Optimization of MRI Gradient Coils With Explicit Peripheral Nerve Stimulation Constraints.
Optimization of MRI Gradient Coils With Explicit Peripheral Nerve Stimulation Constraints.
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DOI：
10.1109/tmi.2020.3023329
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发表时间：
2021-01
影响因子：
10.6
通讯作者：
Wald LL
中科院分区：
文献类型：
--
作者：
Davids M;Guerin B;Klein V;Wald LL
周围神经刺激(PNS)限制了使用强大梯度系统的快速序列的磁共振成像数据的获取速度。目前，在使用构建的线圈原型进行的实验模拟研究中，在线圈设计阶段之后评估PNS的特性。这使得很难找到可以减少PNS的设计修改。在这里，我们演示了一种将PNS效应合并到线圈优化过程中的直接方法。有关外加磁场和周围神经之间相互作用的知识使优化器能够确定线圈解决方案，在满足传统工程限制的同时最大限度地减少PNS。我们将PNS优化的身体和头部梯度的模拟阈值与传统设计进行了比较，发现PNS倾向最多减少了2倍，线圈电感和场线性度方面的损失适中，潜在地将可以安全用于人类的图像编码性能提高了一倍。同样的框架在设计和操作磁刺激和电刺激设备时可能会很有用。
Peripheral Nerve Stimulation (PNS) limits the acquisition rate of Magnetic Resonance Imaging data for fast sequences employing powerful gradient systems. The PNS characteristics are currently assessed after the coil design phase in experimental stimulation studies using constructed coil prototypes. This makes it difficult to find design modifications that can reduce PNS. Here, we demonstrate a direct approach for incorporation of PNS effects into the coil optimization process. Knowledge about the interactions between the applied magnetic fields and peripheral nerves allows the optimizer to identify coil solutions that minimize PNS while satisfying the traditional engineering constraints. We compare the simulated thresholds of PNS-optimized body and head gradients to conventional designs, and find an up to 2-fold reduction in PNS propensity with moderate penalties in coil inductance and field linearity, potentially doubling the image encoding performance that can be safely used in humans. The same framework may be useful in designing and operating magneto- and electro-stimulation devices.