (EEG) and stereo electroencephalography (SEEG), while neglecting the potential of neuroimaging in epilepsy research. Neuroimaging has its important advantages in confirming the range of the epileptic region, which is essential in presurgical evaluation and assessment after surgery. However, it is difficult for EEG to locate the accurate epilepsy lesion region in the brain. In this review, we emphasize the interaction between neuroimaging and machine learning in the context of epilepsy diagnosis and prognosis. We start with an overview of epilepsy and typical neuroimaging modalities used in epilepsy clinics, MRI, DWI, fMRI, and PET. Then, we elaborate two approaches in applying machine learning methods to neuroimaging data: (i) the conventional machine learning approach combining manual feature engineering and classifiers, (ii) the deep learning approach, such as the convolutional neural networks and autoencoders. Subsequently, the application of machine learning on epilepsy neuroimaging, such as segmentation, localization, and lateralization tasks, as well as tasks directly related to diagnosis and prognosis are looked into in detail. Finally, we discuss the current achievements, challenges, and potential future directions in this field, hoping to pave the way for computer-aided diagnosis and prognosis of epilepsy.
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Affiliation(s)
- Jie Yuan
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China
| | - Xuming Ran
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China
| | - Keyin Liu
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China
| | - Chen Yao
- Shenzhen Second People's Hospital, Shenzhen 518035, PR China
| | - Yi Yao
- Shenzhen Children's Hospital, Shenzhen 518017, PR China
| | - Haiyan Wu
- Centre for Cognitive and Brain Sciences and Department of Psychology, University of Macau, Taipa, Macau
| | - Quanying Liu
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China.
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Parasuram H, Gopinath S, Pillai A, Diwakar S, Kumar A. Quantification of Epileptogenic Network From Stereo EEG Recordings Using Epileptogenicity Ranking Method. Front Neurol 2021; 12:738111. [PMID: 34803883 PMCID: PMC8595106 DOI: 10.3389/fneur.2021.738111] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 08/31/2021] [Indexed: 11/13/2022] Open
Abstract
Introduction: Precise localization of the epileptogenic zone is very essential for the success of epilepsy surgery. Epileptogenicity index (EI) computationally estimates epileptogenicity of brain structures based on the temporal domain parameters and magnitude of ictal discharges. This method works well in cases of mesial temporal lobe epilepsy but it showed reduced accuracy in neocortical epilepsy. To overcome this scenario, in this study, we propose Epileptogenicity Rank (ER), a modified method of EI for quantifying epileptogenicity, that is based on spatio-temporal properties of Stereo EEG (SEEG). Methods: Energy ratio during ictal discharges, the time of involvement and Euclidean distance between brain structures were used to compute the ER. Retrospectively, we localized the EZ for 33 patients (9 for mesial-temporal lobe epilepsy and 24 for neocortical epilepsy) using post op MRI and Engel 1 surgical outcome at a mean of 40.9 months and then optimized the ER in this group. Results: Epileptic network estimation based on ER successfully differentiated brain regions involved in the seizure onset from the propagation network. ER was calculated at multiple thresholds leading to an optimum value that differentiated the seizure onset from the propagation network. We observed that ER < 7.1 could localize the EZ in neocortical epilepsy with a sensitivity of 94.6% and specificity of 98.3% and ER < 7.3 in mesial temporal lobe epilepsy with a sensitivity of 95% and specificity of 98%. In non-seizure-free patients, the EZ localization based on ER pointed to brain area beyond the cortical resections. Significance: Methods like ER can improve the accuracy of EZ localization for brain resection and increase the precision of minimally invasive surgery techniques (radio-frequency or laser ablation) by identifying the epileptic hubs where the lesion is extensive or in nonlesional cases. For inclusivity with other clinical applications, this ER method has to be studied in more patients.
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Affiliation(s)
- Harilal Parasuram
- Amrita Advanced Centre for Epilepsy (AACE), Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.,Department of Neurology, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.,Amrita Mind Brain Center, Amrita Vishwa Vidyapeetham, Kollam, India
| | - Siby Gopinath
- Amrita Advanced Centre for Epilepsy (AACE), Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.,Department of Neurology, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.,Amrita Mind Brain Center, Amrita Vishwa Vidyapeetham, Kollam, India
| | - Ashok Pillai
- Amrita Advanced Centre for Epilepsy (AACE), Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.,Department of Neurosurgery, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India
| | - Shyam Diwakar
- Amrita Mind Brain Center, Amrita Vishwa Vidyapeetham, Kollam, India
| | - Anand Kumar
- Department of Neurology, Amrita Institute of Medical Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.,Amrita Mind Brain Center, Amrita Vishwa Vidyapeetham, Kollam, India
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68
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Carboni M, Brunet D, Seeber M, Michel CM, Vulliemoz S, Vorderwülbecke BJ. Linear distributed inverse solutions for interictal EEG source localisation. Clin Neurophysiol 2021; 133:58-67. [PMID: 34801964 DOI: 10.1016/j.clinph.2021.10.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 09/27/2021] [Accepted: 10/09/2021] [Indexed: 01/09/2023]
Abstract
OBJECTIVE To compare the spatial accuracy of 6 linear distributed inverse solutions for EEG source localisation of interictal epileptic discharges: Minimum Norm, Weighted Minimum Norm, Low-Resolution Electromagnetic Tomography (LORETA), Local Autoregressive Average (LAURA), Standardised LORETA, and Exact LORETA. METHODS Spatial accuracy was assessed clinically by retrospectively comparing the maximum source of averaged interictal discharges to the resected brain area in 30 patients with successful epilepsy surgery, based on 204-channel EEG. Additionally, localisation errors of the inverse solutions were assessed in computer simulations, with different levels of noise added to the signal in both sensor space and source space. RESULTS In the clinical evaluations, the source maximum was located inside the resected brain area in 50-57% of patients when using LORETA or LAURA, while all other inverse solutions performed significantly worse (17-30%; corrected p < 0.01). In the simulation studies, when noise levels exceeded 10%, LORETA and LAURA had substantially smaller localisation errors than the other inverse solutions. CONCLUSIONS LORETA and LAURA provided the highest spatial accuracy both in clinical and simulated data, alongside with a comparably high robustness towards noise. SIGNIFICANCE Among the different linear inverse solution algorithms tested, LORETA and LAURA might be preferred for interictal EEG source localisation.
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Affiliation(s)
- Margherita Carboni
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland
| | - Denis Brunet
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland
| | - Martin Seeber
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland
| | - Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Epilepsy-Center Berlin-Brandenburg, Department of Neurology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
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Li X, Gao Z, Ma ML, Li L, Guo S. Identification of serum miR-378 and miR-575 as diagnostic indicators and predicting surgical prognosis in human epilepsy. J Med Biochem 2021; 41:184-190. [PMID: 35510204 PMCID: PMC9010044 DOI: 10.5937/jomb0-32988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/23/2021] [Indexed: 11/15/2022] Open
Abstract
Background Epilepsy (EP) is a common neurological disorder which is characterized by excessive abnormal synchronization of neuronal discharges in the brain due to chronic recurrent seizures of multiple etiologies. Variety of microRNAs have been associated with the occurrence and development of EP. This study aimed to determine the aberrant expression of miR-378 and miR-575 in EP patients to validate their potential to distinguish EP from healthy patients. Methods RT-qPCR was used to determine the expressions of miR-378 and miR-575 from serum specimens of 106 EP and 103 control individuals. Clinical indicators between EP patients and controls were assessed. Based on surgical outcome, EP patients were further divided into Engel I-IV EP. The potentials of miR-378 and miR-575 in discriminating EP from healthy participants and predicting surgical prognosis were calculated by receiver operating characteristic (ROC) analysis. Results We found the miR-378 and miR-575 were significantly declined (P<0.001) in Engel I-II and III-IV EP patients with no difference in clinical parameters compared. Moreover, miR-378 and miR-575 displayed high sensitivity, specificity, and accuracy in distinguishing EP patients and predicting surgical outcomes. Moreover, after surgical treatment, miR-378 and miR-575 levels were increased compared with those at admission, suggesting their potentials in treatment response. Conclusions miR-378 and miR-575 could be utilized as novel and non-invasive serum biomarkers in discriminating EP from healthy controls and predicting surgical outcome, shedding new insights on epileptogenesis and EP treatment.
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Affiliation(s)
- Xiuxiu Li
- Linyi Central Hospital, Department of Neurology, Linyi City, Shandong Province, China
| | - Zhiqing Gao
- Linyi Central Hospital, Department of Neurology, Linyi City, Shandong Province, China
| | - Mei Ling Ma
- Linyi Central Hospital, Department of Neurology, Linyi City, Shandong Province, China
| | - Li Li
- Linyi Central Hospital, Department of Neurology, Linyi City, Shandong Province, China
| | - Shifeng Guo
- Linyi Central Hospital, Department of Neurology, Linyi City, Shandong Province, China
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70
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Sinha N, Davis KA. Mapping Epileptogenic Tissues in MRI-Negative Focal Epilepsy: Can Deep Learning Uncover Hidden Lesions? Neurology 2021; 97:754-755. [PMID: 34521690 DOI: 10.1212/wnl.0000000000012696] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Nishant Sinha
- From the Department of Neurology (N.S., K.A.D.) and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia.
| | - Kathryn Adamiak Davis
- From the Department of Neurology (N.S., K.A.D.) and Center for Neuroengineering and Therapeutics (N.S., K.A.D.), University of Pennsylvania, Philadelphia
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71
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Cheng L, Xing Y, Zhang H, Liu R, Lai H, Piao Y, Wang W, Yan X, Li X, Wang J, Li D, Loh HH, Yu T, Zhang G, Yang X. Mechanistic Analysis of Micro-Neurocircuits Underlying the Epileptogenic Zone in Focal Cortical Dysplasia Patients. Cereb Cortex 2021; 32:2216-2230. [PMID: 34664065 DOI: 10.1093/cercor/bhab350] [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: 06/13/2021] [Revised: 08/22/2021] [Accepted: 08/23/2021] [Indexed: 11/13/2022] Open
Abstract
We aim to explore the microscopic neurophysiology of focal cortical dysplasia (FCD) induced epileptogenesis in specific macroscopic brain regions, therefore mapping a micro-macro neuronal network that potentially indicates the epileptogenic mechanism. Epileptic and relatively non-epileptic temporal neocortex specimens were resected from FCD and mesial temporal lobe epilepsy (mTLE) patients, respectively. Whole-cell patch-clamping was performed on cells from the seizure onset zone (SOZ) and non-SOZ inside the epileptogenic zone (EZ) of FCD patients, as well as the non-epileptic neocortex of mTLE patients. Microscopic data were recorded, including membrane characteristics, spontaneous synaptic activities, and evoked action potentials. Immunohistochemistry was also performed on parvalbumin-positive (PV+) interneurons. We found that SOZ interneurons exhibited abnormal neuronal expression and distribution as well as reduced overall function compared with non-SOZ and mTLE interneurons. The SOZ pyramidal cells experienced higher excitation but lower inhibition than the mTLE controls, whereas the non-SOZ pyramidal cells exhibited intermediate excitability. Action potential properties of both types of neurons also suggested more synchronized neuronal activity inside the EZ, particularly inside the SOZ. Together, our research provides evidence for a potential neurocircuit underlying SOZ epileptogenesis and non-SOZ seizure susceptibility. Further investigation of this microscopic network may promote understanding of the mechanism of FCD-induced epileptogenesis.
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Affiliation(s)
- Lipeng Cheng
- Center of Epilepsy, Beijing Institute of Brain Disorders, Capital Medical University, Beijing 100069, China.,Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China.,Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Yue Xing
- Center of Epilepsy, Beijing Institute of Brain Disorders, Capital Medical University, Beijing 100069, China.,Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China.,Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Herui Zhang
- Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China
| | - Ru Liu
- Center of Epilepsy, Beijing Institute of Brain Disorders, Capital Medical University, Beijing 100069, China.,Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China.,Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Huanling Lai
- Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China
| | - Yueshan Piao
- Department of Pathology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Wei Wang
- Center of Epilepsy, Beijing Institute of Brain Disorders, Capital Medical University, Beijing 100069, China.,Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China.,Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Xiaoming Yan
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Xiaonan Li
- Center of Epilepsy, Beijing Institute of Brain Disorders, Capital Medical University, Beijing 100069, China.,Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China.,Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Jiaoyang Wang
- Center of Epilepsy, Beijing Institute of Brain Disorders, Capital Medical University, Beijing 100069, China.,Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China.,Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Donghong Li
- Center of Epilepsy, Beijing Institute of Brain Disorders, Capital Medical University, Beijing 100069, China.,Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China.,Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.,Department of Neurology, The Third Affiliated Hospital of Sun Yat-sen University, Guangdong 510635, China
| | - Horace H Loh
- Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China
| | - Tao Yu
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Guojun Zhang
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.,Functional Neurosurgery Department, Beijing Children's Hospital, Capital Medical University, Beijing 100045, China
| | - Xiaofeng Yang
- Center of Epilepsy, Beijing Institute of Brain Disorders, Capital Medical University, Beijing 100069, China.,Fundamental Research Department, Guangzhou Laboratory, Guangzhou 510700, China.,Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
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72
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Vorderwülbecke BJ, Baroumand AG, Spinelli L, Seeck M, van Mierlo P, Vulliémoz S. Automated interictal source localisation based on high-density EEG. Seizure 2021; 92:244-251. [PMID: 34626920 DOI: 10.1016/j.seizure.2021.09.020] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 09/25/2021] [Accepted: 09/29/2021] [Indexed: 11/26/2022] Open
Abstract
PURPOSE To study the accuracy of automated interictal EEG source localisation based on high-density EEG, and to compare it to low-density EEG. METHODS Thirty patients operated for pharmacoresistant focal epilepsy were retrospectively examined. Twelve months after resective brain surgery, 18 were seizure-free or had 'auras' only, while 12 had persistence of disabling seizures. Presurgical 257-channel EEG lasting 3-20 h was down-sampled to 25, 40, and 204 channels for separate analyses. For each electrode setup, interictal spikes were detected, clustered, and averaged automatically before validation by an expert reviewer. An individual 6-layer finite difference head model and the standardised low-resolution electromagnetic tomography were used to localise the maximum source activity of the most prevalent spike. Sublobar concordance with the resected brain area was visually assessed and related to favourable vs. unfavourable postsurgical outcome. RESULTS Depending on the EEG setup, epileptic spikes were detected in 21-24 patients (70-80%). The median number of single spikes per average was 470 (range 17-15,066). Diagnostic sensitivity of EEG source localisation was 58-75%, specificity was 50-67%, and overall accuracy was 55-71%. There were no significant differences between low- and high-density EEG setups with 25 to 257 electrodes. CONCLUSION Automated high-density EEG source localisation provides meaningful information in the majority of cases. With hundreds of single spikes averaged, diagnostic accuracy is similar in high- and low-density EEG. Therefore, low-density EEG may be sufficient for interictal EEG source localisation if high numbers of spikes are available.
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Affiliation(s)
- Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Epilepsy-Center Berlin-Brandenburg, Department of Neurology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
| | - Amir G Baroumand
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium
| | - Laurent Spinelli
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland
| | - Pieter van Mierlo
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland
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73
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Nissen IA, Millán AP, Stam CJ, van Straaten ECW, Douw L, Pouwels PJW, Idema S, Baayen JC, Velis D, Van Mieghem P, Hillebrand A. Optimization of epilepsy surgery through virtual resections on individual structural brain networks. Sci Rep 2021; 11:19025. [PMID: 34561483 PMCID: PMC8463605 DOI: 10.1038/s41598-021-98046-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 08/13/2021] [Indexed: 11/10/2022] Open
Abstract
The success of epilepsy surgery in patients with refractory epilepsy depends upon correct identification of the epileptogenic zone (EZ) and an optimal choice of the resection area. In this study we developed individualized computational models based upon structural brain networks to explore the impact of different virtual resections on the propagation of seizures. The propagation of seizures was modelled as an epidemic process [susceptible-infected-recovered (SIR) model] on individual structural networks derived from presurgical diffusion tensor imaging in 19 patients. The candidate connections for the virtual resection were all connections from the clinically hypothesized EZ, from which the seizures were modelled to start, to other brain areas. As a computationally feasible surrogate for the SIR model, we also removed the connections that maximally reduced the eigenvector centrality (EC) (large values indicate network hubs) of the hypothesized EZ, with a large reduction meaning a large effect. The optimal combination of connections to be removed for a maximal effect were found using simulated annealing. For comparison, the same number of connections were removed randomly, or based on measures that quantify the importance of a node or connection within the network. We found that 90% of the effect (defined as reduction of EC of the hypothesized EZ) could already be obtained by removing substantially less than 90% of the connections. Thus, a smaller, optimized, virtual resection achieved almost the same effect as the actual surgery yet at a considerably smaller cost, sparing on average 27.49% (standard deviation: 4.65%) of the connections. Furthermore, the maximally effective connections linked the hypothesized EZ to hubs. Finally, the optimized resection was equally or more effective than removal based on structural network characteristics both regarding reducing the EC of the hypothesized EZ and seizure spreading. The approach of using reduced EC as a surrogate for simulating seizure propagation can suggest more restrictive resection strategies, whilst obtaining an almost optimal effect on reducing seizure propagation, by taking into account the unique topology of individual structural brain networks of patients.
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Affiliation(s)
- Ida A Nissen
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Ana P Millán
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Elisabeth C W van Straaten
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Linda Douw
- Department of Anatomy and Neuroscience, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Petra J W Pouwels
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Sander Idema
- Department of Neurosurgery, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Johannes C Baayen
- Department of Neurosurgery, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Demetrios Velis
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Piet Van Mieghem
- Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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74
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De Stefano P, Carboni M, Marquis R, Spinelli L, Seeck M, Vulliemoz S. Increased delta power as a scalp marker of epileptic activity: a simultaneous scalp and intracranial electroencephalography study. Eur J Neurol 2021; 29:26-35. [PMID: 34528320 PMCID: PMC9293335 DOI: 10.1111/ene.15106] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 09/09/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND PURPOSE The purpose was to evaluate whether intracranial interictal epileptiform discharges (IEDs) that are not visible on the scalp are associated with changes in the frequency spectrum on scalp electroencephalograms (EEGs). METHODS Simultaneous scalp high-density EEG and intracranial EEG recordings were recorded in nine patients undergoing pre-surgical invasive recordings for pharmaco-resistant temporal lobe epilepsy. Epochs with hippocampal IED visible on intracranial EEG (ic-IED) but not on scalp EEG were selected, as well as control epochs without ic-IED. Welch's power spectral density was computed for each scalp electrode and for each subject; the power spectral density was further averaged across the canonical frequency bands and compared between the two conditions with and without ic-IED. For each patient the peak frequency in the delta band (the significantly strongest frequency band in all patients) was determined during periods of ic-IED. The five electrodes showing strongest power at the peak frequency were also determined. RESULTS It was found that intracranial IEDs are associated with an increase in delta power on scalp EEGs, in particular at a frequency ≥1.4 Hz. Electrodes showing slow frequency power changes associated with IEDs were consistent with the hemispheric lateralization of IEDs. Electrodes with maximum power of slow activity were not limited to temporal regions but also involved frontal (bilateral or unilateral) regions. CONCLUSIONS In patients with a clinical picture suggestive of temporal lobe epilepsy, the presence of delta slowing ≥1.4 Hz in anterior temporal regions can represent a scalp marker of hippocampal IEDs. To our best knowledge this is the first study that demonstrates the co-occurrence of ic-IED and increased delta power.
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Affiliation(s)
- Pia De Stefano
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Margherita Carboni
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Renaud Marquis
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Laurent Spinelli
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
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75
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[Imaging in the presurgical evaluation of epilepsy]. DER NERVENARZT 2021; 93:592-598. [PMID: 34491376 PMCID: PMC9200687 DOI: 10.1007/s00115-021-01180-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 06/28/2021] [Indexed: 11/19/2022]
Abstract
Während zwei Drittel der PatientInnen mit Epilepsie durch Medikamente anfallsfrei werden, ist die Erkrankung bei 30 % pharmakoresistent. Bei pharmakoresistenter fokaler Epilepsie bietet die Epilepsiechirurgie eine etwa 65 %ige Chance auf Anfallsfreiheit. Vorab muss der Anfallsfokus exakt eingegrenzt werden, wofür bildgebende Methoden unverzichtbar sind. In den letzten Jahren hat sich in der Prächirurgie der Anteil von PatientInnen mit unauffälliger konventioneller Magnetresonanztomographie (MRT) erhöht. Allerdings konnte die Sensitivität der MRT durch spezielle Aufnahmesequenzen und Techniken der Postprozessierung gesteigert werden. Die Quellenlokalisation des Signals von Elektro- und Magnetenzephalographie (EEG und MEG) verortet den Ursprung iktaler und interiktaler epileptischer Aktivität im Gehirn. Nuklearmedizinische Untersuchungen wie die interiktale Positronen-Emissions-Tomographie (PET) und die iktale Einzelphotonen-Emissionscomputertomographie (SPECT) detektieren chronische oder akute anfallsbezogene Veränderungen des Hirnmetabolismus und können auch bei nichtlokalisierendem MRT auf den epileptogenen Fokus hinweisen. Alle Befunde zusammengenommen werden zur Planung eventueller invasiver EEG-Ableitungen und letztlich der chirurgischen Operation eingesetzt. Konkordante Befunde sind mit besseren chirurgischen Ergebnissen assoziiert und zeigen auch im Langzeitverlauf signifikant höhere Anfallsfreiheitsraten.
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76
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Changes in the Functional Brain Network of Children Undergoing Repeated Epilepsy Surgery: An EEG Source Connectivity Study. Diagnostics (Basel) 2021; 11:diagnostics11071234. [PMID: 34359317 PMCID: PMC8306224 DOI: 10.3390/diagnostics11071234] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 06/29/2021] [Accepted: 07/05/2021] [Indexed: 11/19/2022] Open
Abstract
About 30% of children with drug-resistant epilepsy (DRE) continue to have seizures after epilepsy surgery. Since epilepsy is increasingly conceptualized as a network disorder, understanding how brain regions interact may be critical for planning re-operation in these patients. We aimed to estimate functional brain connectivity using scalp EEG and its evolution over time in patients who had repeated surgery (RS-group, n = 9) and patients who had one successful surgery (seizure-free, SF-group, n = 12). We analyzed EEGs without epileptiform activity at varying time points (before and after each surgery). We estimated functional connectivity between cortical regions and their relative centrality within the network. We compared the pre- and post-surgical centrality of all the non-resected (untouched) regions (far or adjacent to resection) for each group (using the Wilcoxon signed rank test). In alpha, theta, and beta frequency bands, the post-surgical centrality of the untouched cortical regions increased in the SF group (p < 0.001) whereas they decreased (p < 0.05) or did not change (p > 0.05) in the RS group after failed surgeries; when re-operation was successful, the post-surgical centrality of far regions increased (p < 0.05). Our data suggest that removal of the epileptogenic focus in children with DRE leads to a gain in the network centrality of the untouched areas. In contrast, unaltered or decreased connectivity is seen when seizures persist after surgery.
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77
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Bartoňová M, Bartoň M, Říha P, Vojtíšek L, Brázdil M, Rektor I. The benefit of the diffusion kurtosis imaging in presurgical evaluation in patients with focal MR-negative epilepsy. Sci Rep 2021; 11:14208. [PMID: 34244544 PMCID: PMC8270902 DOI: 10.1038/s41598-021-92804-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 06/15/2021] [Indexed: 02/06/2023] Open
Abstract
The effectivity of diffusion-weighted MRI methods in detecting the epileptogenic zone (EZ) was tested. Patients with refractory epilepsy (N=25) who subsequently underwent resective surgery were recruited. First, the extent of white matter (WM) asymmetry from mean kurtosis (MK) was calculated in order to detect the lobe with the strongest impairment. Second, a newly developed metric was used, reflecting a selection of brain areas with concurrently increased mean Diffusivity, reduced fractional Anisotropy, and reduced mean Kurtosis (iDrArK). A two-step EZ detection was performed as (1) lobe-specific detection, (2) iDrArK voxel-wise detection (with a possible lobe-specific restriction if the result of the first step was significant in a given subject). The method results were compared with the surgery resection zones. From the whole cohort (N=25), the numbers of patients with significant results were: 10 patients in lobe detection and 9 patients in EZ detection. From these subsets of patients with significant results, the impaired lobe was successfully detected with 100% accuracy; the EZ was successfully detected with 89% accuracy. The detection of the EZ using iDrArK was substantially more successful when compared with solo diffusional parameters (or their pairwise combinations). For a subgroup with significant results from step one (N=10), iDrArK without lobe restriction achieved 37.5% accuracy; lobe-restricted iDrArK achieved 100% accuracy. The study shows the plausibility of MK for detecting widespread WM changes and the benefit of combining different diffusional voxel-wise parameters.
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Affiliation(s)
- Michaela Bartoňová
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic ,grid.10267.320000 0001 2194 0956Brno Epilepsy Center, Full member of the European Reference Network (ERN) EpiCARE, First Department of Neurology, St. Anne′s University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Marek Bartoň
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
| | - Pavel Říha
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic ,grid.10267.320000 0001 2194 0956Brno Epilepsy Center, Full member of the European Reference Network (ERN) EpiCARE, First Department of Neurology, St. Anne′s University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Lubomír Vojtíšek
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic
| | - Milan Brázdil
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic ,grid.10267.320000 0001 2194 0956Brno Epilepsy Center, Full member of the European Reference Network (ERN) EpiCARE, First Department of Neurology, St. Anne′s University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Ivan Rektor
- grid.10267.320000 0001 2194 0956Central European Institute of Technology (CEITEC), Multimodal and Functional Neuroimaging Research Group, Masaryk University, Kamenice 753/5, 625 00 Brno, Czech Republic ,grid.10267.320000 0001 2194 0956Brno Epilepsy Center, Full member of the European Reference Network (ERN) EpiCARE, First Department of Neurology, St. Anne′s University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic
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78
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Vaudano AE, Mirandola L, Talami F, Giovannini G, Monti G, Riguzzi P, Volpi L, Michelucci R, Bisulli F, Pasini E, Tinuper P, Di Vito L, Gessaroli G, Malagoli M, Pavesi G, Cardinale F, Tassi L, Lemieux L, Meletti S. fMRI-Based Effective Connectivity in Surgical Remediable Epilepsies: A Pilot Study. Brain Topogr 2021; 34:632-650. [PMID: 34152513 DOI: 10.1007/s10548-021-00857-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 06/13/2021] [Indexed: 11/24/2022]
Abstract
Simultaneous EEG-fMRI can contribute to identify the epileptogenic zone (EZ) in focal epilepsies. However, fMRI maps related to Interictal Epileptiform Discharges (IED) commonly show multiple regions of signal change rather than focal ones. Dynamic causal modeling (DCM) can estimate effective connectivity, i.e. the causal effects exerted by one brain region over another, based on fMRI data. Here, we employed DCM on fMRI data in 10 focal epilepsy patients with multiple IED-related regions of BOLD signal change, to test whether this approach can help the localization process of EZ. For each subject, a family of competing deterministic, plausible DCM models were constructed using IED as autonomous input at each node, one at time. The DCM findings were compared to the presurgical evaluation results and classified as: "Concordant" if the node identified by DCM matches the presumed focus, "Discordant" if the node is distant from the presumed focus, or "Inconclusive" (no statistically significant result). Furthermore, patients who subsequently underwent intracranial EEG recordings or surgery were considered as having an independent validation of DCM results. The effective connectivity focus identified using DCM was Concordant in 7 patients, Discordant in two cases and Inconclusive in one. In four of the 6 patients operated, the DCM findings were validated. Notably, the two Discordant and Invalidated results were found in patients with poor surgical outcome. Our findings provide preliminary evidence to support the applicability of DCM on fMRI data to investigate the epileptic networks in focal epilepsy and, particularly, to identify the EZ in complex cases.
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Affiliation(s)
- A E Vaudano
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy. .,Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.
| | - L Mirandola
- Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - F Talami
- Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - G Giovannini
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy.,Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - G Monti
- Neurology Unit, AUSL Modena, Ospedale Ramazzini, Carpi, MO, Italy
| | - P Riguzzi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - L Volpi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - R Michelucci
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - F Bisulli
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Epilepsy Center (Reference Center for Rare and Complex Epilepsies - EpiCARE), Bologna, Italy
| | - E Pasini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - P Tinuper
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Epilepsy Center (Reference Center for Rare and Complex Epilepsies - EpiCARE), Bologna, Italy
| | - L Di Vito
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Epilepsy Center (Reference Center for Rare and Complex Epilepsies - EpiCARE), Bologna, Italy
| | - G Gessaroli
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy
| | - M Malagoli
- Neuroradiology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy
| | - G Pavesi
- Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.,Neurosurgery Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy
| | - F Cardinale
- "Claudio Munari" Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy
| | - L Tassi
- "Claudio Munari" Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy
| | - L Lemieux
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - S Meletti
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy.,Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
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79
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Rigney G, Lennon M, Holderrieth P. The use of computational models in the management and prognosis of refractory epilepsy: A critical evaluation. Seizure 2021; 91:132-140. [PMID: 34153898 DOI: 10.1016/j.seizure.2021.06.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 05/05/2021] [Accepted: 06/06/2021] [Indexed: 11/17/2022] Open
Abstract
PURPOSE Drug resistant epilepsy (DRE) affects approximately 30 percent of individuals with epilepsy worldwide. Surgery remains the most effective treatment for individuals with DRE, but referral to surgery is low and only about 60 percent of individuals who undergo surgery experience seizure control postoperatively. The present paper evaluates the evidence for using computational models in the prediction of surgical resection sites and surgical outcomes for patients with DRE. METHODS We conducted a search in the Medline data base using the terms "refractory epilepsy", "drug-resistant epilepsy", "surgery", "computational model", and "artificial intelligence". Inclusion: original articles in English and case reports from 2000 to 2020. Reviews were excluded. RESULTS Clinical applications of computational models may lead to increased utilisation of surgical services through improving our ability to predict outcomes and by improving surgical outcomes outright. The identification and optimisation of nodes that are crucial for the genesis and propagation of epileptiform activity offers the most promising clinical applications of computational models discussed herein. CONCLUSION Advances in computational models may in the future significantly increase the application and efficacy of surgery for patients with DRE by optimising the site and amount of cortex to resect, but more research is needed before it achieves therapeutic utility.
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Affiliation(s)
- Grant Rigney
- The University of Oxford Department of Psychiatry, Warneford Hospital, Warneford Ln, Headington, Oxford OX3 7JX, United Kingdom.
| | - Matthew Lennon
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, United Kingdom; Faculty of Medicine, University of New South Wales, NSW, Australia.
| | - Peter Holderrieth
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, United Kingdom.
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80
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Ictal gamma-band interactions localize ictogenic nodes of the epileptic network in focal cortical dysplasia. Clin Neurophysiol 2021; 132:1927-1936. [PMID: 34157635 DOI: 10.1016/j.clinph.2021.04.016] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 03/18/2021] [Accepted: 04/05/2021] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Epilepsy surgery fails in > 30% of patients with focal cortical dysplasia (FCD). The seizure persistence after surgery can be attributed to the inability to precisely localize the tissue with an endogenous potential to generate seizures. In this study, we aimed to identify the critical components of the epileptic network that were actively involved in seizure genesis. METHODS The directed transfer function was applied to intracranial EEG recordings and the effective connectivity was determined with a high temporal and frequency resolution. Pre-ictal network properties were compared with ictal epochs to identify regions actively generating ictal activity and discriminate them from the areas of propagation. RESULTS Analysis of 276 seizures from 30 patients revealed the existence of a seizure-related network reconfiguration in the gamma-band (25-170 Hz; p < 0.005) - ictogenic nodes. Unlike seizure onset zone, resecting the majority of ictogenic nodes correlated with favorable outcomes (p < 0.012). CONCLUSION The prerequisite to successful epilepsy surgery is the accurate identification of brain areas from which seizures arise. We show that in FCD-related epilepsy, gamma-band network markers can reliably identify and distinguish ictogenic areas in macroelectrode recordings, improve intracranial EEG interpretation and better delineate the epileptogenic zone. SIGNIFICANCE Ictogenic nodes localize the critical parts of the epileptogenic tissue and increase the diagnostic yield of intracranial evaluation.
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81
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Cai C, Chen J, Findlay AM, Mizuiri D, Sekihara K, Kirsch HE, Nagarajan SS. Clinical Validation of the Champagne Algorithm for Epilepsy Spike Localization. Front Hum Neurosci 2021; 15:642819. [PMID: 34093150 PMCID: PMC8172809 DOI: 10.3389/fnhum.2021.642819] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 03/22/2021] [Indexed: 01/03/2023] Open
Abstract
Magnetoencephalography (MEG) is increasingly used for presurgical planning in people with medically refractory focal epilepsy. Localization of interictal epileptiform activity, a surrogate for the seizure onset zone whose removal may prevent seizures, is challenging and depends on the use of multiple complementary techniques. Accurate and reliable localization of epileptiform activity from spontaneous MEG data has been an elusive goal. One approach toward this goal is to use a novel Bayesian inference algorithm-the Champagne algorithm with noise learning-which has shown tremendous success in source reconstruction, especially for focal brain sources. In this study, we localized sources of manually identified MEG spikes using the Champagne algorithm in a cohort of 16 patients with medically refractory epilepsy collected in two consecutive series. To evaluate the reliability of this approach, we compared the performance to equivalent current dipole (ECD) modeling, a conventional source localization technique that is commonly used in clinical practice. Results suggest that Champagne may be a robust, automated, alternative to manual parametric dipole fitting methods for localization of interictal MEG spikes, in addition to its previously described clinical and research applications.
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Affiliation(s)
- Chang Cai
- National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Jessie Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Anne M. Findlay
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Danielle Mizuiri
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Kensuke Sekihara
- Department of Advanced Technology in Medicine, Tokyo Medical and Dental University, Tokyo, Japan
- Signal Analysis Inc., Hachioji, Japan
| | - Heidi E. Kirsch
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
- Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Srikantan S. Nagarajan
- National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China
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82
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Wang J, Jing B, Liu R, Li D, Wang W, Wang J, Lei J, Xing Y, Yan J, Loh HH, Lu G, Yang X. Characterizing the seizure onset zone and epileptic network using EEG-fMRI in a rat seizure model. Neuroimage 2021; 237:118133. [PMID: 33951515 DOI: 10.1016/j.neuroimage.2021.118133] [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: 02/20/2021] [Revised: 04/07/2021] [Accepted: 04/26/2021] [Indexed: 11/26/2022] Open
Abstract
Accurate epileptogenic zone (EZ) or seizure onset zone (SOZ) localization is crucial for epilepsy surgery optimization. Previous animal and human studies on epilepsy have reported that changes in blood oxygen level-dependent (BOLD) signals induced by epileptic events could be used as diagnostic markers for EZ or SOZ localization. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) recording is gaining interest as a non-invasive tool for preoperative epilepsy evaluation. However, EEG-fMRI studies have reported inconsistent and ambiguous findings. Therefore, it remains unclear whether BOLD responses can be used for accurate EZ or SOZ localization. In this study, we used simultaneous EEG-fMRI recording in a rat model of 4-aminopyridine-induced acute focal seizures to assess the spatial concordance between individual BOLD responses and the SOZ. This was to determine the optimal use of simultaneous EEG-fMRI recording in the SOZ localization. We observed a high spatial consistency between BOLD responses and the SOZ. Further, dynamic BOLD responses were consistent with the regions where the seizures were propagated. These results suggested that simultaneous EEG-fMRI recording could be used as a noninvasive clinical diagnostic technique for localizing the EZ or SOZ and could be an effective tool for mapping epileptic networks.
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Affiliation(s)
- Junling Wang
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Bin Jing
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Ru Liu
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Donghong Li
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Wei Wang
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jiaoyang Wang
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jianfeng Lei
- Core Facilities Center, Capital Medical University, Beijing, China
| | - Yue Xing
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jiaqing Yan
- College of Electrical and Control Engineering, North China University of Technology, Beijing, China
| | - Horace H Loh
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Southern Medical University, Nanjing, China; Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Xiaofeng Yang
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China.
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83
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Tamilia E, Matarrese MAG, Ntolkeras G, Grant PE, Madsen JR, Stufflebeam SM, Pearl PL, Papadelis C. Noninvasive Mapping of Ripple Onset Predicts Outcome in Epilepsy Surgery. Ann Neurol 2021; 89:911-925. [PMID: 33710676 PMCID: PMC8229023 DOI: 10.1002/ana.26066] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 03/09/2021] [Accepted: 03/10/2021] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Intracranial electroencephalographic (icEEG) studies show that interictal ripples propagate across the brain of children with medically refractory epilepsy (MRE), and the onset of this propagation (ripple onset zone [ROZ]) estimates the epileptogenic zone. It is still unknown whether we can map this propagation noninvasively. The goal of this study is to map ripples (ripple zone [RZ]) and their propagation onset (ROZ) using high-density EEG (HD-EEG) and magnetoencephalography (MEG), and to estimate their prognostic value in pediatric epilepsy surgery. METHODS We retrospectively analyzed simultaneous HD-EEG and MEG data from 28 children with MRE who underwent icEEG and epilepsy surgery. Using electric and magnetic source imaging, we estimated virtual sensors (VSs) at brain locations that matched the icEEG implantation. We detected ripples on VSs, defined the virtual RZ and virtual ROZ, and estimated their distance from icEEG. We assessed the predictive value of resecting virtual RZ and virtual ROZ for postsurgical outcome. Interictal spike localization on HD-EEG and MEG was also performed and compared with ripples. RESULTS We mapped ripple propagation in all patients with HD-EEG and in 27 (96%) patients with MEG. The distance from icEEG did not differ between HD-EEG and MEG when mapping the RZ (26-27mm, p = 0.6) or ROZ (22-24mm, p = 0.4). Resecting the virtual ROZ, but not virtual RZ or the sources of spikes, was associated with good outcome for HD-EEG (p = 0.016) and MEG (p = 0.047). INTERPRETATION HD-EEG and MEG can map interictal ripples and their propagation onset (virtual ROZ). Noninvasively mapping the ripple onset may augment epilepsy surgery planning and improve surgical outcome of children with MRE. ANN NEUROL 2021;89:911-925.
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Affiliation(s)
- Eleonora Tamilia
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of MedicineBoston Children's Hospital, Harvard Medical SchoolBostonMA
- Fetal‐Neonatal Neuroimaging and Developmental Science CenterBoston Children's Hospital, Harvard Medical SchoolBostonMA
| | - Margherita A. G. Matarrese
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of MedicineBoston Children's Hospital, Harvard Medical SchoolBostonMA
- Laboratory of Nonlinear Physics and Mathematical Modeling, Department of EngineeringUniversity Bio‐Medico Campus of RomeRomeItaly
| | - Georgios Ntolkeras
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of MedicineBoston Children's Hospital, Harvard Medical SchoolBostonMA
- Fetal‐Neonatal Neuroimaging and Developmental Science CenterBoston Children's Hospital, Harvard Medical SchoolBostonMA
| | - P. Ellen Grant
- Fetal‐Neonatal Neuroimaging and Developmental Science CenterBoston Children's Hospital, Harvard Medical SchoolBostonMA
| | - Joseph R. Madsen
- Epilepsy Surgery Program, Department of NeurosurgeryBoston Children's Hospital, Harvard Medical SchoolBostonMA
| | - Steve M. Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMA
| | - Phillip L. Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of NeurologyBoston Children's Hospital, Harvard Medical SchoolBostonMA
| | - Christos Papadelis
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of MedicineBoston Children's Hospital, Harvard Medical SchoolBostonMA
- Jane and John Justin Neurosciences CenterCook Children's Health Care SystemFort WorthTX
- School of Medicine, Texas Christian University and University of North Texas Health Science CenterFort WorthTX
- Department of BioengineeringUniversity of Texas at ArlingtonArlingtonTX
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84
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Baroumand AG, Arbune AA, Strobbe G, Keereman V, Pinborg LH, Fabricius M, Rubboli G, Gøbel Madsen C, Jespersen B, Brennum J, Mølby Henriksen O, Mierlo PV, Beniczky S. Automated ictal EEG source imaging: A retrospective, blinded clinical validation study. Clin Neurophysiol 2021; 141:119-125. [PMID: 33972159 DOI: 10.1016/j.clinph.2021.03.040] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/23/2021] [Accepted: 03/02/2021] [Indexed: 11/03/2022]
Abstract
OBJECTIVE EEG source imaging (ESI) is a validated tool in the multimodal workup of patients with drug resistant focal epilepsy. However, it requires special expertise and it is underutilized. To circumvent this, automated analysis pipelines have been developed and validated for the interictal discharges. In this study, we present the clinical validation of an automated ESI for ictal EEG signals. METHODS We have developed an automated analysis pipeline of ictal EEG activity, based on spectral analysis in source space, using an individual head model of six tissues. The analysis was done blinded to all other data. As reference standard, we used the concordance with the resected area and one-year postoperative outcome. RESULTS We analyzed 50 consecutive patients undergoing epilepsy surgery (34 temporal and 16 extra-temporal). Thirty patients (60%) became seizure-free. The accuracy of the automated ESI was 74% (95% confidence interval: 59.66-85.37%). CONCLUSIONS Automated ictal ESI has a high accuracy for localizing the seizure onset zone. SIGNIFICANCE Automating the ESI of the ictal EEG signals will facilitate implementation of this tool in the presurgical evaluation.
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Affiliation(s)
- Amir G Baroumand
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Campus UZ Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium
| | - Anca A Arbune
- Department of Clinical Neurophysiology, Danish Epilepsy Centre, Visby Allé 5, 4293 Dianalund, Denmark; Neurology Clinic, Fundeni Clinical Institute, Soseaua Fundeni no. 258, Sector 2, 022328 Bucharest, Romania
| | | | - Vincent Keereman
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Campus UZ Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium
| | - Lars H Pinborg
- Department of Neurology, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark; Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, 9 Blegdamsvej, DK-2100 Copenhagen Ø, Denmark
| | - Martin Fabricius
- Department of Clinical Neurophysiology, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark
| | - Guido Rubboli
- Department of Neurology, Danish Epilepsy Centre, Kolonivej 1, 4293 Dianalund, Denmark; Institute of Clinical Medicine, University of Copenhagen, Denmark
| | - Camilla Gøbel Madsen
- Department of Diagnostic Radiology, Centre for Functional and Diagnostic Imaging and Research, Hvidovre Hospital, Kettegaard Alle 30, 2650 Hvidovre, Denmark
| | - Bo Jespersen
- Department of Neurosurgery, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark
| | - Jannick Brennum
- Department of Neurosurgery, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark
| | - Otto Mølby Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark
| | - Pieter van Mierlo
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Campus UZ Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium
| | - Sándor Beniczky
- Department of Clinical Neurophysiology, Danish Epilepsy Centre, Visby Allé 5, 4293 Dianalund, Denmark; Department of Clinical Neurophysiology, Aarhus University Hospital, Palle Juul-Jensens Blvd., 8200 Aarhus, Denmark.
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85
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Noninvasive high-frequency oscillations riding spikes delineates epileptogenic sources. Proc Natl Acad Sci U S A 2021; 118:2011130118. [PMID: 33875582 PMCID: PMC8092606 DOI: 10.1073/pnas.2011130118] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Millions of people affected by epilepsy may undergo surgical resection of the epileptic tissues to stop seizures if such epileptic foci can be accurately delineated. High-frequency oscillations (HFOs), existing in electroencephalography, are highly correlated with epileptic brain, which is promising for guiding successful neurosurgery. However, it is unclear whether and how pathological HFOs can be differentiated to localize the epileptogenic tissues given the presence of various nonepileptic high-frequency activities. Here, we show morphological and source imaging evidence that pathological HFOs can be identified by the concurrence of epileptiform spikes. We describe a framework to delineate the underlying epileptogenicity using this biomarker. Our work may offer translational tools to improve treatments by noninvasively demarking pathological activities and hence epileptic foci. High-frequency oscillations (HFOs) are a promising biomarker for localizing epileptogenic brain and guiding successful neurosurgery. However, the utility and translation of noninvasive HFOs, although highly desirable, is impeded by the difficulty in differentiating pathological HFOs from nonepileptiform high-frequency activities and localizing the epileptic tissue using noninvasive scalp recordings, which are typically contaminated with high noise levels. Here, we show that the consistent concurrence of HFOs with epileptiform spikes (pHFOs) provides a tractable means to identify pathological HFOs automatically, and this in turn demarks an epileptiform spike subgroup with higher epileptic relevance than the other spikes in a cohort of 25 temporal epilepsy patients (including a total of 2,967 interictal spikes and 1,477 HFO events). We found significant morphological distinctions of HFOs and spikes in the presence/absence of this concurrent status. We also demonstrated that the proposed pHFO source imaging enhanced localization of epileptogenic tissue by 162% (∼5.36 mm) for concordance with surgical resection and by 186% (∼12.48 mm) with seizure-onset zone determined by invasive studies, compared to conventional spike imaging, and demonstrated superior congruence with the surgical outcomes. Strikingly, the performance of spike imaging was selectively boosted by the presence of spikes with pHFOs, especially in patients with multitype spikes. Our findings suggest that concurrent HFOs and spikes reciprocally discriminate pathological activities, providing a translational tool for noninvasive presurgical diagnosis and postsurgical evaluation in vulnerable patients.
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86
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Specchio N, Pepi C, De Palma L, Trivisano M, Vigevano F, Curatolo P. Neuroimaging and genetic characteristics of malformation of cortical development due to mTOR pathway dysregulation: clues for the epileptogenic lesions and indications for epilepsy surgery. Expert Rev Neurother 2021; 21:1333-1345. [PMID: 33754929 DOI: 10.1080/14737175.2021.1906651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Introduction: Malformation of cortical development (MCD) is strongly associated with drug-resistant epilepsies for which surgery to remove epileptogenic lesions is common. Two notable technological advances in this field are identification of the underlying genetic cause and techniques in neuroimaging. These now question how presurgical evaluation ought to be approached for 'mTORpathies.'Area covered: From review of published primary and secondary articles, the authors summarize evidence to consider focal cortical dysplasia (FCD), tuber sclerosis complex (TSC), and hemimegalencephaly (HME) collectively as MCD mTORpathies. The authors also consider the unique features of these related conditions with particular focus on the practicalities of using neuroimaging techniques currently available to define surgical targets and predict post-surgical outcome. Ultimately, the authors consider the surgical dilemmas faced for each condition.Expert opinion: Considering FCD, TSC, and HME collectively as mTORpathies has some merit; however, a unified approach to presurgical evaluation would seem unachievable. Nevertheless, the authors believe combining genetic-centered classification and morphologic findings using advanced imaging techniques will eventually form the basis of a paradigm when considering candidacy for early surgery.
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Affiliation(s)
- Nicola Specchio
- Rare and Complex Epilepsy Unit, Department of Neurosciences, Bambino Gesù Children's Hospital, IRCCS, Member of European Reference Network EpiCARE, Rome, Italy
| | - Chiara Pepi
- Rare and Complex Epilepsy Unit, Department of Neurosciences, Bambino Gesù Children's Hospital, IRCCS, Member of European Reference Network EpiCARE, Rome, Italy
| | - Luca De Palma
- Rare and Complex Epilepsy Unit, Department of Neurosciences, Bambino Gesù Children's Hospital, IRCCS, Member of European Reference Network EpiCARE, Rome, Italy
| | - Marina Trivisano
- Rare and Complex Epilepsy Unit, Department of Neurosciences, Bambino Gesù Children's Hospital, IRCCS, Member of European Reference Network EpiCARE, Rome, Italy
| | - Federico Vigevano
- Department of Neuroscience, Bambino Gesù Children's Hospital, IRCCS, Member of European Reference Network EpiCARE, Rome, Italy
| | - Paolo Curatolo
- Child Neurology and Psychiatry Unit, Systems Medicine Department, Tor Vergata University, Rome, Italy
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87
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Razansky D, Klohs J, Ni R. Multi-scale optoacoustic molecular imaging of brain diseases. Eur J Nucl Med Mol Imaging 2021; 48:4152-4170. [PMID: 33594473 PMCID: PMC8566397 DOI: 10.1007/s00259-021-05207-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 01/17/2021] [Indexed: 02/07/2023]
Abstract
The ability to non-invasively visualize endogenous chromophores and exogenous probes and sensors across the entire rodent brain with the high spatial and temporal resolution has empowered optoacoustic imaging modalities with unprecedented capacities for interrogating the brain under physiological and diseased conditions. This has rapidly transformed optoacoustic microscopy (OAM) and multi-spectral optoacoustic tomography (MSOT) into emerging research tools to study animal models of brain diseases. In this review, we describe the principles of optoacoustic imaging and showcase recent technical advances that enable high-resolution real-time brain observations in preclinical models. In addition, advanced molecular probe designs allow for efficient visualization of pathophysiological processes playing a central role in a variety of neurodegenerative diseases, brain tumors, and stroke. We describe outstanding challenges in optoacoustic imaging methodologies and propose a future outlook.
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Affiliation(s)
- Daniel Razansky
- Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Wolfgang-Pauli-Strasse 27, HIT E42.1, 8093, Zurich, Switzerland
- Zurich Neuroscience Center (ZNZ), Zurich, Switzerland
- Faculty of Medicine and Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Jan Klohs
- Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Wolfgang-Pauli-Strasse 27, HIT E42.1, 8093, Zurich, Switzerland
- Zurich Neuroscience Center (ZNZ), Zurich, Switzerland
| | - Ruiqing Ni
- Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Wolfgang-Pauli-Strasse 27, HIT E42.1, 8093, Zurich, Switzerland.
- Zurich Neuroscience Center (ZNZ), Zurich, Switzerland.
- Institute for Regenerative Medicine, Uiversity of Zurich, Zurich, Switzerland.
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Li R, Plummer C, Vogrin SJ, Woods WP, Kuhlmann L, Boston R, Liley DTJ, Cook MJ, Grayden DB. Interictal spike localization for epilepsy surgery using magnetoencephalography beamforming. Clin Neurophysiol 2021; 132:928-937. [PMID: 33636608 DOI: 10.1016/j.clinph.2020.12.019] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 11/25/2020] [Accepted: 12/03/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE Magnetoencephalography (MEG) kurtosis beamforming is an automated localization method for focal epilepsy. Visual examination of virtual sensors, which are source activities reconstructed by beamforming, can improve performance but can be time-consuming for neurophysiologists. We propose a framework to automate the method and evaluate its effectiveness against surgical resections and outcomes. METHODS We retrospectively analyzed MEG recordings of 13 epilepsy surgery patients who had one-year minimum post-operative follow-up. Kurtosis beamforming was applied and manual inspection was confined to morphological clusters. The region with the Maximum Interictal Spike Frequency (MISF) was validated against prospectively modelled sLORETA solutions and surgical resections linked to outcome. RESULTS Our approach localized spikes in 12 out of 13 patients. In eight patients with Engel I surgical outcomes, beamforming MISF regions were concordant with surgical resection at overlap level for five patients and at lobar level for three patients. The MISF regions localized to spike onset and propagation modelled by sLORETA in two and six patients, respectively. CONCLUSIONS Automated beamforming using MEG can predict postoperative seizure freedom at the lobar level but tends to localize propagated MEG spikes. SIGNIFICANCE MEG beamforming may contribute to non-invasive procedures to predict surgical outcome for patients with drug-refractory focal epilepsy.
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Affiliation(s)
- Rui Li
- Department of Biomedical Engineering, The University of Melbourne, Parkville, VIC, Australia.
| | - Chris Plummer
- Department of Medicine, The University of Melbourne, Fitzroy, VIC, Australia; Department of Neurology, St. Vincent's Hospital, Fitzroy, VIC, Australia; School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC, Australia
| | - Simon J Vogrin
- Department of Medicine, The University of Melbourne, Fitzroy, VIC, Australia; Department of Neurology, St. Vincent's Hospital, Fitzroy, VIC, Australia; School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC, Australia
| | - William P Woods
- School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC, Australia
| | - Levin Kuhlmann
- Faculty of Information Technology, Monash University, Clayton, VIC 3168, Australia
| | - Ray Boston
- Department of Medicine, The University of Melbourne, Fitzroy, VIC, Australia; Department of Clinical Studies, New Bolton Centre, School of Veterinary Medicine, University of Pennsylvania, Kennett Square, PA, USA
| | - David T J Liley
- Department of Medicine, The University of Melbourne, Fitzroy, VIC, Australia; Centre for Human Psychopharmacology, Swinburne University of Technology, Hawthorn, VIC, Australia
| | - Mark J Cook
- Department of Medicine, The University of Melbourne, Fitzroy, VIC, Australia; Department of Neurology, St. Vincent's Hospital, Fitzroy, VIC, Australia; Graeme Clark Institute for Biomedical Engineering, The University of Melbourne, Parkville, VIC, Australia
| | - David B Grayden
- Department of Biomedical Engineering, The University of Melbourne, Parkville, VIC, Australia; Department of Medicine, The University of Melbourne, Fitzroy, VIC, Australia; Graeme Clark Institute for Biomedical Engineering, The University of Melbourne, Parkville, VIC, Australia
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Kaewchur T, Chamroonrat W, Thientunyakit T, Khiewvan B, Wongsurawat N, Chotipanich C, Chinvarun Y, Bunyaratavej K, Amnuaywattakorn S, Poon-Iad N, Sontrapornpol T, Pasawang P, Tepmongkol S. Thai National Guideline for Nuclear Medicine Investigations in Epilepsy. ASIA OCEANIA JOURNAL OF NUCLEAR MEDICINE & BIOLOGY 2021; 9:188-206. [PMID: 34250150 PMCID: PMC8255518 DOI: 10.22038/aojnmb.2021.54567.1379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 03/20/2021] [Accepted: 04/17/2021] [Indexed: 11/06/2022]
Abstract
Epilepsy is a disorder of the brain, which is characterized by recurrent epileptic seizures. These patients are generally treated with antiepileptic drugs. However, more than 30% of the patients become medically intractable and undergo a series of investigations to define candidates for epilepsy surgery. Nuclear Medicine studies using Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) radiopharmaceuticals are among the investigations used for this purpose. Since available guidelines for the investigation of surgical candidates are not up-to-date, The Nuclear Medicine Society of Thailand, The Neurological Society of Thailand, The Royal College of Neurological Surgeons of Thailand, and The Thai Medical Physicist Society has collaborated to develop this Thai national guideline for Nuclear Medicine study in epilepsy. The guideline focuses on the use of brain perfusion SPECT and F-18 fluorodeoxyglucose PET (FDG-PET), the mainly used methods in day-to-day practice. This guideline aims for effective use of Nuclear Medicine investigations by referring physicians e.g. epileptologists and neurologists, radiologists, nuclear medicine physicians, medical physicists, nuclear medicine technologists and technicians.
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Affiliation(s)
- Tawika Kaewchur
- Department of Radiology, PET/CT and Cyclotron Center, Chiang Mai University, Chiang Mai, Thailand
| | - Wichana Chamroonrat
- Division of Nuclear Medicine, Department of Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Tanyaluck Thientunyakit
- Division of Nuclear Medicine, Department of Radiology, Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Benjapa Khiewvan
- Division of Nuclear Medicine, Department of Radiology, Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Nantaporn Wongsurawat
- Division of Nuclear Medicine, Department of Radiology, Khon Kaen University, Khon Kaen, Thailand
| | | | - Yotin Chinvarun
- Department of Medicine, Phramongkutklao Hospital, Bangkok, Thailand
| | | | - Sasithorn Amnuaywattakorn
- Division of Nuclear Medicine, Department of Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Nucharee Poon-Iad
- Division of Nuclear Medicine, Department of Radiology, Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Tanawat Sontrapornpol
- Division of Nuclear Medicine, Department of Radiology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Panya Pasawang
- Division of Nuclear Medicine, Department of Radiology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
| | - Supatporn Tepmongkol
- Nuclear Medicine Division, Department of Radiology, Chulalongkorn University, Rama IV Rd, Pathumwan, Bangkok, Thailand
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90
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Baud MO, Schindler K, Rao VR. Under-sampling in epilepsy: Limitations of conventional EEG. Clin Neurophysiol Pract 2020; 6:41-49. [PMID: 33532669 PMCID: PMC7829106 DOI: 10.1016/j.cnp.2020.12.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 12/04/2020] [Accepted: 12/09/2020] [Indexed: 12/26/2022] Open
Abstract
The cyclical structure of epilepsy was recently (re)-discovered through years-long intracranial electroencephalography (EEG) obtained with implanted devices. In this review, we discuss how new revelations from chronic EEG relate to the practice and interpretation of conventional EEG. We argue for an electrographic definition of seizures and highlight the caveats of counting epileptiform discharges in EEG recordings of short duration. Limitations of conventional EEG have practical implications with regard to titrating anti-seizure medications and allowing patients to drive, and we propose that chronic monitoring of brain activity could greatly improve epilepsy care. An impending paradigm shift in epilepsy will involve using next-generation devices for chronic EEG to leverage known biomarkers of disease state.
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Affiliation(s)
- Maxime O. Baud
- Sleep Wake Epilepsy Center, NeuroTec and Center for Experimental Neurology, Department of Neurology, Inselspital Bern, University Hospital, University of Bern, Switzerland
- Wyss Center for Bio- and Neuro-engineering, Geneva, Switzerland
| | - Kaspar Schindler
- Sleep Wake Epilepsy Center, NeuroTec and Center for Experimental Neurology, Department of Neurology, Inselspital Bern, University Hospital, University of Bern, Switzerland
| | - Vikram R. Rao
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, United States
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91
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Poch C, Toledano R, García-Morales I, Alemán-Gómez Y, Gil-Nagel A, Campo P. Contributions of left and right anterior temporal lobes to semantic cognition: Evidence from patients with small temporopolar lesions. Neuropsychologia 2020; 152:107738. [PMID: 33383038 DOI: 10.1016/j.neuropsychologia.2020.107738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 12/04/2020] [Accepted: 12/24/2020] [Indexed: 11/18/2022]
Abstract
Decades of research have increased the understanding of the contribution of the anterior temporal lobes (ATLs) to semantic cognition. Nonetheless, whether semantic processing of different types of information show a selective relationship with left and right ATLs, or whether semantic processing in the ATLs is independent of the modality of the input is currently unknown. There exists evidence supporting each of these alternatives. A fundamental objection to these findings is that they were obtained from studies with patients with brain damage affecting extensive regions, sometimes bilaterally. In the current study, we assessed a group of 38 temporal lobe epilepsy (TLE) patients with either left or right small epileptogenic lesions with a battery of commonly used semantic tasks that tested verbal and non-verbal semantic processing. We found that left TLE patients exhibited worse performance than controls on the verbal semantic tasks, as expected, but also on the non-verbal semantic task. On the other hand, performance of the right TLE group did not differ from controls on the non-verbal task, but was worse on a semantic fluency task. When performance between patient groups was compared, we found that left TLE not only did worse than right TLE on the naming task, but also on the non-verbal associative memory task. When considered together, current data do not support a strong view of input modality differences between left and right ATLs. Additionally, they provide evidence indicating that the left and right ATLs do not make similar contributions to a singular functional system for semantic representation.
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Affiliation(s)
- Claudia Poch
- Facultad de Lenguas y Educación, Universidad Nebrija, Spain
| | - Rafael Toledano
- Hospital Ruber Internacional, Epilepsy Unit, Neurology Department, Madrid, Spain; University Hospital of Ramón y Cajal, Epilepsy Unit, Neurology Department, Madrid, Spain
| | - Irene García-Morales
- Hospital Ruber Internacional, Epilepsy Unit, Neurology Department, Madrid, Spain; University Hospital of San Carlos, Epilepsy Unit, Neurology Department, Madrid, Spain
| | - Yasser Alemán-Gómez
- Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Medical Image Analysis Laboratory (MIAL), Centre D'Imagerie BioMédicale (CIBM), Lausanne, Switzerland
| | - Antonio Gil-Nagel
- Hospital Ruber Internacional, Epilepsy Unit, Neurology Department, Madrid, Spain
| | - Pablo Campo
- Department of Basic Psychology, Autonoma University of Madrid, Madrid, Spain.
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Josephson CB, Wiebe S. Precision Medicine: Academic dreaming or clinical reality? Epilepsia 2020; 62 Suppl 2:S78-S89. [PMID: 33205406 DOI: 10.1111/epi.16739] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 10/02/2020] [Accepted: 10/02/2020] [Indexed: 12/26/2022]
Abstract
Precision medicine can be distilled into a concept of accounting for an individual's unique collection of clinical, physiologic, genetic, and sociodemographic characteristics to provide patient-level predictions of disease course and response to therapy. Abundant evidence now allows us to determine how an average person with epilepsy will respond to specific medical and surgical treatments. This is useful, but not readily applicable to an individual patient. This has brought into sharp focus the desire for a more individualized approach through which we counsel people based on individual characteristics, as opposed to population-level data. We are now accruing data at unprecedented rates, allowing us to convert this ideal into reality. In addition, we have access to growing volumes of administrative and electronic health records data, biometric, imaging, genetics data, microbiome, and other "omics" data, thus paving the way toward phenome-wide association studies and "the epidemiology of one." Despite this, there are many challenges ahead. The collating, integrating, and storing sensitive multimodal data for advanced analytics remains difficult as patient consent and data security issues increase in complexity. Agreement on many aspects of epilepsy remains imperfect, rendering models sensitive to misclassification due to a lack of "ground truth." Even with existing data, advanced analytics models are prone to overfitting and often failure to generalize externally. Finally, uptake by clinicians is often hindered by opaque, "black box" algorithms. Systematic approaches to data collection and model generation, and an emphasis on education to promote uptake and knowledge translation, are required to propel epilepsy-based precision medicine from the realm of the theoretical into routine clinical practice.
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Affiliation(s)
- Colin B Josephson
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada.,Centre for Health Informatics, University of Calgary, Calgary, AB, Canada
| | - Samuel Wiebe
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada.,Clinical Research Unit, University of Calgary, Calgary, AB, Canada
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Vorderwülbecke BJ, Carboni M, Tourbier S, Brunet D, Seeber M, Spinelli L, Seeck M, Vulliemoz S. High-density Electric Source Imaging of interictal epileptic discharges: How many electrodes and which time point? Clin Neurophysiol 2020; 131:2795-2803. [PMID: 33137569 DOI: 10.1016/j.clinph.2020.09.018] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 07/31/2020] [Accepted: 09/07/2020] [Indexed: 11/18/2022]
Abstract
OBJECTIVE To assess the value of caudal EEG electrodes over cheeks and neck for high-density electric source imaging (ESI) in presurgical epilepsy evaluation, and to identify the best time point during averaged interictal epileptic discharges (IEDs) for optimal ESI accuracy. METHODS We retrospectively examined presurgical 257-channel EEG recordings of 45 patients with pharmacoresistant focal epilepsy. By stepwise removal of cheek and neck electrodes, averaged IEDs were downsampled to 219, 204, and 156 EEG channels. Additionally, ESI at the IED's half-rise was compared to other time points. The respective sources of maximum activity were compared to the resected brain area and postsurgical outcome. RESULTS Caudal channels had disproportionately more artefacts. In 30 patients with favourable outcome, the 204-channel array yielded the most accurate results with ESI maxima < 10 mm from the resection in 67% and inside affected sublobes in 83%. Neither in temporal nor in extratemporal cases did the full 257-channel setup improve ESI accuracy. ESI was most accurate at 50% of the IED's rising phase. CONCLUSION Information from cheeks and neck electrodes did not improve high-density ESI accuracy, probably due to higher artefact load and suboptimal biophysical modelling. SIGNIFICANCE Very caudal EEG electrodes should be used for ESI with caution.
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Affiliation(s)
- Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Department of Neurology, Epilepsy-Center Berlin-Brandenburg, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
| | - Margherita Carboni
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland.
| | - Sebastien Tourbier
- Connectomics Lab, Department of Radiology, Lausanne University Hospital, Rue du Bugnon 46, 1011 Lausanne, Switzerland.
| | - Denis Brunet
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland.
| | - Martin Seeber
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland.
| | - Laurent Spinelli
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
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Demuru M, Zweiphenning W, van Blooijs D, Van Eijsden P, Leijten F, Zijlmans M, Kalitzin S. Validation of virtual resection on intraoperative interictal data acquired during epilepsy surgery. J Neural Eng 2020; 17. [PMID: 33086212 DOI: 10.1088/1741-2552/abc3a8] [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: 07/06/2020] [Accepted: 10/21/2020] [Indexed: 11/11/2022]
Abstract
OBJECTIVE A 'Virtual resection' consists of computationally simulating the effect of an actual resection on the brain. We validated two functional connectivity based virtual resection methods with the actual connectivity measured using post-resection intraoperative recordings. METHODS A non-linear association index was applied to pre-resection recordings from 11 extra-temporal focal epilepsy patients. We computed two virtual resection strategies: first, a 'naive' one obtained by simply removing from the connectivity matrix the electrodes that were resected; second, a virtual resection with partialization accounting for the influence of resected electrodes on not-resected electrodes. We validated the virtual resections with two analysis: 1) We tested with a Kolmogorov-Smirnov test if the distributions of connectivity values after the virtual resections differed from the actual post-resection connectivity distribution; 2) we tested if the overall effect of the resection measured by contrasting pre-resection and post-resection connectivity values is detectable with the virtual resection approach using a Kolmogorv-Smirnov test. RESULTS The estimation of post-resection connectivity values did not succeed for both methods. In the second analysis, the naive method failed completely to detect the effect found between pre-resection and post-resection connectivity distributions, while the partialization method agreed with post-resection measurements in detecting a drop connectivity compared to pre-resection recordings. CONCLUSION Our findings suggest that the partialization technique is superior to the naive method in detecting the overall effect after the resection. SIGNIFICANCE We pointed out how a realistic validation based on actual post-resection recordings reveals that virtual resection methods are not yet mature to inform the clinical decision-making.
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Affiliation(s)
- Matteo Demuru
- Research, SEIN, Hoofddorp, Noord-Holland, NETHERLANDS
| | - Willemiek Zweiphenning
- Neurology and Neurosurgery, UMC Utrecht Brain Center Rudolf Magnus, Utrecht, Utrecht, NETHERLANDS
| | - Dorien van Blooijs
- Neurology and Neurosurgery, UMC Utrecht Brain Center Rudolf Magnus, Utrecht, Utrecht, NETHERLANDS
| | - Pieter Van Eijsden
- Neurology and Neurosurgery, UMC Utrecht Brain Center Rudolf Magnus, Utrecht, Utrecht, NETHERLANDS
| | - Frans Leijten
- Neurology and Neurosurgery, UMC Utrecht Brain Center Rudolf Magnus, Utrecht, Utrecht, NETHERLANDS
| | - Maeike Zijlmans
- Neurology and Neurosurgery, UMC Utrecht Brain Center Rudolf Magnus, Utrecht, Utrecht, NETHERLANDS
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Zhang M, Liu W, Huang P, Lin X, Huang X, Meng H, Wang J, Hu K, Li J, Lin M, Sun B, Zhan S, Li B. Utility of hybrid PET/MRI multiparametric imaging in navigating SEEG placement in refractory epilepsy. Seizure 2020; 81:295-303. [PMID: 32932134 DOI: 10.1016/j.seizure.2020.08.027] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 08/09/2020] [Accepted: 08/25/2020] [Indexed: 02/07/2023] Open
Abstract
PURPOSE Stereo-electroencephalography (SEEG) implantation before epilepsy surgery is critical for precise localization and complete resection of the seizure onset zone (SOZ). Combined metabolic and morphological imaging using hybrid PET/MRI may provide supportive information for the optimization of the SEEG coverage of brain structures. In this study, we originally imported PET/MRI images into the SEEG positioning system to evaluate the application of PET/MRI in guiding SEEG implantation in refractory epilepsy patients. MATERIALS Forty-two patients undergoing simultaneous PET/MRI examinations were recruited. All the patients underwent SEEG implantation guided by hybrid PET/MRI and surgical resection or ablation of epileptic lesion. Surgery outcome was assessed using a modified Engel classification one year (13.60 ± 2.49 months) after surgery. Areas of SOZ were identified using hybrid PET/MRI and concordance with SEEG was evaluated. Logistic regression analysis was used to predict the presence of a favorable outcome with the coherence of concordance of PET/MRI and SEEG. RESULTS Hybrid PET/MRI (including visual PET, MRI, plus MI Neuro) identified SOZ lesions in 38 epilepsy patients (90.47 %). PET/MRI showed the same SOZ localization with SEEG in 29 patients (69.05 %), which was considered to be concordant. The concordance between the PET/MRI and SEEG findings was significantly predictive of a successful surgery outcome (odds ratio = 20.41; 95 % CI = 2.75-151.4, P = 0.003**). CONCLUSION Hybrid PET/MRI combined visual PET, multiple sequences MRI and SPM PET helps identify epilepsy lesions particularly in subtle hypometabolic areas. Patients with concordant epileptic lesion localization on PET/MRI and SEEG demonstrated a more favorable outcome than those with inconsistent localization between modalities.
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Affiliation(s)
- Miao Zhang
- Department of Nuclear Medicine, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Wei Liu
- Department of Neurosurgery, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Peng Huang
- Department of Neurosurgery, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xiaozhu Lin
- Department of Nuclear Medicine, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xinyun Huang
- Department of Nuclear Medicine, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Hongping Meng
- Department of Nuclear Medicine, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jin Wang
- Department of Nuclear Medicine, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Kejia Hu
- Department of Neurosurgery, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jian Li
- Clinical Research Center, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Mu Lin
- MR Collaborations, Siemens Healthcare Ltd., Shanghai, China
| | - Bomin Sun
- Department of Neurosurgery, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Shikun Zhan
- Department of Neurosurgery, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
| | - Biao Li
- Department of Nuclear Medicine, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
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Demuru M, Kalitzin S, Zweiphenning W, van Blooijs D, Van't Klooster M, Van Eijsden P, Leijten F, Zijlmans M. The value of intra-operative electrographic biomarkers for tailoring during epilepsy surgery: from group-level to patient-level analysis. Sci Rep 2020; 10:14654. [PMID: 32887896 PMCID: PMC7474097 DOI: 10.1038/s41598-020-71359-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 04/23/2020] [Indexed: 01/08/2023] Open
Abstract
Signal analysis biomarkers, in an intra-operative setting, may be complementary tools to guide and tailor the resection in drug-resistant focal epilepsy patients. Effective assessment of biomarker performances are needed to evaluate their clinical usefulness and translation. We defined a realistic ground-truth scenario and compared the effectiveness of different biomarkers alone and combined to localize epileptogenic tissue during surgery. We investigated the performances of univariate, bivariate and multivariate signal biomarkers applied to 1 min inter-ictal intra-operative electrocorticography to discriminate between epileptogenic and non-epileptogenic locations in 47 drug-resistant people with epilepsy (temporal and extra-temporal) who had been seizure-free one year after the operation. The best result using a single biomarker was obtained using the phase-amplitude coupling measure for which the epileptogenic tissue was localized in 17 out of 47 patients. Combining the whole set of biomarkers provided an improvement of the performances: 27 out of 47 patients. Repeating the analysis only on the temporal-lobe resections we detected the epileptogenic tissue in 29 out of 30 combining all the biomarkers. We suggest that the assessment of biomarker performances on a ground-truth scenario is required to have a proper estimate on how biomarkers translate into clinical use. Phase-amplitude coupling seems the best performing single biomarker and combining biomarkers improves localization of epileptogenic tissue. Performance achieved is not adequate as a tool in the operation theater yet, but it can improve the understanding of pathophysiological process.
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Affiliation(s)
- Matteo Demuru
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands.
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Stiliyan Kalitzin
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Willemiek Zweiphenning
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dorien van Blooijs
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Maryse Van't Klooster
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Pieter Van Eijsden
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Frans Leijten
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Maeike Zijlmans
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
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Guo ZH, Zhao BT, Toprani S, Hu WH, Zhang C, Wang X, Sang L, Ma YS, Shao XQ, Razavi B, Parvizi J, Fisher R, Zhang JG, Zhang K. Epileptogenic network of focal epilepsies mapped with cortico-cortical evoked potentials. Clin Neurophysiol 2020; 131:2657-2666. [PMID: 32957038 DOI: 10.1016/j.clinph.2020.08.012] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 06/23/2020] [Accepted: 08/05/2020] [Indexed: 12/26/2022]
Abstract
OBJECTIVE The goal of this study was to investigate the spatial extent and functional organization of the epileptogenic network through cortico-cortical evoked potentials (CCEPs) in patients being evaluated with intracranial stereoelectroencephalography. METHODS We retrospectively included 25 patients. We divided the recorded sites into three regions: epileptogenic zone (EZ); propagation zone (PZ); and noninvolved zone (NIZ). The root mean square of the amplitudes was calculated to reconstruct effective connectivity network. We also analyzed the N1/N2 amplitudes to explore the responsiveness influenced by epileptogenicity. Prognostic analysis was performed by comparing intra-region and inter-region connectivity between seizure-free and non-seizure-free groups. RESULTS Our results confirmed that stimulation of the EZ caused the strongest responses on other sites within and outside the EZ. Moreover, we found a hierarchical connectivity pattern showing the highest connectivity strength within EZ, and decreasing connectivity gradient from EZ, PZ to NIZ. Prognostic analysis indicated a stronger intra-EZ connection in the seizure-free group. CONCLUSION The EZ showed highest excitability and dominantly influenced other regions. Quantitative CCEPs can be useful in mapping epileptic networks and predicting surgical outcome. SIGNIFICANCE The generated computational connectivity model may enhance our understanding of epileptogenic networks and provide useful information for surgical planning and prognosis prediction.
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Affiliation(s)
- Zhi-Hao Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Bao-Tian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Sheela Toprani
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Wen-Han Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lin Sang
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Yan-Shan Ma
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Xiao-Qiu Shao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Babak Razavi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Josef Parvizi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Robert Fisher
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, CA, USA.
| | - Jian-Guo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China.
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China.
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99
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Wang J, Shan Y, Dai J, Cui B, Shang K, Yang H, Chen Z, Shan B, Zhao G, Lu J. Altered coupling between resting-state glucose metabolism and functional activity in epilepsy. Ann Clin Transl Neurol 2020; 7:1831-1842. [PMID: 32860354 PMCID: PMC7545617 DOI: 10.1002/acn3.51168] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 06/22/2020] [Accepted: 07/30/2020] [Indexed: 11/07/2022] Open
Abstract
OBJECTIVE Altered functional activities and hypometabolism have been found in medial temporal lobe epilepsy patients with hippocampal sclerosis (mTLE-HS). Hybrid PET/MR scanners provide opportunities to explore the relationship between resting-state energy consumption and functional activities, but whether repeated seizures disturb the bioenergetic coupling and its relationship with seizure outcomes remain unknown. METHODS 18 F-FDG PET and resting-state functional MRI (rs-fMRI) scans were performed with hybrid PET/MR in 26 patients with mTLE-HS and in healthy controls. Energy consumption was quantified by 18 F-FDG standardized uptake value ratio(SUVR) relative to cerebellum. Spontaneous neural activities were estimated using regional homogeneity (ReHo), fractional amplitude of low frequency fluctuations (fALFF) from rs-fMRI. Between-group differences in SUVR and rs-fMRI derived metrics were evaluated by two-sample t test. Voxel-wise spatial correlations were explored between SUVR and ReHo, fALFF across gray matter and compared between groups. Furthermore, the relationships between altered fALFF/SUVR and ReHo/SUVR coupling and surgical outcomes were evaluated. RESULTS Both the patients and healthy controls showed significant positive correlations between SUVR and rs-fMRI metrics. Spatial correlations between SUVR and fMRI-derived metrics across gray matter were significantly higher in patients with mTLE-HS compared with healthy controls (fALFF/SUVR, P < 0.001; ReHo/SUVR, P = 0.022). Higher fALFF/SUVR couplings were found in patients who had Engel class IA after surgery than all other (P = 0.025), while altered ReHo/SUVR couplings (P = 0.097) were not. CONCLUSION These findings demonstrated altered bioenergetic coupling across gray matter and its relationship with seizure outcomes, which may provide novel insights into pathogenesis of mTLE-HS and potential biomarkers for epilepsy surgery planning.
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Affiliation(s)
- Jingjuan Wang
- Department of Nuclear MedicineXuanwu Hospital Capital Medical UniversityBeijingChina
| | - Yi Shan
- Department of RadiologyXuanwu Hospital Capital Medical UniversityBeijingChina
- Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
| | - Jindong Dai
- Department of NeurosurgeryBeijing Haidian Section of Peking University Third HospitalBeijingChina
- Department of Functional NeurosurgeryXuanwu Hospital Capital Medical UniversityBeijingChina
| | - Bixiao Cui
- Department of Nuclear MedicineXuanwu Hospital Capital Medical UniversityBeijingChina
| | - Kun Shang
- Department of Nuclear MedicineXuanwu Hospital Capital Medical UniversityBeijingChina
| | - Hongwei Yang
- Department of Nuclear MedicineXuanwu Hospital Capital Medical UniversityBeijingChina
| | | | - Baoci Shan
- Division of Nuclear Technology and ApplicationsInstitute of High Energy PhysicsChinese Academy of SciencesBeijingChina
- Beijing Engineering Research Center of Radiographic Techniques and EquipmentBeijingChina
- CAS Centre for Excellence in Brain Science and Intelligent TechnologyShanghaiChina
| | - Guoguang Zhao
- Department of NeurosurgeryXuanwu HospitalCapital Medical UniversityBeijingChina
| | - Jie Lu
- Department of Nuclear MedicineXuanwu Hospital Capital Medical UniversityBeijingChina
- Department of RadiologyXuanwu Hospital Capital Medical UniversityBeijingChina
- Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
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100
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Charupanit K, Sen-Gupta I, Lin JJ, Lopour BA. Amplitude of high frequency oscillations as a biomarker of the seizure onset zone. Clin Neurophysiol 2020; 131:2542-2550. [PMID: 32927209 DOI: 10.1016/j.clinph.2020.07.021] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 07/13/2020] [Accepted: 07/19/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVE Studies of high frequency oscillations (HFOs) in epilepsy have primarily tested the HFO rate as a biomarker of the seizure onset zone (SOZ), but the rate varies over time and is not robust for all individual subjects. As an alternative, we tested the performance of HFO amplitude as a potential SOZ biomarker using two automated detection algorithms. METHOD HFOs were detected in intracranial electroencephalogram (iEEG) from 11 patients using a machine learning algorithm and a standard amplitude-based algorithm. For each detector, SOZ and non-SOZ channels were classified using the rate and amplitude of high frequency events, and performance was compared using receiver operating characteristic curves. RESULTS The amplitude of detected events was significantly higher in SOZ. Across subjects, amplitude more accurately classified SOZ/non-SOZ than rate (higher values of area under the ROC curve and sensitivity, and lower false positive rates). Moreover, amplitude was more consistent across segments of data, indicated by lower coefficient of variation. CONCLUSION As an SOZ biomarker, HFO amplitude offers advantages over HFO rate: it exhibits higher classification accuracy, more consistency over time, and robustness to parameter changes. SIGNIFICANCE This biomarker has the potential to increase the generalizability of HFOs and facilitate clinical implementation as a tool for SOZ localization.
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Affiliation(s)
- Krit Charupanit
- University of California, Irvine, Biomedical Engineering, 3120 Natural Sciences II, University of California, Irvine, CA 92697, USA
| | - Indranil Sen-Gupta
- University of California Irvine Medical Center, Neurology, 101 The City Drive South, Pavilion 1, Orange, CA 92868, USA
| | - Jack J Lin
- University of California, Irvine, Neurology, 101 The City Drive South, Building 22C, 2nd Floor, RT13, Orange, CA 92602, USA
| | - Beth A Lopour
- University of California, Irvine, Biomedical Engineering, 3120 Natural Sciences II, University of California, Irvine, CA 92697, USA.
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