Mitigation of peripheral nerve stimulation (PNS) in MRI

减轻 MRI 中的周围神经刺激 (PNS)

• 批准号: 10378759
• 负责人: Bastien Guerin
• 金额: $ 59.69万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10378759
• 关键词: Action Potentials; Address; Amplifiers; Atlases; Boundary Elements; Caliber; Clinic; Clinical Research; Coiled Bodies; Dependence; Development; Electromagnetics; Engineering; Equipment; Esthesia; Excision; Foundations; Freedom; Gender; Generations; Grant; Head; Head and neck structure; Human body; Image; Industry Standard; Magnetic Resonance Imaging; Measurement; Measures; Mechanics; Methods; Modeling; Modernization; Morphologic artifacts; Motor; Nerve; Nerve Fibers; Nonlinear Dynamics; Pain; Pattern; Performance; Peripheral Nerve Stimulation; Peripheral Nerves; Phase; Population; Population Heterogeneity; Procedures; Property; Research; Resolution; Shapes; Shoulder; Speed; Stream; System; Techniques; Technology; Testing; Tissues; Validation; Work; body system; clinical application; connectome; cost; design; electric field; experimental study; healthy volunteer; improved; in vivo; insight; magnetic field; medical specialties; neuroimaging; next generation; programs; prototype; research study; simulation; somatosensory; tool; volunteer

7. Project Summary/Abstract Peripheral nerve stimulation (PNS) in MRI results from electric fields induced by the switching of gradient coil, which may result in stimulation of the largest nerves in the body (large diameter nerves are easier to excite than small ones). The use of current generation of Gmax=80 mT/m, Smax=200 T/m/s whole-body MRI gradients is largely constrained by PNS rather than amplifier power, mechanical issues or heat removal and specialty coils such as the Gmax=300 mT/m, Smax=200 T/m/s “MGH Connectome” coil can only be fully used within a fraction of its operational parameter space. Impacting these PNS limitations will allow faster imaging, higher resolution and reduced distortions in many sequences routinely used for research and in the clinic for head/neck as well as body imaging, such as EPI, DWI, bSSFP, RARE and PROPELLER. Head-only (HO) gradient inserts have higher thresholds but their latest generation are also PNS limited. Additionally, most neuroimaging research studies and nearly all clinical studies use whole-body (WB) gradient systems. In this program, we develop a gradient design tool with explicit PNS constraints and validate the PNS benefits by experimental tests of optimized WB and HO designs. The state-of- the-art boundary element (BEM)-stream function (SF) approach for designing the winding patterns of gradient coils optimizes the magnetic field subject to electrical, mechanical and thermal constraints, but ignores the primary limiting factor; PNS. Although design rules-of-thumb exist, PNS is not directly incorporated in the design step. Instead, PNS is assessed after construction of a coil prototype on volunteers. This is a costly and slow approach that allows only minimal PNS mitigation iteration. In this proposal, we build on our work modeling magneto-stimulation in full-body peripheral nerve models which takes into account: i) the coil wire pattern, ii) the detailed shaping of the induced electric fields by the tissue boundaries, iii) the dependence of the stimulation effect on the relative orientation between electric field and nerves, iv) the non-linear nerve dynamics and their differing properties depending on class (motor, somatosensory or autonomic) and branching distance from the CNS. Our preliminary results indicate that we can increase PNS thresholds by 2X for WB and 1.7X for HO designs. The cost is a moderate increase of the linearity error (5%) and inductance (32%, only required for WB designs). This shows that winding patterns intrinsically contain degrees-of-freedom that can support substantial PNS improvements if one has the tools to uncover them during the design phase. We therefore incorporate our PNS analysis into an industry-standard BEM-SF design optimization framework and validate our results by building and testing the best coil designs in a PNS threshold study of healthy volunteers.

7。项目摘要/摘要 MRI的周围神经刺激（PNS）是由转换引起的电场结果 梯度线圈，可能导致体内最大神经刺激（大直径神经 比小型gmax = 80 mt/m更容易激发。 T/m/s全身体体的mridigents在很大程度上受到PNS而不是放大器功率的约束， 机械的ISSUSE或去除热量和专业线圈，例如Gmax = 300 mt/m，smax = 200 t/m/s “ MGH Connectome”线圈可以在ATS操作操作参数空间中充分使用。 影响PNS的限制将允许更快的成像，更高的分辨率和减少 许多序列常规用于研究和诊所的头部/颈部以及身体成像， 例如EPI，DWI，BSSFP，稀有和螺旋桨。 阈值，但最新一代也有限。 研究和几乎所有临床研究使用体（WB）梯度系统。 在此程序中，我们开发了具有明确PNS约束的梯度设计工具， 通过优化的WB和HO设计来验证PNS的益处。 艺术边界元素（BEM） - 流函数（SF）方法用于设计绕组模式 梯度线圈优化受电气，机械和热约束的磁场， 但是忽略了主要限制因素； 在设计步骤中纳入。 志愿者 这项建议，我们以全身周围神经的MODETO刺激为基础 考虑的模型：i）线圈线模式，ii）诱导的详细塑造 组织边界的电场，iii）刺激对相对的依赖性 电场神经之间的方向，iv）非线性神经动力学和不同 属性取决于类（电动机，体感或自主神经）以及距离分支的分支距离 CNS。我们的初步结果表明，我们可以将PNS阈值增加2倍 对于HO设计。 WB设计需要）。 如果有人在Touncover期间使用工具，则可以支持大量的PNS改进 设计阶段。 优化框架并通过在PNS中构建和测试最佳线圈设计来验证我们的结果 健康志愿者的阈值研究。