APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France.
Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France.
Ann Clin Transl Neurol. 2023 Nov;10(11):2114-2126. doi: 10.1002/acn3.51900. Epub 2023 Sep 21.
Stereoelectroencephalography (SEEG) is the reference method in the presurgical exploration of drug-resistant focal epilepsy. However, prognosticating surgery on an individual level is difficult. A quantified estimation of the most epileptogenic regions by searching for relevant biomarkers can be proposed for this purpose. We investigated the performances of ictal (Epileptogenicity Index, EI; Connectivity EI, cEI), interictal (spikes, high-frequency oscillations, HFO [80-300 Hz]; Spikes × HFO), and combined (Spikes × EI; Spikes × cEI) biomarkers in predicting surgical outcome and searched for prognostic factors based on SEEG-signal quantification.
Fifty-three patients operated on following SEEG were included. We compared, using precision-recall, the epileptogenic zone quantified using different biomarkers (EZ ) against the visual analysis (EZ ). Correlations between the EZ resection rates or the EZ extent and surgical prognosis were analyzed.
EI and Spikes × EI showed the best precision against EZ (0.74; 0.70), followed by Spikes × cEI and cEI, whereas interictal markers showed lower precision. The EZ resection rates were greater in seizure-free than in non-seizure-free patients for the EZ defined by ictal biomarkers and were correlated with the outcome for EI and Spikes × EI. No such correlation was found for interictal markers. The extent of the quantified EZ did not correlate with the prognosis.
Ictal or combined ictal-interictal markers overperformed the interictal markers both for detecting the EZ and predicting seizure freedom. Combining ictal and interictal epileptogenicity markers improves detection accuracy. Resection rates of the quantified EZ using ictal markers were the only statistically significant determinants for surgical prognosis.
立体脑电图（SEEG）是耐药性局灶性癫痫术前探索的参考方法。然而，在个体水平上预测手术效果是困难的。通过寻找相关生物标志物，可以提出一种量化评估最致痫区域的方法。为此，我们研究了发作期（致痫性指数，EI；连接 EI，cEI）、发作间期（棘波、高频振荡，HFO[80-300Hz]；棘波×HFO）和联合（棘波×EI；棘波×cEI）生物标志物在预测手术结果中的表现，并基于 SEEG 信号量化寻找预后因素。
纳入了 53 例接受 SEEG 术后手术的患者。我们使用精度-召回率比较了使用不同生物标志物（EZ）量化的致痫区与视觉分析（EZ）的致痫区。分析了 EZ 切除率或 EZ 范围与手术预后的相关性。
EI 和棘波×EI 在与 EZ 相比时显示出最好的精度（0.74；0.70），其次是棘波×cEI 和 cEI，而发作间期标志物的精度较低。在无癫痫发作的患者中，癫痫发作标志物定义的 EZ 切除率大于非癫痫发作的患者，并且与 EI 和棘波×EI 的结果相关。在发作间期标志物中未发现这种相关性。量化的 EZ 范围与预后无关。
发作期或发作期与发作间期的联合致痫性标志物在检测 EZ 和预测无癫痫发作方面均优于发作间期标志物。结合发作期和发作间期致痫性标志物可提高检测准确性。使用发作期标志物量化的 EZ 切除率是唯一具有统计学意义的手术预后决定因素。
