Hasan Nahian I, Dannhauer Moritz, Wang Dezhi, Deng Zhi-De, Gomez Luis J
Elmore Family School of Electrical and Computer Engineering, Purdue University,, West Lafayette, 47907, Indiana, USA.
Computational Neurostimulation Research Program, Noninvasive Neuromodulation Unit, Experimental Therapeutics & Pathophysiology Branch, National Institute of Mental Health Intramural Research Program, National Institutes of Health,, Bethesda, 20892, Maryland, USA.
bioRxiv. 2023 Oct 30:2023.10.25.564044. doi: 10.1101/2023.10.25.564044.
Transcranial Magnetic Stimulation (TMS) coil placement and pulse waveform current are often chosen to achieve a specified E-field dose on targeted brain regions. TMS neuronavigation could be improved by including real-time accurate distributions of the E-field dose on the cortex. We introduce a method and develop software for computing brain E-field distributions in real-time enabling easy integration into neuronavigation and with the same accuracy as 1 -order finite element method (FEM) solvers. Initially, a spanning basis set (< 400) of E-fields generated by white noise magnetic currents on a surface separating the head and permissible coil placements are orthogonalized to generate the modes. Subsequently, Reciprocity and Huygens' principles are utilized to compute fields induced by the modes on a surface separating the head and coil by FEM, which are used in conjunction with online (real-time) computed primary fields on the separating surface to evaluate the mode expansion. We conducted a comparative analysis of E-fields computed by FEM and in real-time for eight subjects, utilizing two head model types (SimNIBS's 'headreco' and 'mri2mesh' pipeline), three coil types (circular, double-cone, and Figure-8), and 1000 coil placements (48,000 simulations). The real-time computation for any coil placement is within 4 milliseconds (ms), for 400 modes, and requires less than 4 GB of memory on a GPU. Our solver is capable of computing E-fields within 4 ms, making it a practical approach for integrating E-field information into the neuronavigation systems without imposing a significant overhead on frame generation (20 and 50 frames per second within 50 and 20 ms, respectively).
经颅磁刺激(TMS)线圈的放置位置和脉冲波形电流通常是为了在目标脑区实现特定的电场剂量而选择的。通过纳入皮层上电场剂量的实时准确分布,可以改进TMS神经导航。我们介绍了一种方法并开发了软件,用于实时计算脑电场分布,便于轻松集成到神经导航中,并且具有与一阶有限元法(FEM)求解器相同的精度。最初,在分隔头部和允许的线圈放置位置的表面上,由白噪声磁电流产生的一组跨度基集(<400)电场被正交化以生成模式。随后,利用互易原理和惠更斯原理,通过有限元法计算模式在分隔头部和线圈的表面上感应的场,这些场与在分隔表面上在线(实时)计算的一次场结合使用,以评估模式展开。我们对八名受试者进行了有限元法计算的电场和实时计算的电场的对比分析,使用了两种头部模型类型(SimNIBS的“headreco”和“mri2mesh”管道)、三种线圈类型(圆形、双锥形和8字形)以及1000个线圈放置位置(48,000次模拟)。对于任何线圈放置位置的实时计算在4毫秒(ms)内,对于400个模式,并且在GPU上所需内存小于4GB。我们的求解器能够在4毫秒内计算电场,使其成为将电场信息集成到神经导航系统中的一种实用方法,而不会在帧生成上造成显著开销(分别在50毫秒和20毫秒内每秒20帧和50帧)。