Gallagher Ryan S, Sinha Nishant, Pattnaik Akash R, Ojemann William K S, Lucas Alfredo, LaRocque Joshua J, Bernabei John M, Greenblatt Adam S, Sweeney Elizabeth M, Chen H Isaac, Davis Kathryn A, Conrad Erin C, Litt Brian
Center for Neuroengineering and Therapeutics, University of Pennsylvania.
Perelman School of Medicine, University of Pennsylvania.
ArXiv. 2023 Jul 27:arXiv:2307.15170v1.
Intracranial EEG (IEEG) is used for 2 main purposes, to determine: (1) if epileptic networks are amenable to focal treatment and (2) where to intervene. Currently these questions are answered qualitatively and sometimes differently across centers. There is a need for objective, standardized methods to guide surgical decision making and to enable large scale data analysis across centers and prospective clinical trials.
We analyzed interictal data from 101 patients with drug resistant epilepsy who underwent presurgical evaluation with IEEG. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. 65 patients had unifocal seizure onset on IEEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal IEEG abnormalities for each patient. We compared these measures against the "5 Sense Score (5SS)," a pre-implant estimate of the likelihood of focal seizure onset, and assessed their ability to predict the clinicians' choice of therapeutic intervention and the patient outcome.
The spatial dispersion of IEEG electrodes predicted network focality with precision similar to the 5SS (AUC = 0.67), indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5SS and the spatial dispersion of interictal IEEG abnormalities significantly improved this prediction (AUC = 0.79; p<0.05). The combined model predicted ultimate treatment strategy (surgery vs. device) with an AUC of 0.81 and post-surgical outcome at 2 years with an AUC of 0.70. The 5SS, interictal IEEG, and electrode placement were not correlated and provided complementary information.
Quantitative, interictal IEEG significantly improved upon pre-implant estimates of network focality and predicted treatment with precision approaching that of clinical experts. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery.
颅内脑电图（IEEG）主要用于两个目的，即确定：（1）癫痫网络是否适合进行局灶性治疗；（2）干预位置。目前，这些问题是通过定性方式回答的，而且不同中心的回答有时也有所不同。需要客观、标准化的方法来指导手术决策，并实现跨中心的大规模数据分析以及前瞻性临床试验。
我们分析了101例接受IEEG术前评估的药物难治性癫痫患者的发作间期数据。我们选择发作间期数据是因为其有可能降低与发作期记录相关的发病率和成本。65例患者在IEEG上有单灶性发作起始，36例为非局灶性或多灶性。我们对每位患者植入电极的空间分散度和发作间期IEEG异常进行了量化。我们将这些指标与“五感评分（5SS）”进行比较，5SS是植入前对局灶性发作起始可能性的估计，并评估它们预测临床医生治疗干预选择和患者预后的能力。
IEEG电极的空间分散度预测网络局灶性的精度与5SS相似（曲线下面积[AUC]=0.67），表明电极放置准确反映了植入前的信息。一个结合5SS和发作间期IEEG异常空间分散度的交叉验证模型显著改善了这一预测（AUC=0.79；p<0.05）。联合模型预测最终治疗策略（手术与装置）的AUC为0.81，预测术后2年结果的AUC为0.70。5SS、发作间期IEEG和电极放置不相关，且提供了互补信息。
定量的发作间期IEEG在网络局灶性的植入前估计基础上有显著改善，并以接近临床专家的精度预测治疗。我们将本研究视为构建指导癫痫手术的标准化定量工具的重要一步。
