Currently, simulations of the induced currents in the brain produced by transcranial magnetic stimulation (TMS) are used to elucidate the regions reached by stimuli. However, models commonly found in the literature are too general and neglect imperfections in the windings. Aiming to predict the stimulation sites in patients requires precise modeling of the electric field (E-field), and a proper calibration to adequate to the empirical data of the particular coil employed. Furthermore, most fabricators do not provide precise information about the coil geometries, and even using X-ray images may lead to subjective interpretations. We measured the three components of the vector magnetic field induced by a TMS figure-8 coil with spatial resolutions of up to 1 mm. Starting from a computerized tomography-based coil model, we applied a multivariate optimization algorithm to automatically modify the original model and obtain one that optimally fits the measurements. Differences between models were assessed in a human brain mesh using the finite-elements method showing up to 6% variations in the E-field magnitude. Our calibrated model could increase the precision of the estimated E-field induced in the brain during TMS, enhance the accuracy of delivered stimulation during functional brain mapping, and improve dosimetry for repetitive TMS. Graphical Abstract Geometrical model of TMS coil based on TAC images is optimally deformed to match magnetic field measurements. The calibrated model's induced electric field in the brain differs from the original.

中文翻译：

---

使用磁场测量获得用于经颅磁刺激的准确和校准的线圈模型。

当前，通过经颅磁刺激（TMS）产生的大脑感应电流的模拟用于阐明刺激所到达的区域。但是，文献中常见的模型过于笼统，忽略了绕组中的缺陷。为了预测患者的刺激部位，需要对电场（E场）进行精确建模，并进行适当的校准以充分适应所用特定线圈的经验数据。此外，大多数制造商不提供有关线圈几何形状的精确信息，甚至使用X射线图像也可能导致主观解释。我们测量了由TMS图8线圈感应的矢量磁场的三个分量，其空间分辨率高达1 mm。从基于计算机断层扫描的线圈模型开始，我们应用了多元优化算法来自动修改原始模型，并获得最适合测量结果的模型。使用有限元方法在人脑网格中评估模型之间的差异，该方法显示出电场强度的最大变化为6％。我们的校准模型可以提高TMS期间在大脑中诱发的估计电场的精度，增强功能性大脑测绘期间传递的刺激的准确性，并改善重复TMS的剂量。基于TAC图像的TMS线圈的图形抽象几何模型经过优化变形以匹配磁场测量结果。校准模型在大脑中的感应电场与原始电场不同。使用有限元方法在人脑网格中评估模型之间的差异，该方法显示出电场强度的最大变化为6％。我们的校准模型可以提高TMS期间在大脑中诱发的估计电场的精度，增强功能性大脑测绘期间传递的刺激的准确性，并改善重复TMS的剂量。基于TAC图像的TMS线圈的图形抽象几何模型经过优化变形以匹配磁场测量结果。校准模型在大脑中的感应电场与原始电场不同。使用有限元方法在人脑网格中评估模型之间的差异，该方法显示出电场强度的最大变化为6％。我们的校准模型可以提高TMS期间在大脑中诱发的估计电场的精度，增强功能性大脑测绘期间传递的刺激的准确性，并改善重复TMS的剂量。基于TAC图像的TMS线圈的图形抽象几何模型经过优化变形以匹配磁场测量结果。校准模型在大脑中的感应电场与原始电场不同。增强功能性脑图绘制过程中传递刺激的准确性，并改善重复性TMS的剂量测定。基于TAC图像的TMS线圈的图形抽象几何模型经过优化变形以匹配磁场测量结果。校准模型在大脑中的感应电场与原始电场不同。提高功能性脑图绘制过程中传递刺激的准确性，并改善重复性TMS的剂量。基于TAC图像的TMS线圈的图形抽象几何模型经过优化变形以匹配磁场测量结果。校准模型在大脑中的感应电场与原始电场不同。