Accurate and reliable computational dosimetry and targeting for transcranial magnetic stimulation

准确可靠的计算剂量测定和经颅磁刺激靶向

• 批准号: 9892046
• 负责人: Luis Javier Gomez
• 金额: $ 7.55万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2020-09-09
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9892046
• 关键词: Address; Algorithms; Anatomy; Brain; Brain Diseases; Clinical; Computer Models; Computer Simulation; Computing Methodologies; Confidence Intervals; Data; Development; Dose; Drug or chemical Tissue Distribution; Electricity; Electroencephalography; Electromagnetic Fields; Ensure; Exposure to; FDA approved; Generations; Geometry; Head; Hour; Individual; Individual Differences; Magnetic Resonance Imaging; Measurement; Measures; Mediating; Medical; Mental Depression; Mental disorders; Methods; Migraine; Modeling; Neuronavigation; Neurosciences; Neurosciences Research; Outcome; Physiological; Population; Positioning Attribute; Prefrontal Cortex; Probability; Procedures; Process; Psychiatric therapeutic procedure; Reproducibility; Research; Research Personnel; Resolution; Scalp structure; Schizophrenia; Scientist; Source; Stroke; System; Techniques; Technology; Time; Tissues; Transcranial magnetic stimulation; Uncertainty; Variant; Work; base; chronic pain; clinical application; computer framework; cost; dosimetry; electric field; imaging Segmentation; improved; interest; nervous system disorder; neuronal circuitry; neuroregulation; research study; simulation; statistics; tool

Transcranial magnetic stimulation (TMS) is a noninvasive technique used for neuroscience research and treatment of psychiatric and neurological disorders. During TMS, a current-carrying coil placed on the scalp induces an electric field that modulates targeted neuronal circuits. Computational simulations of the electric field (E-field) induced by TMS are increasingly used to gain a mechanistic understanding of the effect of TMS on the brain and to inform its administration. To ensure safe and effective use of computational simulation results, it is of primary importance to systematically quantify and enhance the level of confidence in them. As we show, much of the error inherent to the computational methods deployed for TMS simulation can be controlled by increasing the fidelity of the numerical approximations. However, the accuracy and precision of TMS simulations are still largely uncertain because of inherent variability in TMS setups (e.g. inter-session variability in coil placement and inter-individual differences) and error introduced in the generation of input simulation parameters from experimental data (e.g. error in coil placement measurements and error introduced in an individual head image segmentation process). Finally, there are no existing frameworks that consider this variability in selecting the placement of the TMS coil for most efficient and reliable delivery of E-field to the target. The objective of this project is to develop an uncertainty quantification (UQ) framework for systematically modeling input uncertainties of TMS procedures, quantifying confidence and statistics of TMS simulations, and informing TMS dosimetry. Aim 1 concerns the creation of efficient computational frameworks for rapid and accurate simulation of TMS E-fields. Aim 2 involves the development of UQ methods for analyzing uncertainty and variability in TMS E-field dose. Aim 3 addresses the development of a framework for determining TMS coil placement that maximizes the E- field delivered at the target and minimizes its variability. The proposed work will increase the fidelity and reliability of computational TMS dosimetry and enable more accurate and precise targeting. This could empower TMS researchers and clinicians to quantify statistically the E-field dose, infer sources of variation in experimental and clinical outcomes, and select coil placements that result in increased and consistent efficacy.

经颅磁刺激（TMS）是一种用于神经科学研究和治疗的非侵入性技术。 治疗精神和神经系统疾病。在 TMS 过程中，将载流线圈放置在头皮上 感应调节目标神经元电路的电场。电场的计算模拟 TMS 引起的（电场）越来越多地用于获得 TMS 对 大脑并通知其管理。为保证计算模拟结果的安全、有效利用， 最重要的是系统地量化和增强对它们的信心水平。正如我们所展示的，很多 TMS 模拟所部署的计算方法固有的误差可以通过增加来控制 数值近似的保真度。然而，TMS模拟的准确度和精确度仍然有待提高。 由于 TMS 设置的固有可变性（例如线圈放置的会话间可变性），很大程度上不确定 和个体间的差异）以及在生成输入模拟参数时引入的误差 实验数据（例如线圈放置测量的误差和单个头部图像中引入的误差 分割过程）。最后，没有现有的框架在选择时考虑这种可变性。 TMS 线圈的放置可以最有效、最可靠地将电场传送到目标。此举的目的 该项目旨在开发一个不确定性量化（UQ）框架，用于系统地对输入不确定性进行建模 TMS 程序、量化 TMS 模拟的置信度和统计数据以及为 TMS 剂量测定提供信息。目的 图 1 涉及创建高效的计算框架，以快速、准确地模拟 TMS 电场。 目标 2 涉及开发 UQ 方法来分析 TMS 电场剂量的不确定性和变异性。 目标 3 致力于开发一个框架，用于确定 TMS 线圈的放置，从而最大限度地提高 E- 场传递到目标并最大限度地减少其变化。拟议的工作将提高保真度和可靠性 计算 TMS 剂量测定并实现更准确和精确的定位。这可以增强 TMS 的能力 研究人员和临床医生对电场剂量进行统计量化，推断实验和实验中的变异来源 临床结果，并选择可提高且一致疗效的线圈放置位置。