Realistic volumetric-approach to simulate transcranial electric stimulation-ROAST-a fully automated open-source pipeline
Realistic volumetric-approach to simulate transcranial electric stimulation-ROAST-a fully automated open-source pipeline
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DOI：
10.1088/1741-2552/ab208d
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发表时间：
2019-10-01
影响因子：
4
通讯作者：
Parra, Lucas C.
中科院分区：
文献类型：
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作者：
Huang, Yu;Datta, Abhishek;Parra, Lucas C.
目标。经颅电刺激(TES)领域的研究通常依赖于脑内电流的计算模型。模型是基于人头的磁共振图像(MRI)建立的，以捕捉详细的个体解剖。为了模拟个体上的电流流动，对受试者的MRI进行分割，在该解剖模型上放置虚拟电极，将体积网格划分为网格，并通过数值求解有限元模型来估计电流流动。这些步骤中的每一步都有各种软件工具可用，以及连接这些工具以进行自动化或半自动处理的处理管道。本工具-模拟经颅电模拟(ROAST)的真实体积方法-的目标是提供一种端到端的管道，该管道可以利用开放源代码软件和定制脚本来改进分割和执行电极放置，从而自动处理具有真实体积解剖的个体头部。接近。Roast结合了SPM12的分割算法、用于修饰和自动电极放置的MatLab脚本、有限元网格分割器Iso2 Mesh和求解器getDP。我们将其与商业有限元软件以及成熟的开源建模管道SimNIBS的性能进行了比较。主要结果。用焙烧法计算的电场与商用网格划分和有限元求解软件得到的结果相差不大。我们也没有发现Roast和SimNIBS使用的各种自动分割方法之间有很大的差异。当在SimNIBS中体分割转换为曲面时，我们确实发现了更大的差异。然而，对来自人类受试者的颅内记录的评估表明，如果用户对SimNIBS有详细的了解，则ROAST和SimNIBS在预测场分布方面没有显著差异。意义重大。我们希望这里提供的对此建模管道中的各种选择的详细比较可以为未来的工具开发提供指导。我们发布了Roast，这是一个开源、易于安装和全自动化的管道，用于个性化的TES建模。
Objective. Research in the area of transcranial electrical stimulation (TES) often relies on computational models of current flow in the brain. Models are built based on magnetic resonance images (MRI) of the human head to capture detailed individual anatomy. To simulate current flow on an individual, the subject's MRI is segmented, virtual electrodes are placed on this anatomical model, the volume is tessellated into a mesh, and a finite element model (FEM) is solved numerically to estimate the current flow. Various software tools are available for each of these steps, as well as processing pipelines that connect these tools for automated or semi-automated processing. The goal of the present tool-realistic volumetric-approach to simulate transcranial electric simulation (ROAST)-is to provide an end-to-end pipeline that can automatically process individual heads with realistic volumetric anatomy leveraging open-source software and custom scripts to improve segmentation and execute electrode placement. Approach. ROAST combines the segmentation algorithm of SPM12, a Matlab script for touch-up and automatic electrode placement, the finite element mesher iso2mesh and the solver getDP. We compared its performance with commercial FEM software, and SimNIBS, a well-established open-source modeling pipeline. Main results. The electric fields estimated with ROAST differ little from the results obtained with commercial meshing and FEM solving software. We also do not find large differences between the various automated segmentation methods used by ROAST and SimNIBS. We do find bigger differences when volumetric segmentation are converted into surfaces in SimNIBS. However, evaluation on intracranial recordings from human subjects suggests that ROAST and SimNIBS are not significantly different in predicting field distribution, provided that users have detailed knowledge of SimNIBS. Significance. We hope that the detailed comparisons presented here of various choices in this modeling pipeline can provide guidance for future tool development. We released ROAST as an open-source, easy-to-install and fully-automated pipeline for individualized TES modeling.