Koessler L, Benhadid A, Maillard L, Vignal J P, Felblinger J, Vespignani H, Braun M
INSERM ERI13, Nancy, France.
Neuroimage. 2008 Jul 1;41(3):914-23. doi: 10.1016/j.neuroimage.2008.02.039. Epub 2008 Mar 6.
Spatial localization of scalp EEG electrodes is a major step for dipole source localization and must be accurate, reproducible and practical. Several methods have been proposed in the last 15 years. The most widely used method is currently electromagnetic digitization. Nevertheless, this method is difficult to use in a clinical environment and has not been validated with a high number of electrodes. In this paper, we introduce a new automatic method for localizing and labeling EEG sensors using MRI. First, we design a new scalp EEG sensor. Secondly, we validate this new technique on a head phantom and then in a clinical environment with volunteers and patients. For this, we compare the reproducibility, accuracy and performance of our method with electromagnetic digitization. We demonstrate that our method provides better reproducibility with a significant difference (p<0.01). Concerning precision, both methods are equally accurate with no statistical differences. To conclude, our method offers the possibility of using MRI volume for both source localization and spatial localization of EEG sensors. Automation makes this method very reproducible and easy to handle in a routine clinical environment.
头皮脑电图电极的空间定位是偶极子源定位的重要步骤，必须准确、可重复且实用。在过去15年里已提出了几种方法。目前使用最广泛的方法是电磁数字化。然而，这种方法在临床环境中难以使用，且尚未在大量电极上得到验证。在本文中，我们介绍一种利用磁共振成像（MRI）对脑电图传感器进行定位和标记的新自动方法。首先，我们设计了一种新的头皮脑电图传感器。其次，我们在头部模型上，然后在有志愿者和患者参与的临床环境中对这项新技术进行验证。为此，我们将我们方法的可重复性、准确性和性能与电磁数字化进行比较。我们证明我们的方法具有更好的可重复性，差异显著（p<0.01）。关于精度，两种方法同样准确，无统计学差异。总之，我们的方法提供了利用MRI容积进行脑电图传感器源定位和空间定位的可能性。自动化使该方法具有很高的可重复性，且在常规临床环境中易于操作。
