Interictal high frequency background activity as a biomarker of epileptogenic tissue.

Brain Communications Pub Date : 2021-08-31 eCollection Date: 2021-01-01 DOI:10.1093/braincomms/fcab188
Truman Stovall, Brian Hunt, Simon Glynn, William C Stacey, Stephen V Gliske
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引用次数: 6

Abstract

High frequency oscillations (HFOs) are very brief events that are a well-established biomarker of the epileptogenic zone (EZ) but are rare and comprise only a tiny fraction of the total recorded EEG. We hypothesize that the interictal high frequency 'background' data, which has received little attention but represents the majority of the EEG record, also may contain additional, novel information for identifying the EZ. We analysed intracranial EEG (30-500 Hz frequency range) acquired from 24 patients who underwent resective surgery. We computed 38 quantitative features based on all usable, interictal data (63-307 h per subject), excluding all detected HFOs. We assessed association between each feature and the seizure onset zone (SOZ) and resected volume (RV) using logistic regression. A pathology score per channel was also created via principle component analysis and logistic regression, using hold-out-one-patient cross-validation to avoid in-sample training. Association of the pathology score with the SOZ and RV was quantified using an asymmetry measure. Many features were associated with the SOZ: 23/38 features had odds ratios >1.3 or <0.7 and 17/38 had odds ratios different than zero with high significance (P < 0.001/39, logistic regression with Bonferroni Correction). The pathology score, the rate of HFOs, and their channel-wise product were each strongly associated with the SOZ [median asymmetry ≥0.44, good surgery outcome patients; median asymmetry ≥0.40, patients with other outcomes; 95% confidence interval (CI) > 0.27 in both cases]. The pathology score and the channel-wise product also had higher asymmetry with respect to the SOZ than the HFO rate alone (median difference in asymmetry ≥0.18, 95% CI >0.05). These results support that the high frequency background data contains useful information for determining the EZ, distinct and complementary to information from detected HFOs. The concordance between the high frequency activity pathology score and the rate of HFOs appears to be a better biomarker of epileptic tissue than either measure alone.

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间隔期高频背景活动作为致痫组织的生物标志物。
高频振荡(hfo)是一种非常短暂的事件,是一种公认的癫痫区(EZ)生物标志物,但很罕见,只占总记录脑电图的一小部分。我们假设间隔高频“背景”数据,很少受到关注,但代表了大部分脑电图记录,也可能包含额外的,用于识别EZ的新信息。我们分析了24例接受切除手术患者的颅内脑电图(30-500 Hz频率范围)。我们根据所有可用的间隔数据(每位受试者63-307小时)计算了38个定量特征,排除了所有检测到的hfo。我们使用逻辑回归评估每个特征与癫痫发作区(SOZ)和切除体积(RV)之间的关联。每个通道的病理评分也通过主成分分析和逻辑回归创建,使用保留一名患者的交叉验证来避免样本内训练。病理评分与SOZ和RV的关联使用不对称测量进行量化。许多特征与SOZ相关:23/38个特征的比值比>1.3或P < 0.001/39(采用Bonferroni校正的逻辑回归)。病理评分、hfo发生率及其通道产物均与SOZ呈强相关[中位不对称≥0.44,手术预后良好患者;中位不对称≥0.40,患者有其他结局;95%置信区间(CI)均> 0.27]。病理评分和通道产品与SOZ的不对称性也高于单独的HFO率(不对称性中位数差≥0.18,95% CI >0.05)。这些结果支持高频背景数据包含了确定EZ的有用信息,与检测到的hfo信息不同且互补。高频活动病理评分和HFOs发生率之间的一致性似乎是癫痫组织的更好的生物标志物,而不是单独测量。
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