Department of Electrical Energy, Systems and Automation, Ghent University, Sint-Pietersnieuwstraat 41, B-9000 Ghent, Belgium.
Phys Med Biol. 2012 Apr 21;57(8):2169-88. doi: 10.1088/0031-9155/57/8/2169. Epub 2012 Mar 28.
Accurate simulations on detailed realistic head models are necessary to gain a better understanding of the response to transcranial magnetic stimulation (TMS). Hitherto, head models with simplified geometries and constant isotropic material properties are often used, whereas some biological tissues have anisotropic characteristics which vary naturally with frequency. Moreover, most computational methods do not take the tissue permittivity into account. Therefore, we calculate the electromagnetic behaviour due to TMS in a head model with realistic geometry and where realistic dispersive anisotropic tissue properties are incorporated, based on T1-weighted and diffusion-weighted magnetic resonance images. This paper studies the impact of tissue anisotropy, permittivity and frequency dependence, using the anisotropic independent impedance method. The results show that anisotropy yields differences up to 32% and 19% of the maximum induced currents and electric field, respectively. Neglecting the permittivity values leads to a decrease of about 72% and 24% of the maximum currents and field, respectively. Implementing the dispersive effects of biological tissues results in a difference of 6% of the maximum currents. The cerebral voxels show limited sensitivity of the induced electric field to changes in conductivity and permittivity, whereas the field varies approximately linearly with frequency. These findings illustrate the importance of including each of the above parameters in the model and confirm the need for accuracy in the applied patient-specific method, which can be used in computer-assisted TMS.
准确的仿真需要基于详细的现实头部模型，这对于理解经颅磁刺激（TMS）的反应非常重要。迄今为止，通常使用具有简化几何形状和各向同性材料特性的头部模型，而一些生物组织具有各向异性特征，其会随频率自然变化。此外，大多数计算方法都没有考虑组织介电常数。因此，我们基于 T1 加权和弥散加权磁共振图像，在具有真实几何形状的头部模型中计算了具有真实各向异性弥散特性的电磁行为。本文使用各向异性独立阻抗法研究了组织各向异性、介电常数和频率依赖性的影响。结果表明，各向异性导致最大感应电流和电场的差异分别达到 32%和 19%。忽略介电常数值会导致最大电流和场分别减少约 72%和 24%。实现生物组织的色散效应会导致最大电流差异 6%。大脑体素对电导率和介电常数变化的感应电场的灵敏度有限，而电场随频率大致呈线性变化。这些发现说明了在模型中包含上述每个参数的重要性，并证实了在计算机辅助 TMS 中应用的特定于患者的方法需要准确性。
