Development of volume conductor and source models to localize epileptic foci
Development of volume conductor and source models to localize epileptic foci
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DOI：
10.1097/wnp.0b013e318038fb3e
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发表时间：
2007-04-01
影响因子：
2.4
通讯作者：
Kastner, Joern
中科院分区：
文献类型：
--
作者：
Fuchs, Manfred;Wagner, Michael;Kastner, Joern
从皮层脑电图（ECoG）网格数据的映射和源重建以及与癫痫患者的表面EEG评估的比较越来越受到关注。ECoG映射到来自磁共振图像和计算机断层扫描（CT）的个体皮质解剖结构的三维渲染图上，在解剖和功能坐标系配准后形成PET。使用不同的源模型和真实形状的体积导体模型对ECoG和EEG的源重建进行比较。真实形状的体积导体模型的EEG源重建是提高定位精度的先决条件。来自MRI的个体边界元法（BEM）模型代表了“金标准”，并且可以近似各向同性均质头部隔间，从而与经典的过度简化的球壳模型相比，给出了头部形状的改进描述。骨层或白色物质纤维的各向异性体积传导特性可以通过有限元方法（FEM）来描述;不幸的是，这些模型需要巨大的计算工作量，因此不用于日常应用中。为了避免这种计算工作，可以使用从平均MRI数据集导出的头部模型。这种方法可以使用具有大量节点的高度精细的模型，从而具有更好的数值精度，因为设置仅执行一次，并且分解的模型或预先计算的导联场矩阵被保存以供以后应用。如果不需要重建结果与解剖结构的叠加，则完全不需要单独的图像数据。利用预先计算的导联场矩阵和线性插值技术，至少从平均MRI数据集导出的标准化BEM和FEM体积导体模型可以实现与分析球形模型相同的计算速度。平滑的皮质包络被用作ECoG源重建的逼真形状的单壳体积导体模型，而三室BEM模型是EEG所需的。作者描述了如何定位ECoG网格电极的位置，以及如何从磁共振和CT图像中分割皮质表面。在两种图像模式中使用共同基准点进行基于地标的配准。另一种更有前途的自动方法是基于相互的三维体灰度信息。ECoG电极位置可以从三维CT切片手动检索使用光标在阈值图像与深度信息。或者，从MRI分割的皮质表面的平滑包络线用于通过标记四个角并测量沿平滑表面的沿着距离来半自动地确定网格电极位置。扩展源补丁皮质限制扫描和电流密度重建，ECoG和表面EEG数据的结果进行了比较。单等效偶极子被用来解释EEG远场，并与解释ECoG数据的原始电流密度分布的结果进行了比较。作者研究了球形和真实形状的BEM体积导体模型在头部球形和非球形部分的EEG和ECoG源重建中的性能，模拟和测量了癫痫棘波数据。在头部的球形部分，球形和真实形状的模型之间只有很小的差异，而在非球形部分，如颞叶区域，真实形状的模型在单壳ECoG和三壳EEG情况下上级球形近似。ECoG的近场是更复杂的解释比表面EEG的远场，并不能解释一般简单的等效偶极子。然而，通过使用真实形状的体积导体模型和皮质约束源模型进行模拟，作者研究了骨骼和皮肤层如何充当空间低通滤波器，从而平滑和简化表面EEG图，该表面EEG图是由从测量的ECoG数据导出的看起来更复杂的源配置生成的。
There is increasing interest in mapping and source reconstruction from electrocorticoencephalographic (ECoG) grid data and comparison to surface EEG evaluations of epileptic patients. ECoG mapping onto three-dimensional renderings of the individual cortical anatomy derived from magnetic resonance images and computed tomography (CT) is pet-formed after coregistration of anatomical and functional coordinate systems. Source reconstructions from ECoG and EEG are compared using different source models and realistically shaped volume conductor models. Realistically shaped volume conductor models for EEG source reconstruction are a prerequisite for improved localization accuracy. Individual boundary element method (BEM) models derived from MRI represent the "gold standard" and can approximate isotropic homogeneous head compartments and thus give an improved description of the head shape as compared with classical oversimplifying spherical shell models. Anisotropic volume conduction properties of the bone layer or the white matter fibers can be described by the finite element method (FEM); unfortunately, these models require a huge computational effort and are thus not used in daily applications. To avoid this computational effort, head models derived from an averaged MRI dataset can be used. Highly refined models with a large number of nodes and thus better numerical accuracy can be used by this approach, because the setup is performed only once and the decomposed models or precomputed leadfield matrices are saved for later application. Individual image data are not at all needed, if an overlay of the reconstruction results with the anatomy is not desired. With precomputed leadfield matrices and linear interpolation techniques, at least standardized BEM and FEM volume conductor models derived from averaged MRI datasets can achieve the same computational speed as analytical spherical models. The smoothed cortical envelope is used as a realistically shaped single-shell volume conductor model for ECoG source reconstruction, whereas three-compartment BEM-models are required for EEG. The authors describe how to localize ECoG-grid electrode positions and how to segment the cortical surface from coregistered magnetic resonance and CT images. Landmark-based coregistration is performed using common fiducials in both image modalities. Another more promising automatic approach is based on mutual three-dimensional volume graylevel information. The ECoG electrode positions can be retrieved from three-dimensional CT slices manually using cursors in thresholded images with depth information. Alternatively, the smoothed envelope of the cortical surface segmented from the MRI is used to semiautomatically determine the grid electrode positions by marking the four corners and measuring distances along the smoothed surface. With extended source patches for cortically constrained scans and current density reconstructions, results from ECoG and surface EEG data were compared. Single equivalent dipoles were used to explain the EEG far fields, and results were compared with the original current density distributions explaining the ECoG data. The authors studied the performance of spherical and realistically shaped BEM volume conductor models for EEG and ECoG source reconstruction in spherical and nonspherical parts of the head with simulations and measured epileptic spike data.Only small differences between spherical and realistically shaped models were found in the spherical parts of the head, whereas realistically shaped models are superior to spherical approximtions in both single-shell ECoG and three-shell EEG cases in the nonspherical parts, such as the temporal lobe areas. The ECoG near field is more complicated to interpret than the surface EEG far field and cannot be explained in general by simple equivalent dipoles. However, from simulations with realistically shaped volume conductor models and cortically constrained source models, the authors studied how the bone and skin layer act as spatial low pass filters that smooth and simplify the surface EEG maps generated by much more complicated-looking source configurations derived from measured ECoG data.