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2. Factors associated with poor sleep in children with drug‐resistant epilepsy.

Author

Proost, Renee, Cleeren, Evy, Jansen, Bastiaan, Lagae, Lieven, Van Paesschen, Wim, and Jansen, Katrien

Subjects
*SLOW wave sleep, *SLEEP interruptions, *SLEEP, *CHILDREN with epilepsy, *RAPID eye movement sleep
Abstract

Objective: We aimed to investigate sleep in children with drug‐resistant epilepsy (DRE), including developmental and epileptic encephalopathies (DEEs). Next, we examined differences in sleep macrostructure and microstructure and questionnaire outcomes between children with well‐controlled epilepsy (WCE) and children with DRE. Furthermore, we wanted to identify factors associated with poor sleep outcome in these children, as some factors might be targets to improve epilepsy and neurodevelopmental outcomes. Methods: A cross‐sectional study was conducted in children 4 to 18‐years‐old. Children without epilepsy, with WCE, and with DRE were included. Overnight electroencephalography (EEG), including chin electromyography and electrooculography, to allow sleep staging, was performed. Parents were asked to fill out a sleep questionnaire. Classical five‐stage sleep scoring was performed manually, spindles were automatically counted, and slow wave activity (SWA) in the first and last hour of slow wave sleep was calculated. Results: One hundred eighty‐two patients were included: 48 without epilepsy, 75 with WCE, and 59 with DRE. We found that children with DRE have significantly lower sleep efficiency (SE%), less time spent in rapid eye movement (REM) sleep, fewer sleep spindles, and a lower SWA decline over the night compared to children with WCE. Subjectively more severe sleep problems were reported by the caregivers and more daytime sleepiness was present in children with DRE. Least absolute shrinkage and selection operator (LASSO) regression showed that multifocal interictal epileptiform discharges (IEDs), benzodiazepine treatment, and longer duration of epilepsy were associated with lower SE% and lower REM sleep time. The presence of multifocal discharges and cerebral palsy was associated with fewer spindles. Benzodiazepine treatment, drug resistance, seizures during sleep, intellectual disability, and older age were associated with lower SWA decline. Significance: Both sleep macrostructure and microstructure are severely impacted in children with DRE, including those with DEEs. Epilepsy parameters play a distinct role in the disruption REM sleep, spindle count, and SWA decline. [ABSTRACT FROM AUTHOR]

Published
2024
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5. Seizure outcome and use of antiepileptic drugs after epilepsy surgery according to histopathological diagnosis: a retrospective multicentre cohort study

Author

Aichholzer, Martin, Amorim, Isabel, Aparicio, Javier, Aronica, Eleonora, Arzimanoglou, Alexis, Barba, Carmen, Beck, Jürgen, Becker, Albert, Beckervordersandforth, Jan C, Bien, Christian G, Blümcke, Ingmar, Bodi, Istvan, Braun, Kees PJ, Catenoix, Helene, Chassoux, Francine, Chipaux, Mathilde, Cloppenborg, Thomas, Coras, Roland, Cross, J Helen, De Palma, Luca, De Tisi, Jane, Deleo, Francesco, Devaux, Bertrand, Di Gennaro, Giancarlo, Dorfmüller, Georg, Duncan, John S, Elger, Christian, Ernst, Katharina, Esposito, Vincenzo, Feucht, Martha, Gadze, Zeljka Petelin, Garbelli, Rita, Geleijns, Karin, Gil-Nagel, Antonio, Grote, Alexander, Grunwald, Thomas, Guerrini, Renzo, Hamer, Hajo, Honavar, Mrinalini, Jacques, Thomas S, Jakovcevic, Antonia, Jutila, Leena, Kalina, Adam, Kälviäinen, Reetta, Klein, Karl Martin, Koenig, Kristina, Krsek, Pavel, Kudernatsch, Manfred, Kudr, Martin, Lamberink, Herm J, Malmgren, Kristina, Marusic, Petr, Melikyan, Armen, Menzler, Katja, Noachtar, Soheyl, Otte, Willem M, Özkara, Çiğdem, Pieper, Tom, Pimentel, Jose, Raicevic, Savo, Rheims, Sylvain, Ribeiro, Joana, Rosenow, Felix, Rössler, Karl, Rydenhag, Bertil, Sales, Francisco, San Antonio-Arce, Victoria, Schaller, Karl Lothar, Schijns, Olaf, Scholl, Theresa, Schramm, Johannes, Schulze-Bonhage, Andreas, Sciot, Raf, Seeck, Margitta, Shishkina, Lyudmila, Sokic, Dragoslav, Specchio, Nicola, Theys, Tom, Thom, Maria, Delgado, Rafael Toledano, Toulouse, Joseph, Uzan, Mustafa, van Loon, Johannes, Van Paesschen, Wim, von Oertzen, Tim J, Jansen, Floor, Leijten, Frans, van Rijen, Peter, Spliet, Wim GM, Mühlebner, Angelika, Kasper, Burkhard S, Fauser, Susanne, Polster, Tilman, Kalbhenn, Thilo, Delev, Daniel, McEvoy, Andrew, Miserocchi, Anna, Landré, Elisabeth, Turak, Bares, Varlet, Pascale, Ferrand-Sorbets, Sarah, Fohlen, Martine, Bulteau, Christine, Edelvik, Anna, Shah, Mukesch J, Scheiwe, Christian, Delicado, Eva Gutierrez, Tisdall, Martin, Eltze, Christin, Akkol, Serdar, Deniz, Kaancan, Oz, Buge, Holthausen, Hans, Hartlieb, Till, Staudt, Martin, Casciato, Sara, Quarato, Pier P, Giangaspero, Felice, Streichenberger, Nathalie, Guenot, Marc, Isnard, Jean, Valentijn, Antonio, Chang, Amanda, Mullatti, Nandini, Zamecnik, Josef, Zarubova, Jana, Tomasek, Martin, Immonen, Arto, Saarela, Anni, Rauramaa, Tuomas, Lobrinus, Johannes A, Egervari, Kristof, Momjian, Shahan, Harti, Elisabeth, Lohr, Hannah, Kroell, Judith, Vermeulen, Lynn, Cleeren, Evy, Vlasov, Pavel, Kozlova, Antonia, Vorobyev, Alexey, Goeppel, Gudrun, Samueli, Sharon, Czech, Thomas, Hainfellner, Johannes, Puttinger, Gertraud, Schwarz, Gabriele, Stefanits, Harald, Weis, Serge, Spreafico, Roberto, Villani, Flavio, Rossini, Laura, Hermsen, Anke, Knake, Susanne, Nimsky, Christopher, Carl, Barbara, Belohlavkova, Anezka, Benova, Barbora, Bisschop, Jeroen, Colon, Albert, van Kranen-Mastenbroek, Vivianne, Rouhl, Rob PW, Hoogland, Govert, Rumiá, Jordi, Ramírez-Camacho, Alia, Candela-Cantó, Santiago, Ostrowsky-Coste, Karine, Panagiotakaki, Eleni, Montavont, Alexandra, Kosal, Pascale Keo, Gokce-Samar, Zeynep, Milleret, Clara, Buccoliero, Anna M, Giordano, Flavio, Sulentic, Vlatko, Mrak, Goran, Desnica, Andrej, CarfíPavia, Giusy, De Benedictis, Alessandro, Marras, Carlo E, Bascarevic, Vladimir, Vojvodic, Nikola, Ristic, Aleksandar, Rebelo, Olinda, Aledo-Serrano, Angel, Garcia-Morales, Irene, Anciones, Carla, and Braun, Kees P J

Published
2020
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8. Comparative validation of automated presurgical tractography based on constrained spherical deconvolution and diffusion tensor imaging with direct electrical stimulation.

Author

Radwan, Ahmed Mohamed, Emsell, Louise, Vansteelandt, Kristof, Cleeren, Evy, Peeters, Ronald, De Vleeschouwer, Steven, Theys, Tom, Dupont, Patrick, and Sunaert, Stefan

Subjects
DIFFUSION tensor imaging, ELECTRIC stimulation, BODY surface mapping, PYRAMIDAL tract, WHITE matter (Nerve tissue), RECEIVER operating characteristic curves
Abstract

Objectives: Accurate presurgical brain mapping enables preoperative risk assessment and intraoperative guidance. This cross‐sectional study investigated whether constrained spherical deconvolution (CSD) methods were more accurate than diffusion tensor imaging (DTI)‐based methods for presurgical white matter mapping using intraoperative direct electrical stimulation (DES) as the ground truth. Methods: Five different tractography methods were compared (three DTI‐based and two CSD‐based) in 22 preoperative neurosurgical patients undergoing surgery with DES mapping. The corticospinal tract (CST, N = 20) and arcuate fasciculus (AF, N = 7) bundles were reconstructed, then minimum distances between tractograms and DES coordinates were compared between tractography methods. Receiver‐operating characteristic (ROC) curves were used for both bundles. For the CST, binary agreement, linear modeling, and posthoc testing were used to compare tractography methods while correcting for relative lesion and bundle volumes. Results: Distance measures between 154 positive (functional response, pDES) and negative (no response, nDES) coordinates, and 134 tractograms resulted in 860 data points. Higher agreement was found between pDES coordinates and CSD‐based compared to DTI‐based tractograms. ROC curves showed overall higher sensitivity at shorter distance cutoffs for CSD (8.5 mm) compared to DTI (14.5 mm). CSD‐based CST tractograms showed significantly higher agreement with pDES, which was confirmed by linear modeling and posthoc tests (PFWE <.05). Conclusions: CSD‐based CST tractograms were more accurate than DTI‐based ones when validated using DES‐based assessment of motor and sensory function. This demonstrates the potential benefits of structural mapping using CSD in clinical practice. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Deep Brain Stimulation of the Anterior Nucleus of the Thalamus in Drug-Resistant Epilepsy in the MORE Multicenter Patient Registry

Author

Peltola, Jukka, Colon, Albert J., Pimentel, José, Coenen, Volker A., Gil-Nagel, Antonio, Gonçalves Ferreira, Antonio, Lehtimäki, Kai, Ryvlin, Philippe, Taylor, Rod S., Ackermans, Linda, Ardesch, Jacqueline, Bentes, Carla, Bosak, Magdalena, Burneo, Jorge G., Chamadoira, Clara, Elger, Christian E., Erőss, Loránd, Fabo, Dániel, Faulkner, Howard, Gawlowicz, Jacek, Gharabaghi, Alireza, Iacoangeli, Maurizio, Janszky, Jozsef, Järvenpää, Soila, Kaufmann, Elisabeth, Kho, Kuan H., Kumlien, Eva, Laufs, Helmut, Lettieri, Christian, Linhares, Paulo, Noachtar, Soheyl, Parrent, Andrew, Pataraia, Ekaterina, Patel, Nikunj K., Peralta, Ana Rita, Rácz, Attila, Campos, Alexandre Rainha, Rego, Ricardo, Ricciuti, Riccardo A., Rona, Sabine, Rouhl, Rob P.W., Schulze-Bonhage, Andreas, Schuurman, Rick, Sprengers, Mathieu, Sufianov, Albert, Temel, Yasin, Theys, Tom, Van Paesschen, Wim, Van Roost, Dirk, Vaz, Rui, Vonck, Kristl, Wagner, Louis, Zwemmer, Jack, Abouihia, Abdallah, Brionne, Thomas C., Gielen, Frans, Boon, Paul A.J.M., Amorim, Isabel, Aull-Watschinger, Susanne, BALÁS, István, BÓNÉ, Beáta, Brown, Suzan, Cesaroni, Elisabetta, Cleeren, Evy, Dec-Ćwiek, Małgorzata, Eleopra, Dr. Roberto, Falk, Daniela, Franco, Ana, Hackelberg, Birte, Hampel, Kevin, Hirsch, Dr. Martin, Meyne, Johannes Konrad, KOVÁCS, Norbert, Lang, Nicolas, Möddel, Gabriel, Moeller, Bettina, Mondani, Dr. Massimo, Nass, Robert D, Novak, Klaus, Obszanska, Dr. Katarzyna, Orlov, Alexander, Pietraszko, Wojciech, Scerrati, Massimo, Shapkin, Andrey, Skripnikov, Alexander, Van Hoylandt, Anais, Viebahn, Bettina, Wieszmuellner, Sonja, and Zamponi, Nelia

Published
2023
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17. The power of ECG in multimodal patient‐specific seizure monitoring: Added value to an EEG‐based detector using limited channels

Author

Vandecasteele, Kaat, primary, De Cooman, Thomas, additional, Chatzichristos, Christos, additional, Cleeren, Evy, additional, Swinnen, Lauren, additional, Macea Ortiz, Jaiver, additional, Van Huffel, Sabine, additional, Dümpelmann, Matthias, additional, Schulze‐Bonhage, Andreas, additional, De Vos, Maarten, additional, Van Paesschen, Wim, additional, and Hunyadi, Borbála, additional

Published
2021
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18. The power of ECG in multimodal patient-specific seizure monitoring: Added value to an EEG-based detector using limited channels

Author

Vandecasteele, Kaat (author), De Cooman, Thomas (author), Chatzichristos, Christos (author), Cleeren, Evy (author), Swinnen, Lauren (author), Ortiz, Jaiver Macea (author), Van Huffel, Sabine (author), Dümpelmann, Matthias (author), Schulze- Bonhage, Andreas (author), De Vos, Maarten (author), Van Paesschen, Wim (author), Hunyadi, B. (author), Vandecasteele, Kaat (author), De Cooman, Thomas (author), Chatzichristos, Christos (author), Cleeren, Evy (author), Swinnen, Lauren (author), Ortiz, Jaiver Macea (author), Van Huffel, Sabine (author), Dümpelmann, Matthias (author), Schulze- Bonhage, Andreas (author), De Vos, Maarten (author), Van Paesschen, Wim (author), and Hunyadi, B. (author)

Abstract

Objective: Wearable seizure detection devices could provide more reliable seizure documentation outside the hospital compared to seizure self-reporting by patients, which is the current standard. Previously, during the SeizeIT1 project, we studied seizure detection based on behind-the-ear electroencephalography (EEG). However, the obtained sensitivities were too low for practical use, because not all seizures are associated with typical ictal EEG patterns. Therefore, in this paper, we aim to develop a multimodal automated seizure detection algorithm integrating behind-the-ear EEG and electrocardiography (ECG) for detecting focal seizures. In this framework, we quantified the added value of ECG to behind-the-ear EEG. Methods: This study analyzed three multicenter databases consisting of 135 patients having focal epilepsy and a total of 896 seizures. A patient-specific multimodal automated seizure detection algorithm was developed using behind-the-ear/temporal EEG and single-lead ECG. The EEG and ECG data were processed separately using machine learning methods. A late integration approach was applied for fusing those predictions. Results: The multimodal algorithm outperformed the EEG-based algorithm in two of three databases, with an increase of 11% and 8% in sensitivity for the same false alarm rate. Significance: ECG can be of added value to an EEG-based seizure detection algorithm using only behind-the-ear/temporal lobe electrodes for patients with focal epilepsy., Circuits and Systems

Published
2021
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20. Seizure outcome and use of antiepileptic drugs after epilepsy surgery according to histopathological diagnosis: a retrospective multicentre cohort study

Author

Lamberink, Herm J, primary, Otte, Willem M, additional, Blümcke, Ingmar, additional, Braun, Kees P J, additional, Aichholzer, Martin, additional, Amorim, Isabel, additional, Aparicio, Javier, additional, Aronica, Eleonora, additional, Arzimanoglou, Alexis, additional, Barba, Carmen, additional, Beck, Jürgen, additional, Becker, Albert, additional, Beckervordersandforth, Jan C, additional, Bien, Christian G, additional, Bodi, Istvan, additional, Braun, Kees PJ, additional, Catenoix, Helene, additional, Chassoux, Francine, additional, Chipaux, Mathilde, additional, Cloppenborg, Thomas, additional, Coras, Roland, additional, Cross, J Helen, additional, De Palma, Luca, additional, De Tisi, Jane, additional, Deleo, Francesco, additional, Devaux, Bertrand, additional, Di Gennaro, Giancarlo, additional, Dorfmüller, Georg, additional, Duncan, John S, additional, Elger, Christian, additional, Ernst, Katharina, additional, Esposito, Vincenzo, additional, Feucht, Martha, additional, Gadze, Zeljka Petelin, additional, Garbelli, Rita, additional, Geleijns, Karin, additional, Gil-Nagel, Antonio, additional, Grote, Alexander, additional, Grunwald, Thomas, additional, Guerrini, Renzo, additional, Hamer, Hajo, additional, Honavar, Mrinalini, additional, Jacques, Thomas S, additional, Jakovcevic, Antonia, additional, Jutila, Leena, additional, Kalina, Adam, additional, Kälviäinen, Reetta, additional, Klein, Karl Martin, additional, Koenig, Kristina, additional, Krsek, Pavel, additional, Kudernatsch, Manfred, additional, Kudr, Martin, additional, Lamberink, Herm J, additional, Malmgren, Kristina, additional, Marusic, Petr, additional, Melikyan, Armen, additional, Menzler, Katja, additional, Noachtar, Soheyl, additional, Özkara, Çiğdem, additional, Pieper, Tom, additional, Pimentel, Jose, additional, Raicevic, Savo, additional, Rheims, Sylvain, additional, Ribeiro, Joana, additional, Rosenow, Felix, additional, Rössler, Karl, additional, Rydenhag, Bertil, additional, Sales, Francisco, additional, San Antonio-Arce, Victoria, additional, Schaller, Karl Lothar, additional, Schijns, Olaf, additional, Scholl, Theresa, additional, Schramm, Johannes, additional, Schulze-Bonhage, Andreas, additional, Sciot, Raf, additional, Seeck, Margitta, additional, Shishkina, Lyudmila, additional, Sokic, Dragoslav, additional, Specchio, Nicola, additional, Theys, Tom, additional, Thom, Maria, additional, Delgado, Rafael Toledano, additional, Toulouse, Joseph, additional, Uzan, Mustafa, additional, van Loon, Johannes, additional, Van Paesschen, Wim, additional, von Oertzen, Tim J, additional, Jansen, Floor, additional, Leijten, Frans, additional, van Rijen, Peter, additional, Spliet, Wim GM, additional, Mühlebner, Angelika, additional, Kasper, Burkhard S, additional, Fauser, Susanne, additional, Polster, Tilman, additional, Kalbhenn, Thilo, additional, Delev, Daniel, additional, McEvoy, Andrew, additional, Miserocchi, Anna, additional, Landré, Elisabeth, additional, Turak, Bares, additional, Varlet, Pascale, additional, Ferrand-Sorbets, Sarah, additional, Fohlen, Martine, additional, Bulteau, Christine, additional, Edelvik, Anna, additional, Shah, Mukesch J, additional, Scheiwe, Christian, additional, Delicado, Eva Gutierrez, additional, Tisdall, Martin, additional, Eltze, Christin, additional, Akkol, Serdar, additional, Deniz, Kaancan, additional, Oz, Buge, additional, Holthausen, Hans, additional, Hartlieb, Till, additional, Staudt, Martin, additional, Casciato, Sara, additional, Quarato, Pier P, additional, Giangaspero, Felice, additional, Streichenberger, Nathalie, additional, Guenot, Marc, additional, Isnard, Jean, additional, Valentijn, Antonio, additional, Chang, Amanda, additional, Mullatti, Nandini, additional, Zamecnik, Josef, additional, Zarubova, Jana, additional, Tomasek, Martin, additional, Immonen, Arto, additional, Saarela, Anni, additional, Rauramaa, Tuomas, additional, Lobrinus, Johannes A, additional, Egervari, Kristof, additional, Momjian, Shahan, additional, Harti, Elisabeth, additional, Lohr, Hannah, additional, Kroell, Judith, additional, Vermeulen, Lynn, additional, Cleeren, Evy, additional, Vlasov, Pavel, additional, Kozlova, Antonia, additional, Vorobyev, Alexey, additional, Goeppel, Gudrun, additional, Samueli, Sharon, additional, Czech, Thomas, additional, Hainfellner, Johannes, additional, Puttinger, Gertraud, additional, Schwarz, Gabriele, additional, Stefanits, Harald, additional, Weis, Serge, additional, Spreafico, Roberto, additional, Villani, Flavio, additional, Rossini, Laura, additional, Hermsen, Anke, additional, Knake, Susanne, additional, Nimsky, Christopher, additional, Carl, Barbara, additional, Belohlavkova, Anezka, additional, Benova, Barbora, additional, Bisschop, Jeroen, additional, Colon, Albert, additional, van Kranen-Mastenbroek, Vivianne, additional, Rouhl, Rob PW, additional, Hoogland, Govert, additional, Rumiá, Jordi, additional, Ramírez-Camacho, Alia, additional, Candela-Cantó, Santiago, additional, Ostrowsky-Coste, Karine, additional, Panagiotakaki, Eleni, additional, Montavont, Alexandra, additional, Kosal, Pascale Keo, additional, Gokce-Samar, Zeynep, additional, Milleret, Clara, additional, Buccoliero, Anna M, additional, Giordano, Flavio, additional, Sulentic, Vlatko, additional, Mrak, Goran, additional, Desnica, Andrej, additional, CarfíPavia, Giusy, additional, De Benedictis, Alessandro, additional, Marras, Carlo E, additional, Bascarevic, Vladimir, additional, Vojvodic, Nikola, additional, Ristic, Aleksandar, additional, Rebelo, Olinda, additional, Aledo-Serrano, Angel, additional, Garcia-Morales, Irene, additional, and Anciones, Carla, additional

Published
2020
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23. Personalizing Heart Rate-Based Seizure Detection Using Supervised SVM Transfer Learning

Author

De Cooman, Thomas (author), Vandecasteele, Kaat (author), Varon, Carolina (author), Hunyadi, B. (author), Cleeren, Evy (author), Van Paesschen, Wim (author), Van Huffel, Sabine (author), De Cooman, Thomas (author), Vandecasteele, Kaat (author), Varon, Carolina (author), Hunyadi, B. (author), Cleeren, Evy (author), Van Paesschen, Wim (author), and Van Huffel, Sabine (author)

Abstract

Objective: Automated seizure detection is a key aspect of wearable seizure warning systems. As a result, the quality of life of refractory epilepsy patients could be improved. Most state-of-the-art algorithms for heart rate-based seizure detection use a so-called patient-independent approach, which do not take into account patient-specific data during algorithm training. Although such systems are easy to use in practice, they lead to many false detections as the ictal heart rate changes are patient-dependent. In practice, only a limited amount of accurately annotated patient data is typically available, which makes it difficult to create fully patient-specific algorithms. Methods: In this context, this study proposes for the first time a new transfer learning approach that allows to personalize heart rate-based seizure detection by using only a couple of days of data per patient. The algorithm was evaluated on 2,172 h of single-lead ECG data from 24 temporal lobe epilepsy patients including 227 focal impaired awareness seizures. Results: The proposed personalized approach resulted in an overall sensitivity of 71% with 1.9 false detections per hour. This is an average decrease in false detection rate of 37% compared to the reference patient-independent algorithm using only a limited amount of personal seizure data. The proposed transfer learning approach adapts faster and more robustly to patient-specific characteristics than other alternatives for personalization in the literature. Conclusion: The proposed method allows an easy implementable solution to personalize heart rate-based seizure detection, which can improve the quality of life of refractory epilepsy patients when used as part of a multimodal seizure detection system., Circuits and Systems

Published
2020
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24. Visual seizure annotation and automated seizure detection using behind-the-ear electroencephalographic channels

Author

Vandecasteele, Kaat (author), De Cooman, Thomas (author), Dan, Jonathan (author), Cleeren, Evy (author), Van Huffel, Sabine (author), Hunyadi, B. (author), Van Paesschen, Wim (author), Vandecasteele, Kaat (author), De Cooman, Thomas (author), Dan, Jonathan (author), Cleeren, Evy (author), Van Huffel, Sabine (author), Hunyadi, B. (author), and Van Paesschen, Wim (author)

Abstract

Objective: Seizure diaries kept by patients are unreliable. Automated electroencephalography (EEG)-based seizure detection systems are a useful support tool to objectively detect and register seizures during long-term video-EEG recording. However, this standard full scalp-EEG recording setup is of limited use outside the hospital, and a discreet, wearable device is needed for capturing seizures in the home setting. We are developing a wearable device that records EEG with behind-the-ear electrodes. In this study, we determined whether the recognition of ictal patterns using only behind-the-ear EEG channels is possible. Second, an automated seizure detection algorithm was developed using only those behind-the-ear EEG channels. Methods: Fifty-four patients with a total of 182 seizures, mostly temporal lobe epilepsy (TLE), and 5284 hours of data, were recorded with a standard video-EEG at University Hospital Leuven. In addition, extra behind-the-ear EEG channels were recorded. First, a neurologist was asked to annotate behind-the-ear EEG segments containing selected seizure and nonseizure fragments. Second, a data-driven algorithm was developed using only behind-the-ear EEG. This algorithm was trained using data from other patients (patient-independent model) or from the same patient (patient-specific model). Results: The visual recognition study resulted in 65.7% sensitivity and 94.4% specificity. By using those seizure annotations, the automated algorithm obtained 64.1% sensitivity and 2.8 false-positive detections (FPs)/24 hours with the patient-independent model. The patient-specific model achieved 69.1% sensitivity and 0.49 FPs/24 hours. Significance: Visual recognition of ictal EEG patterns using only behind-the-ear EEG is possible in a significant number of patients with TLE. A patient-specific seizure detection algorithm using only behind-the-ear EEG was able to detect more seizures automatically than what patients typically report, with 0.49 FPs/24 hours. W, Circuits and Systems

Published
2020
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25. Development of temporal lobe epilepsy during maintenance electroconvulsive therapy: A case of human kindling?

Author

Schotte, Caroline (author), Cleeren, Evy (author), Goffin, Karolien (author), Hunyadi, B. (author), Buggenhout, Satya (author), Van Laere, Koen (author), Van Paesschen, Wim (author), Schotte, Caroline (author), Cleeren, Evy (author), Goffin, Karolien (author), Hunyadi, B. (author), Buggenhout, Satya (author), Van Laere, Koen (author), and Van Paesschen, Wim (author)

Abstract

We describe a patient with new-onset temporal lobe epilepsy during prolonged maintenance electroconvulsive therapy. We suggest a possible causal relationship with maintenance electroconvulsive therapy through electrical kindling of the temporal lobe., Circuits and Systems

Published
2019
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31. Subclinical mesial temporal lobe activity in Alzheimer's Disease.

Author

Devulder, Astrid, Testelmans, Dries, Bossche, Maarten Van Den, Cleeren, Evy, Theys, Tom, and Van Paesschen, Wim

Abstract

Background: Animal and human studies of Alzheimer's disease (AD) demonstrated that aberrant network activity with neuronal hyperexcitability plays a role in disease pathogenesis and cognitive functioning. Suppressing network hyperexcitability with levetiracetam improved cognitive functioning in familial AD mice and executive functioning in patients with AD and epileptiform activity. Manifestations of network hyperexcitability are unsensitive biomarkers since they are mostly subclinical and not visible on scalp EEG. (Lam et al. 2019, Vossel et al. 2021, Sanchez et al. 2012). Our purpose was to identify subclinical epileptiform activity in two patients with mild cognitive impairment (MCI) and one patient with moderate AD, with a suspicion of network hyperexcitability based on either spikes on 24‐h scalp EEG or a history suspect for seizures without epileptiform discharges on scalp EEG. Method: Three patients were implanted with bilateral foramen ovale (FO) electrodes to obtain more direct measures of mesial temporal lobe epileptiform activity. Scalp EEG according to the 10‐20 system and polysomnography were simultaneously recorded in all subjects for three to five consecutive days. Polysomnography was scored according to the AASM scoring rules. Persyst 14 software was used for automatic spike detection. Result: Invasive recordings showed interictal epileptic activity in all three patients, which was occasional during wakefulness and abundant during sleep. In one patient two nocturnal unilateral mesiotemporal seizures, characterized by arousal, were recorded during N1 sleep, while at the same time no epileptiform activity was visible on scalp EEG. Conclusion: In patients with AD subclinical mesial temporal epileptiform activity can be present with a normal scalp EEG. Epileptic activity is predominantly found during sleep. Our findings suggest an important role for network hyperexcitability in AD disease pathogenesis. [ABSTRACT FROM AUTHOR]

Published
2023
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32. Comparison between Scalp EEG and Behind-the-Ear EEG for Development of a Wearable Seizure Detection System for Patients with Focal Epilepsy.

Author

Gu, Ying, Cleeren, Evy, Dan, Jonathan, Claes, Kasper, Van Paesschen, Wim, Van Huffel, Sabine, and Hunyadi, Borbála

Subjects
*ELECTROENCEPHALOGRAPHY, *WEARABLE technology, *DIAGNOSIS of epilepsy, *FAULT tolerance (Engineering), *SUPPORT vector machines
Abstract

A wearable electroencephalogram (EEG) device for continuous monitoring of patients suffering from epilepsy would provide valuable information for the management of the disease. Currently no EEG setup is small and unobtrusive enough to be used in daily life. Recording behind the ear could prove to be a solution to a wearable EEG setup. This article examines the feasibility of recording epileptic EEG from behind the ear. It is achieved by comparison with scalp EEG recordings. Traditional scalp EEG and behind-the-ear EEG were simultaneously acquired from 12 patients with temporal, parietal, or occipital lobe epilepsy. Behind-the-ear EEG consisted of cross-head channels and unilateral channels. The analysis on Electrooculography (EOG) artifacts resulting from eye blinking showed that EOG artifacts were absent on cross-head channels and had significantly small amplitudes on unilateral channels. Temporal waveform and frequency content during seizures from behind-the-ear EEG visually resembled that from scalp EEG. Further, coherence analysis confirmed that behind-the-ear EEG acquired meaningful epileptic discharges similarly to scalp EEG. Moreover, automatic seizure detection based on support vector machine (SVM) showed that comparable seizure detection performance can be achieved using these two recordings. With scalp EEG, detection had a median sensitivity of 100% and a false detection rate of 1.14 per hour, while, with behind-the-ear EEG, it had a median sensitivity of 94.5% and a false detection rate of 0.52 per hour. These findings demonstrate the feasibility of detecting seizures from EEG recordings behind the ear for patients with focal epilepsy. [ABSTRACT FROM AUTHOR]

Published
2018
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35. On the optimal <italic>z</italic>-score threshold for SISCOM analysis to localize the ictal onset zone.

Author

De Coster, Liesbeth, Van Laere, Koen, Cleeren, Evy, Baete, Kristof, Dupont, Patrick, Van Paesschen, Wim, and Goffin, Karolien E.

Subjects
DIAGNOSIS of epilepsy, EPILEPSY surgery, COMPUTED tomography, MAGNETIC resonance imaging, POSTOPERATIVE period
Abstract

Background: In epilepsy patients, SISCOM or subtraction ictal single photon emission computed tomography co-registered to magnetic resonance imaging has become a routinely used, non-invasive technique to localize the ictal onset zone (IOZ). Thresholding of clusters with a predefined number of standard deviations from normality (z-score) is generally accepted to localize the IOZ. In this study, we aimed to assess the robustness of this parameter in a group of patients with well-characterized drug-resistant epilepsy in whom the exact location of the IOZ was known after successful epilepsy surgery. Eighty patients underwent preoperative SISCOM and were seizure free in a postoperative period of minimum 1 year. SISCOMs with z-threshold 2 and 1.5 were analyzed by two experienced readers separately, blinded from the clinical ground truth data. Their reported location of the IOZ was compared with the operative resection zone. Furthermore, confidence scores of the SISCOM IOZ were compared for the two thresholds.Results: Visual reporting with a z-score threshold of 1.5 and 2 showed no statistically significant difference in localizing correspondence with the ground truth (70 vs. 72% respectively, p = 0.17). Interrater agreement was moderate (κ = 0.65) at the threshold of 1.5, but high (κ = 0.84) at a threshold of 2, where also reviewers were significantly more confident (p < 0.01).Conclusions: SISCOM is a clinically useful, routinely used modality in the preoperative work-up in many epilepsy surgery centers. We found no significant differences in localizing value of the IOZ using a threshold of 1.5 or 2, but interrater agreement and reader confidence were higher using a z-score threshold of 2. [ABSTRACT FROM AUTHOR]

Published
2018
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