Academic Journal
Intracranial EEG Biomarkers for Seizure Lateralization in Rapidly-Bisynchronous Epilepsy After Laser Corpus Callosotomy
| العنوان: | Intracranial EEG Biomarkers for Seizure Lateralization in Rapidly-Bisynchronous Epilepsy After Laser Corpus Callosotomy |
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| المؤلفون: | Khuvis, Simon, Hwang, Sean T., Mehta, Ashesh D. |
| المساهمون: | National Institutes of Health, United States-Israel Binational Science Foundation |
| المصدر: | Frontiers in Neurology ; volume 12 ; ISSN 1664-2295 |
| بيانات النشر: | Frontiers Media SA |
| سنة النشر: | 2021 |
| المجموعة: | Frontiers (Publisher - via CrossRef) |
| الوصف: | Objective: It has been asserted that high-frequency analysis of intracranial EEG (iEEG) data may yield information useful in localizing epileptogenic foci. Methods: We tested whether proposed biomarkers could predict lateralization based on iEEG data collected prior to corpus callosotomy (CC) in three patients with bisynchronous epilepsy, whose seizures lateralized definitively post-CC. Lateralization data derived from algorithmically-computed ictal phase-locked high gamma (PLHG), high gamma amplitude (HGA), and low-frequency (filtered) line length (LFLL), as well as interictal high-frequency oscillation (HFO) and interictal epileptiform discharge (IED) rate metrics were compared against ground-truth lateralization from post-CC ictal iEEG. Results: Pre-CC unilateral IEDs were more frequent on the more-pathologic side in all subjects. HFO rate predicted lateralization in one subject, but was sensitive to detection threshold. On pre-CC data, no ictal metric showed better predictive power than any other. All post-corpus callosotomy seizures lateralized to the pathological hemisphere using PLHG, HGA, and LFLL metrics. Conclusions: While quantitative metrics of IED rate and ictal HGA, PHLG, and LFLL all accurately lateralize based on post-CC iEEG, only IED rate consistently did so based on pre-CC data. Significance: Quantitative analysis of IEDs may be useful in lateralizing seizure pathology. More work is needed to develop reliable techniques for high-frequency iEEG analysis. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | unknown |
| DOI: | 10.3389/fneur.2021.696492 |
| DOI: | 10.3389/fneur.2021.696492/full |
| الاتاحة: | http://dx.doi.org/10.3389/fneur.2021.696492 https://www.frontiersin.org/articles/10.3389/fneur.2021.696492/full |
| Rights: | https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: | edsbas.C6C8795A |
| قاعدة البيانات: | BASE |
| DOI: | 10.3389/fneur.2021.696492 |
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