Diagnostic validity and safety of high-gamma language mapping with intracranial EEG

为避免难治性癫痫术后语言障碍，皮质电刺激 刺激映射(ESM)被广泛依赖于语言皮质的定位，但ESM往往在- 放电(ADS)、癫痫发作、不自主运动和疼痛，这些可能会限制标测和影响患者 安全。此外，ESM很耗时，通常会产生全有或全无的结果，提供的洞察力有限 刺激部位的功能。最后，高达30%的患者在切除后可能会有语言障碍 由ESM指导的。这些限制促使了另一种基于任务相关的映射方法 高伽马频率(≈50-200赫兹)的功率变化，这与神经元数量高度相关 射速发生变化。尽管高伽马映射(HGM)克服了ESM的上述限制， 它的临床验证仅限于ESM-HGM在具有显著差异的小病例系列中的比较 在跨中心的技术上，产生不一致的结果，方法之间存在无法解释的差异。 此外，HGM和ESM在预测术后语言方面都没有得到前瞻性的验证 硬膜下皮质脑电图(ECoG)或立体脑电波(SEEG)的损害，越来越安全 ECoG的替代方案)。这项研究总体目标是使用一个由三个大型学者组成的小财团 癫痫手术中心证明iEEG HGM对ECoG和HGM的诊断有效性和安全性 在221名前瞻性患者中进行sEEG，使用基于浏览器的创新床边HGM系统 标准化方法并跨中心共享数据。这项研究将检验HGM可以准确地 预测手术后的语言结果，但需要不同于用于解释的框架 ESM。首先，使用传统的方法来解释HGM结果，我们将检验HGM之间的一致性 和ESM，并比较它们的安全性和可行性。根据以前的研究，我们预测HGM将是一种 对ESM结果的预测很好，但并不完美。然而，我们预测，由于ESM相关的癫痫发作和 不同的标测时间，HGM将更安全，患者对其耐受性更好。第二，我们将测试模型 试图解释和调和HGM关于ESM的假阴性和假阳性，我们将 测试这些模型是否包含功能激活(HGM)和有效连接(测量 皮质诱发电位(CCEP)可以更好地预测ESM结果。第三，发展和发展 基于解剖范围和体积预测术后语言结果的测试模型 根据HGM和ESM结果，使用体素-病变-症状匹配(VLSM)进行皮质切除。自.以来 目前临床决策是基于ESM的，临床医生将对HGM视而不见，我们预测 当HGM+电极被切除时，语言缺陷的发生率将显著增加。这项研究将有一个直接的 对神经外科手术的语言映射的临床实践产生了深远的影响，同时也做出了贡献 对人类语言网络的结构和动态的有价值的见解。

To avoid post-operative language impairments after surgery for drug-resistant epilepsy, electrical cortical stimulation mapping (ESM) is widely relied upon to localize language cortex, but ESM often elicits after- discharges (ADs), seizures, involuntary movements, and pain, which can limit mapping and impact patient safety. Furthermore, ESM is time-consuming and usually produces all-or-none results, providing limited insight into the function of stimulated sites. Finally, up to 30% of patients can have language dysfunction after resections that are guided by ESM. These limitations have motivated an alternative mapping method based on task-related power changes in high-gamma frequencies (≈50-200 Hz), which are highly correlated with neuronal population firing rate changes. Although high-gamma mapping (HGM) overcomes the aforementioned limitations of ESM, its clinical validation has been limited to ESM-HGM comparisons in small case series with significant variations in technique across centers, yielding inconsistent results, with unexplained discrepancies between methods. Moreover, neither HGM nor ESM have been prospectively validated for predicting post-operative language impairments with either subdural electrocorticography (ECoG) or stereo-EEG (sEEG, increasingly a safer alternative to ECoG). The overall objective of this study is to use a small consortium of three large academic epilepsy surgery centers to demonstrate the diagnostic validity and safety of iEEG HGM for both ECoG and sEEG in a prospective series of 221 patients, using an innovative browser-based bedside HGM system to standardize methods and share data across centers. This study will test the hypothesis that HGM can accurately predict post-surgical language outcomes but requires a different framework for interpretation than that used for ESM. First, using traditional methods for interpreting HGM results, we will test the concordance between HGM and ESM, and compare their safety and feasibility. Based on previous studies, we predict that HGM will be a good, but imperfect, predictor of ESM results. However, we predict that due to ESM-related seizures and differences in mapping duration, HGM will be safer and better tolerated by patients. Second, we will test models that attempt to explain and reconcile HGM false negatives and false positives with respect to ESM, and we will test whether these models, incorporating both functional activation (HGM) and effective connectivity (measured with cortico-cortical evoked potentials, or CCEPs) can better predict ESM results. Third, we will develop and test models for prediction of post-operative language outcomes, based on the anatomical extent and volume of cortical resection with respect to HGM and ESM results, using voxel-lesion-symptom matching (VLSM). Since clinical decisions are currently based on ESM and clinicians will be blinded to HGM, we predict that the incidence of language deficits will be significantly higher when HGM+ electrodes are resected. This study will have a direct and profound impact on the clinical practice of language mapping for neurosurgical procures, while contributing valuable insights into the structure and dynamics of human language networks.