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: 10260604
• 负责人: Luis Javier Gomez
• 金额: $ 22.67万
• 依托单位: PURDUE 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 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10260604
• 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; noninvasive brain stimulation; 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的非侵入性技术， 治疗精神和神经疾病。在TMS期间，将载流线圈放置在头皮上 诱导电场调节目标神经元回路。电场的计算模拟 （电场）诱导的TMS越来越多地用于获得一个机制的理解TMS的影响， 大脑并告知其管理。为了确保安全有效地使用计算模拟结果， 最重要的是系统地量化和提高对它们的信任程度。正如我们所展示的， TMS模拟所采用的计算方法的固有误差可以通过增加 数值近似的保真度。然而，TMS模拟的准确性和精度仍然是 由于TMS设置的固有可变性（例如，线圈放置的会话间可变性）， 和个体间差异）和在从输入模拟参数生成中引入的误差 实验数据（例如，线圈放置测量中的误差和个体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 TMS线圈的放置，以最有效和可靠地将电场输送到目标。的目的 项目是开发一个不确定性量化（UQ）框架，用于系统地建模输入不确定性 的TMS程序，量化的信心和TMS模拟的统计，并告知TMS剂量。目的 1涉及建立有效的计算框架，快速和准确的模拟TMS电场。 目标2涉及用于分析TMS电场剂量的不确定性和可变性的UQ方法的发展。 目标3解决了确定TMS线圈放置的框架的发展，最大限度地提高了E- 场在目标处传递并最小化其可变性。所提出的工作将提高保真度和可靠性 的计算TMS剂量测定，并使更准确和精确的目标。这可以使TMS 研究人员和临床医生在统计上量化电场剂量，推断实验和 临床结果，并选择线圈放置，从而提高和一致的疗效。