Estimation of brain network ictogenicity predicts outcome from epilepsy surgery.
Estimation of brain network ictogenicity predicts outcome from epilepsy surgery.
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DOI：
10.1038/srep29215
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发表时间：
2016-07-07
影响因子：
4.6
通讯作者：
Terry JR
中科院分区：
文献类型：
--
作者：
Goodfellow M;Rummel C;Abela E;Richardson MP;Schindler K;Terry JR
手术是治疗难治性癫痫的一个有价值的选择。然而，并不总是能获得显著的术后改善。这部分是由于我们对大脑网络的癫痫发作能力的不完全理解。在这里，我们介绍了一个在硅片，基于模型的框架来研究手术的影响，在癫痫脑网络。我们发现，传统上决定切除组织区域的因素，如局灶性脑病变的位置或癫痫样节律的存在，并不一定能预测最佳的切除策略。我们通过分析接受癫痫手术的患者的皮层脑电图（ECoG）记录来验证我们的框架。我们发现，当术后结果是好的，模型预测的最佳策略更好地与实际手术进行比术后结果是穷人。至关重要的是，这允许预测最佳手术策略，并为接受癫痫手术的患者提供定量评估。
Surgery is a valuable option for pharmacologically intractable epilepsy. However, significant post-operative improvements are not always attained. This is due in part to our incomplete understanding of the seizure generating (ictogenic) capabilities of brain networks. Here we introduce an in silico, model-based framework to study the effects of surgery within ictogenic brain networks. We find that factors conventionally determining the region of tissue to resect, such as the location of focal brain lesions or the presence of epileptiform rhythms, do not necessarily predict the best resection strategy. We validate our framework by analysing electrocorticogram (ECoG) recordings from patients who have undergone epilepsy surgery. We find that when post-operative outcome is good, model predictions for optimal strategies align better with the actual surgery undertaken than when post-operative outcome is poor. Crucially, this allows the prediction of optimal surgical strategies and the provision of quantitative prognoses for patients undergoing epilepsy surgery.