Walter H, Kristeva R, Knorr U, Schlaug G, Huang Y, Steinmetz H, Nebeling B, Herzog H, Seitz R J
Department of Neurology Heinrich-Heine-University Düsseldorf, Germany.
Brain Topogr. 1992 Winter;5(2):183-7. doi: 10.1007/BF01129048.
A method for comparing estimated magnetoencephalographic (MEG) dipole localizations with regional cerebral blood flow (rCBF) activation areas is presented. This approach utilizes individual intermodal matching of MEG data, of rCBF measurements with [15O]-butanol and positron emission tomography (PET), and of anatomical information obtained from magnetic resonance (MR) images. The MEG data and the rCBF measurements were recorded in a healthy subject during right-sided simple voluntary movements of the foot, thumb, index finger, and mouth. High resolution 3D-FLASH MR images of the brain consisting of 128 contiguous sagittal slices of 1.17-mm thickness were used. MEG/MR integration was performed by superimposing the 3D head coordinate system constructed during the MEG measurement onto the MR image data using identical anatomical landmarks as references. PET/MR integration was achieved by a phantom-validated iterative front-to-back-projection algorithm resulting in one integrated MEG/PET/MR image. The estimated dipole locations followed the somatotopic organisation of the task-specific rCBF increases as evident from PET, although they did not match point-to-point. Our results demonstrate that intermodal matching of MEG, PET and MR data provides a tool for relating estimated neuromagnetic field locations to task-specific rCBF changes in individual subjects. Our method offers the perspective of refined dipole modelling.
本文提出了一种将估计的脑磁图（MEG）偶极子定位与局部脑血流（rCBF）激活区域进行比较的方法。该方法利用了MEG数据、用[15O] -丁醇和正电子发射断层扫描（PET）进行的rCBF测量以及从磁共振（MR）图像获得的解剖学信息的个体多模态匹配。在一名健康受试者进行右侧足部、拇指、食指和口部的简单自主运动期间记录了MEG数据和rCBF测量值。使用了由128个连续的1.17毫米厚矢状切片组成的大脑高分辨率3D - FLASH MR图像。通过将MEG测量期间构建的3D头部坐标系叠加到以相同解剖标志为参考的MR图像数据上，进行MEG/MR整合。通过一种经模型验证的迭代前后投影算法实现PET/MR整合，从而得到一张整合的MEG/PET/MR图像。尽管估计的偶极子位置并非点对点匹配，但从PET可以明显看出，它们遵循特定任务rCBF增加的躯体感觉组织。我们的结果表明，MEG、PET和MR数据的多模态匹配为将估计的神经磁场位置与个体受试者特定任务的rCBF变化相关联提供了一种工具。我们的方法为改进偶极子建模提供了前景。
