Interictal intracranial EEG asymmetry lateralizes temporal lobe epilepsy.

IF 4.1 Q1 CLINICAL NEUROLOGY
Brain communications Pub Date : 2024-08-22 eCollection Date: 2024-01-01 DOI:10.1093/braincomms/fcae284
Erin C Conrad, Alfredo Lucas, William K S Ojemann, Carlos A Aguila, Marissa Mojena, Joshua J LaRocque, Akash R Pattnaik, Ryan Gallagher, Adam Greenblatt, Ashley Tranquille, Alexandra Parashos, Ezequiel Gleichgerrcht, Leonardo Bonilha, Brian Litt, Saurabh R Sinha, Lyle Ungar, Kathryn A Davis
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引用次数: 0

Abstract

Patients with drug-resistant temporal lobe epilepsy often undergo intracranial EEG recording to capture multiple seizures in order to lateralize the seizure onset zone. This process is associated with morbidity and often ends in postoperative seizure recurrence. Abundant interictal (between-seizure) data are captured during this process, but these data currently play a small role in surgical planning. Our objective was to predict the laterality of the seizure onset zone using interictal intracranial EEG data in patients with temporal lobe epilepsy. We performed a retrospective cohort study (single-centre study for model development; two-centre study for model validation). We studied patients with temporal lobe epilepsy undergoing intracranial EEG at the University of Pennsylvania (internal cohort) and the Medical University of South Carolina (external cohort) between 2015 and 2022. We developed a logistic regression model to predict seizure onset zone laterality using several interictal EEG features derived from recent publications. We compared the concordance between the model-predicted seizure onset zone laterality and the side of surgery between patients with good and poor surgical outcomes. Forty-seven patients (30 female; ages 20-69; 20 left-sided, 10 right-sided and 17 bilateral seizure onsets) were analysed for model development and internal validation. Nineteen patients (10 female; ages 23-73; 5 left-sided, 10 right-sided, 4 bilateral) were analysed for external validation. The internal cohort cross-validated area under the curve for a model trained using spike rates was 0.83 for a model predicting left-sided seizure onset and 0.68 for a model predicting right-sided seizure onset. Balanced accuracies in the external cohort were 79.3% and 78.9% for the left- and right-sided predictions, respectively. The predicted concordance between the laterality of the seizure onset zone and the side of surgery was higher in patients with good surgical outcome. We replicated the finding that right temporal lobe epilepsy was harder to distinguish in a separate modality of resting-state functional MRI. In conclusion, interictal EEG signatures are distinct across seizure onset zone lateralities. Left-sided seizure onsets are easier to distinguish than right-sided onsets. A model trained on spike rates accurately identifies patients with left-sided seizure onset zones and predicts surgical outcome. A potential clinical application of these findings could be to either support or oppose a hypothesis of unilateral temporal lobe epilepsy when deciding to pursue surgical resection or ablation as opposed to device implantation.

发作间期颅内脑电图不对称会使颞叶癫痫偏侧。
耐药性颞叶癫痫患者通常需要进行颅内脑电图记录,以捕捉多次癫痫发作,从而确定癫痫发作区的侧位。这一过程与发病率有关,而且往往以术后癫痫复发告终。在这一过程中会捕获大量发作间期(发作间期)数据,但这些数据目前在手术规划中的作用很小。我们的目标是利用发作间期颅内脑电图数据预测颞叶癫痫患者发作起始区的侧位。我们进行了一项回顾性队列研究(单中心研究用于模型开发;双中心研究用于模型验证)。我们研究了2015年至2022年期间在宾夕法尼亚大学(内部队列)和南卡罗来纳医科大学(外部队列)接受颅内脑电图检查的颞叶癫痫患者。我们建立了一个逻辑回归模型,利用从近期出版物中获得的几个发作间期脑电图特征来预测发作起始区的侧向性。我们比较了手术效果好和手术效果差患者的模型预测发作起始区偏侧与手术侧之间的一致性。我们对 47 名患者(30 名女性;年龄 20-69 岁;20 名左侧、10 名右侧和 17 名双侧癫痫发作)进行了模型开发和内部验证分析。19 名患者(10 名女性;年龄 23-73 岁;5 名左侧,10 名右侧,4 名双侧)接受了外部验证分析。使用尖峰率训练的模型预测左侧癫痫发作的内部队列交叉验证曲线下面积为 0.83,预测右侧癫痫发作的内部队列交叉验证曲线下面积为 0.68。在外部队列中,左侧和右侧预测的平衡准确率分别为 79.3% 和 78.9%。在手术效果良好的患者中,癫痫发作区的侧位与手术侧位的预测一致性更高。我们在静息状态功能磁共振成像的单独模式中重复了右侧颞叶癫痫更难区分的发现。总之,发作间期脑电图特征在不同的发作起始区侧向是不同的。左侧发作比右侧发作更容易区分。根据尖峰率训练的模型能准确识别左侧癫痫发作起始区的患者,并预测手术结果。这些发现的一个潜在临床应用是,在决定进行手术切除或消融而不是植入设备时,可以支持或反对单侧颞叶癫痫的假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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