Brain Modulation Laboratory, Department of Neurological Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
University of Pittsburgh Comprehensive Epilepsy Center, Pittsburgh, Pennsylvania.
JAMA Neurol. 2019 Jul 1;76(7):800-808. doi: 10.1001/jamaneurol.2019.0658.
A bidirectional brain-computer interface that performs neurostimulation has been shown to improve seizure control in patients with refractory epilepsy, but the therapeutic mechanism is unknown.
To investigate whether electrographic effects of responsive neurostimulation (RNS), identified in electrocorticographic (ECOG) recordings from the device, are associated with patient outcomes.
DESIGN, SETTING, AND PARTICIPANTS: Retrospective review of ECOG recordings and accompanying clinical meta-data from 11 consecutive patients with focal epilepsy who were implanted with a neurostimulation system between January 28, 2015, and June 6, 2017, with 22 to 112 weeks of follow-up. Recorded ECOG data were obtained from the manufacturer; additional system-generated meta-data, including recording and detection settings, were collected directly from the manufacturer's management system using an in-house, custom-built platform. Electrographic seizure patterns were identified in RNS recordings and evaluated in the time-frequency domain, which was locked to the onset of the seizure pattern.
Patterns of electrophysiological modulation were identified and then classified according to their latency of onset in relation to triggered stimulation events. Seizure control after RNS implantation was assessed by 3 main variables: mean frequency of seizure occurrence, estimated mean severity of seizures, and mean duration of seizures. Overall seizure outcomes were evaluated by the extended Personal Impact of Epilepsy Scale questionnaires, a patient-reported outcome measure of 3 domains (seizure characteristics, medication adverse effects, and quality of life), with a range of possible scores from 0 to 300 in which lower scores indicate worse status, and the Engel scale, which comprises 4 classes (I-IV) in which lower numbers indicate greater improvement.
Electrocorticographic data from 11 patients (8 female; mean [range] age, 35 [19-65] years; mean [range] duration of epilepsy, 19 [5-37] years) were analyzed. Two main categories of electrophysiological signatures of stimulation-induced modulation of the seizure network were discovered: direct and indirect effects. Direct effects included ictal inhibition and early frequency modulation but were not associated with improved clinical outcomes (odds ratio [OR], 0.67; 95% CI, 0.06-7.35; P > .99). Only indirect effects-those occurring remote from triggered stimulation-were associated with improved clinical outcomes (OR, infinity; 95% CI, -infinity to infinity; P = .02). These indirect effects included spontaneous ictal inhibition, frequency modulation, fragmentation, and ictal duration modulation.
These findings suggest that RNS effectiveness may be explained by long-term, stimulation-induced modulation of seizure network activity rather than by direct effects on each detected seizure.
已经证明，一种双向脑-机接口，通过对神经进行刺激，可改善难治性癫痫患者的癫痫控制，但治疗机制尚不清楚。
研究可响应神经刺激（RNS）的电描记图效应，这是在设备的皮质电图（ECOG）记录中发现的，与患者的结果是否相关。
设计、设置和参与者：对 11 例连续患有局灶性癫痫的患者的 ECOG 记录和伴随的临床元数据进行回顾性分析，这些患者于 2015 年 1 月 28 日至 2017 年 6 月 6 日之间植入了神经刺激系统，随访时间为 22 至 112 周。记录的 ECOG 数据是从制造商处获得的；其他系统生成的元数据，包括记录和检测设置，是直接从制造商的管理系统使用内部定制的平台收集的。在 RNS 记录中识别出电生理调节模式，并在时间-频率域中进行评估，该域与癫痫发作模式的开始锁定。
根据与触发刺激事件的关系，确定电生理调制模式的潜伏期，并对其进行分类。通过 3 个主要变量评估 RNS 植入后的癫痫控制情况：癫痫发作频率的平均值、癫痫发作严重程度的估计平均值和癫痫发作持续时间的平均值。总体癫痫发作结果通过扩展的癫痫个人影响量表问卷进行评估，这是一种患者报告的 3 个领域（癫痫发作特征、药物不良反应和生活质量）的结果测量，可能的得分范围为 0 到 300，得分越低表示状态越差，以及 Engel 量表，它包括 4 个等级（I-IV），其中较低的数字表示更大的改善。
对 11 名患者（8 名女性；平均[范围]年龄，35 [19-65]岁；平均[范围]癫痫持续时间，19 [5-37]岁）的 ECOG 数据进行了分析。发现了两种主要的刺激诱导的癫痫网络调制的电生理特征类别：直接效应和间接效应。直接效应包括癫痫发作抑制和早期频率调制，但与临床结果改善无关（比值比[OR]，0.67；95%置信区间，0.06-7.35；P>.99）。只有间接效应-那些发生在触发刺激之外的效应-与临床结果改善相关（OR，无穷大；95%置信区间，-无穷大到无穷大；P=.02）。这些间接效应包括自发性癫痫发作抑制、频率调制、碎片化和癫痫发作持续时间调制。
这些发现表明，RNS 的有效性可能可以用刺激诱导的癫痫网络活动的长期调制来解释，而不是用直接作用于每个检测到的癫痫发作来解释。
