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Detection of interictal epileptiform discharges: A comparison of on-scalp MEG and conventional MEG measurements
Clinical Neurophysiology ( IF 3.7 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.clinph.2020.03.041
Karin Westin 1 , Christoph Pfeiffer 2 , Lau M Andersen 3 , Silvia Ruffieux 2 , Gerald Cooray 1 , Alexei Kalaboukhov 2 , Dag Winkler 2 , Martin Ingvar 4 , Justin Schneiderman 5 , Daniel Lundqvist 4
Affiliation  

OBJECTIVE Conventional MEG provides an unsurpassed ability to, non-invasively, detect epileptic activity. However, highly resolved information on small neuronal populations required in epilepsy diagnostics is lost and can be detected only intracranially. Next-generation on-scalp magnetencephalography (MEG) sensors aim to retrieve information unavailable to conventional non-invasive brain imaging techniques. To evaluate the benefits of on-scalp MEG in epilepsy, we performed the first-ever such measurement on an epilepsy patient. METHODS Conducted as a benchmarking study focusing on interictal epileptiform discharge (IED) detectability, an on-scalp high-temperature superconducting quantum interference device magnetometer (high-Tc SQUID) system was compared to a conventional, low-temperature SQUID system. Co-registration of electroencephalopraphy (EEG) was performed. A novel machine learning-based IED-detection algorithm was developed to aid identification of on-scalp MEG unique IEDs. RESULTS Conventional MEG contained 24 IEDs. On-scalp MEG revealed 47 IEDs (16 co-registered by EEG, 31 unique to the on-scalp MEG recording). CONCLUSION Our results indicate that on-scalp MEG might capture IEDs not seen by other non-invasive modalities. SIGNIFICANCE On-scalp MEG has the potential of improving non-invasive epilepsy evaluation.

中文翻译:

发作间期癫痫样放电的检测:头皮上 MEG 和传统 MEG 测量的比较

目标 传统 MEG 提供了一种无与伦比的无创检测癫痫活动的能力。然而,癫痫诊断所需的小神经元群的高分辨率信息丢失了,只能在颅内检测到。下一代头皮上脑磁图 (MEG) 传感器旨在检索传统非侵入性脑成像技术无法获得的信息。为了评估头皮上 MEG 在癫痫中的益处,我们首次对癫痫患者进行了此类测量。方法 作为侧重于发作间期癫痫样放电 (IED) 可检测性的基准研究,将头皮上高温超导量子干涉设备磁力计 (high-Tc SQUID) 系统与传统的低温 SQUID 系统进行比较。进行了脑电图 (EEG) 的联合配准。开发了一种新的基于机器学习的 IED 检测算法,以帮助识别头皮上的 MEG 独特的 IED。结果 常规 MEG 包含 24 个简易爆炸装置。头皮上的 MEG 显示了 47 个 IED(16 个由 EEG 共同注册,31 个是头皮上的 MEG 记录独有的)。结论我们的结果表明,头皮上的 MEG 可能会捕获其他非侵入性方式无法看到的 IED。意义 头皮上的 MEG 具有改善非侵入性癫痫评估的潜力。结论我们的结果表明,头皮上的 MEG 可能会捕获其他非侵入性方式无法看到的 IED。意义 头皮上的 MEG 具有改善非侵入性癫痫评估的潜力。结论我们的结果表明,头皮上的 MEG 可能会捕获其他非侵入性方式无法看到的 IED。意义 头皮上的 MEG 具有改善非侵入性癫痫评估的潜力。
更新日期:2020-08-01
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