Validating and optimizing personalized current flow simulations across the human lifespan using in-vivo magnetic resonance current density imaging

使用体内磁共振电流密度成像验证和优化整个人类生命周期的个性化电流模拟

• 批准号: 507084192
• 负责人: Professor Dr.-Ing. Axel Thielscher, Ph.D.
• 金额: --
• 依托单位: Technical University of Denmark
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/507084192?language=en
• 关键词: Validating; optimizing; personalized; current; flow

Computer simulations have become an important tool for characterizing and optimizing the electric field distribution induced by transcranial electric stimulation (tES) in the human brain. Simulations also enable personalized stimulation approaches that control for the impact of different head and brain anatomies on the individual field distribution, and they are an integral component of the research strategy of the research unit (RU). However, as simulations estimate the electric fields based on potentially uncertain information about head anatomy and tissue conductivities, validating their accuracy is highly important. Critically, theoretical analyses and invasive electrode recordings in selected human patients undergoing surgery showed that the accuracy of field simulations can vary strongly between individuals. This generates the risk that potential associations between the estimated fields and the recorded physiological responses are obscured.In project 10 (P10) of the RU, we will for the first time apply magnetic resonance current density imaging (MRCDI) to a large group of subjects in order to systematically and non-invasively validate the electric field simulations used in the RU. The planned work will leverage our recent, comprehensive work on MR acquisition schemes, optimized tES hardware and analytical methods, which helped to mature MRCDI and make it ready for the envisioned large-scale application in humans. We will start by collecting MRCDI data of 40 healthy participants for all target regions used in the RU. We will use this data in a new Bayesian analysis framework to systematically optimize the tissue conductivities of the personalized head models. Employing a Bayesian framework will reveal the uncertainty of the estimated conductivities in a principled manner, and give insight into which conductivities benefit from the optimization by MRCDI. As second step, we aim to extend this approach towards the comparison of head models of varying anatomical complexity using Bayesian model selection. Finally, we will test the impact of anatomical features (skull thickness, CSF volume) and selected demographic variables (age, sex) on the simulation accuracy at the individual level. These results will be used for the development of an optimized head modelling pipeline with improved accuracy which will be implemented in the post-hoc analyses in projects P1-9 of the RU and also provided open source for broad use.Complementing the above work, we will streamline the MRCDI acquisition procedures that currently require expert knowledge. The improved procedures will be pilot-tested within four projects of the RU, making MRCDI ready for a broader usage. In particular, this work will prepare MRCDI for its general use across all projects in the potential second phase of the RU, where changes in skull composition and brain anatomy at old age might require further adaptations of the simulations to ensure accurate field estimates.

计算机仿真已经成为表征和优化经颅电刺激（tES）在人脑中诱导的电场分布的重要工具。模拟还可以实现个性化刺激方法，控制不同头部和大脑解剖结构对个体场分布的影响，并且它们是研究单元（RU）研究策略的组成部分。然而，由于模拟基于关于头部解剖结构和组织电导率的潜在不确定信息来估计电场，因此验证其准确性非常重要。重要的是，理论分析和选定的接受手术的人类患者的侵入性电极记录表明，场模拟的准确性在个体之间可能存在很大差异。在RU的项目10（P10）中，我们将首次将磁共振电流密度成像（MRCDI）应用于一大群受试者，以系统地和非侵入性地验证RU中使用的电场模拟。计划中的工作将利用我们最近在MR采集方案、优化的tES硬件和分析方法方面的全面工作，这些工作有助于成熟MRCDI，并使其为预期的人类大规模应用做好准备。我们将首先收集RU中使用的所有目标区域的40名健康参与者的MRCDI数据。我们将在一个新的贝叶斯分析框架中使用这些数据来系统地优化个性化头部模型的组织电导率。采用贝叶斯框架将以原则性的方式揭示所估计的电导率的不确定性，并深入了解哪些电导率受益于MRCDI的优化。作为第二步，我们的目标是扩展这种方法对头部模型的比较不同的解剖复杂性，使用贝叶斯模型选择。最后，我们将测试解剖特征（颅骨厚度，CSF体积）和选定的人口统计学变量（年龄，性别）在个人水平上对模拟准确性的影响。这些结果将用于开发一个优化的头部建模管道，提高精度，这将在RU项目P1-9的事后分析中实施，并提供开源以广泛使用。作为对上述工作的补充，我们将简化目前需要专业知识的MRCDI采集程序。改进后的程序将在RU的四个项目中进行试点测试，使MRCDI准备更广泛地使用。特别是，这项工作将准备MRCDI在RU潜在的第二阶段的所有项目中的一般使用，其中老年时头骨组成和大脑解剖结构的变化可能需要进一步调整模拟，以确保准确的现场估计。