Klimes Petr, Peter-Derex Laure, Hall Jeff, Dubeau François, Frauscher Birgit
Analytical Neurophysiology Lab, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic.
Analytical Neurophysiology Lab, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Center for Sleep Medicine and Respiratory Diseases, Lyon University Hospital, Lyon 1 University, Lyon, France; Lyon Neuroscience Research Center, Lyon, France.
Clin Neurophysiol. 2022 Feb;134:88-99. doi: 10.1016/j.clinph.2021.10.023. Epub 2021 Dec 16.
We hypothesized that spatio-temporal dynamics of interictal spikes reflect the extent and stability of epileptic sources and determine surgical outcome.
We studied 30 consecutive patients (14 good outcome). Spikes were detected in prolonged stereo-electroencephalography recordings. We quantified the spatio-temporal dynamics of spikes using the variance of the spike rate, line length and skewness of the spike distribution, and related these features to outcome. We built a logistic regression model, and compared its performance to traditional markers.
Good outcome patients had more dominant and stable sources than poor outcome patients as expressed by a higher variance of spike rates, a lower variance of line length, and a lower variance of positive skewness (ps < 0.05). The outcome was correctly predicted in 80% of patients. This was better or non-inferior to predictions based on a focal lesion (p = 0.016), focal seizure-onset zone, or complete resection (ps > 0.05). In the five patients where traditional markers failed, spike distribution predicted the outcome correctly. The best results were achieved by 18-h periods or longer.
Analysis of spike dynamics shows that surgery outcome depends on strong, single and stable sources.
Our quantitative method has the potential to be a reliable predictor of surgical outcome.
我们假设发作间期棘波的时空动态反映了癫痫源的范围和稳定性，并决定手术结果。
我们研究了30例连续患者（14例预后良好）。在长时间的立体脑电图记录中检测棘波。我们使用棘波率的方差、棘波分布的线长度和偏度来量化棘波的时空动态，并将这些特征与结果相关联。我们建立了一个逻辑回归模型，并将其性能与传统标志物进行比较。
预后良好的患者比预后不良的患者有更占主导地位和更稳定的癫痫源，表现为棘波率的方差更高、线长度的方差更低以及正偏度的方差更低（P<0.05）。80%的患者结果被正确预测。这优于或不劣于基于局灶性病变（P = 0.016）、局灶性发作起始区或完全切除的预测（P>0.05）。在传统标志物失败的5例患者中，棘波分布正确预测了结果。18小时或更长时间的分析取得了最佳结果。
棘波动态分析表明手术结果取决于强大、单一且稳定的癫痫源。
我们的定量方法有可能成为手术结果的可靠预测指标。
