Iwata Takamitsu, Yanagisawa Takufumi, Fukuma Ryohei, Ikegaya Yuji, Oshino Satoru, Tani Naoki, Khoo Hui Ming, Sugano Hidenori, Iimura Yasushi, Suzuki Hiroharu, Kishima Haruhiko
Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
Department of Neuroinformatics, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
Ann Clin Transl Neurol. 2025 May;12(5):986-997. doi: 10.1002/acn3.70032. Epub 2025 Mar 20.
Discriminating between epileptogenic and physiological ripples in the hippocampus is important for identifying epileptogenic (EP) zones; however, distinguishing these ripples on the basis of their waveforms is difficult. We hypothesized that the nocturnal synchronization of hippocampal ripples and cortical delta power could be used to classify epileptogenic and physiological ripples in the hippocampus.
We enrolled 38 patients with electrodes implanted in the hippocampus or parahippocampal gyrus between April 2014 and March 2023 at our institution. We divided 11 patients (11 hippocampi) who were pathologically diagnosed with hippocampal sclerosis into the EP group and five patients (six hippocampi) with no epileptogenicity in the hippocampus into the nonepileptogenic (NE) group. Hippocampal ripples were detected using intracranial electroencephalography with hippocampal or parahippocampal electrodes. Cortical delta power (0.5-4 Hz) was assessed using cortical electrodes. The Pearson correlation coefficient between the ripple rates and cortical delta power (Corr-RD) was calculated on the basis of the intracranial electroencephalographic signals recorded each night.
Although hippocampal ripples were similar among the EP and NE groups based on their waveforms and frequency properties, the Corr-RDs in the EP group (mean [standard deviation]: 0.20 [0.049]) were significantly lower than those in the NE group (0.67 [0.070]). On the basis of the minimum Corr-RDs, the two groups were classified with 94.1% accuracy.
Our results demonstrate that the Corr-RD is a biomarker of hippocampal epileptogenicity.
区分海马体中致痫性和生理性涟漪对于识别致痫区很重要；然而，基于其波形来区分这些涟漪很困难。我们假设海马体涟漪与皮质δ波功率的夜间同步性可用于对海马体中的致痫性和生理性涟漪进行分类。
我们纳入了2014年4月至2023年3月期间在我们机构植入海马体或海马旁回电极的38例患者。我们将11例经病理诊断为海马硬化的患者（11个海马体）分为致痫组，将5例海马体无致痫性的患者（6个海马体）分为非致痫组。使用带有海马体或海马旁回电极的颅内脑电图检测海马体涟漪。使用皮质电极评估皮质δ波功率（0.5 - 4Hz）。根据每晚记录的颅内脑电图信号计算涟漪发生率与皮质δ波功率之间的皮尔逊相关系数（Corr - RD）。
尽管致痫组和非致痫组的海马体涟漪在波形和频率特性方面相似，但致痫组的Corr - RD（均值[标准差]：0.20[0.049]）显著低于非致痫组（0.67[0.070]）。基于最小Corr - RD，两组分类的准确率为94.1%。
我们的结果表明Corr - RD是海马体致痫性的一个生物标志物。
