优化经颅磁刺激线圈放置的刺激效应映射。

IF 2.7 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Gangliang Zhong, Fang Jin, Liang Ma, Yongfeng Yang, Baogui Zhang, Dan Cao, Jin Li, Nianming Zuo, Lingzhong Fan, Zhengyi Yang, Tianzi Jiang
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引用次数: 0

摘要

经颅磁刺激(TMS)线圈的位置和方向,我们统称为线圈的放置,显著影响皮质兴奋性的评估和调节。TMS电场(e场)模拟可用于确定最佳线圈布局。然而,目前的电场模拟需要费力的分割和网格划分程序来确定最佳线圈位置。我们打算创建一个框架,使我们能够提供最佳的线圈位置,而不需要分割和网格划分过程。我们使用CASIA数据集构建了刺激效应图(SEM)框架,以优化线圈的放置。我们使用留一受试者的交叉验证来评估CASIA、HCP15和HCP100数据集的MRI数据中74个目标roi的最佳线圈放置与SEM确定的目标区域的一致性。此外,我们对比了基于DP和CASIA II数据集,使用SEM和辅助偶极子方法(ADM)确定的最佳线圈放置的e规范。我们在“基于头部解剖”(HAC)极坐标和目标区域的MNI坐标中提供了最佳线圈放置位置。结果还证明了74个目标roi的SEM框架的一致性。SEM测定的正常电场比adm得到的值更显著。我们使用CASIA数据库创建了SEM框架,以确定最佳线圈位置,而不进行分割或网格划分。我们为目标区域提供了HAC和MNI坐标下的最佳线圈位置。来自不同数据集的几个目标roi的验证证明了SEM方法的一致性。通过简化寻找最佳线圈放置的过程,我们打算使经颅磁刺激评估和治疗更方便。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stimulation Effects Mapping for Optimizing Coil Placement for Transcranial Magnetic Stimulation.

The position and orientation of transcranial magnetic stimulation (TMS) coil, which we collectively refer to as coil placement, significantly affect both the assessment and modulation of cortical excitability. TMS electric field (E-field) simulation can be used to identify optimal coil placement. However, the present E-field simulation required a laborious segmentation and meshing procedure to determine optimal coil placement. We intended to create a framework that would enable us to offer optimal coil placement without requiring the segmentation and meshing procedure. We constructed the stimulation effects map (SEM) framework using the CASIA dataset for optimal coil placement. We used leave-one-subject-out cross-validation to evaluate the consistency of the optimal coil placement and the target regions determined by SEM for the 74 target ROIs in MRI data from the CASIA, HCP15 and HCP100 datasets. Additionally, we contrasted the E-norms determined by optimal coil placements using SEM and auxiliary dipole method (ADM) based on the DP and CASIA II datasets. We provided optimal coil placement in 'head-anatomy-based' (HAC) polar coordinates and MNI coordinates for the target region. The results also demonstrated the consistency of the SEM framework for the 74 target ROIs. The normal E-field determined by SEM was more significant than the value received by ADM. We created the SEM framework using the CASIA database to determine optimal coil placement without segmentation or meshing. We provided optimal coil placement in HAC and MNI coordinates for the target region. The validation of several target ROIs from various datasets demonstrated the consistency of the SEM approach. By streamlining the process of finding optimal coil placement, we intended to make TMS assessment and therapy more convenient.

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来源期刊
Neuroinformatics
Neuroinformatics 医学-计算机:跨学科应用
CiteScore
6.00
自引率
6.70%
发文量
54
审稿时长
3 months
期刊介绍: Neuroinformatics publishes original articles and reviews with an emphasis on data structure and software tools related to analysis, modeling, integration, and sharing in all areas of neuroscience research. The editors particularly invite contributions on: (1) Theory and methodology, including discussions on ontologies, modeling approaches, database design, and meta-analyses; (2) Descriptions of developed databases and software tools, and of the methods for their distribution; (3) Relevant experimental results, such as reports accompanie by the release of massive data sets; (4) Computational simulations of models integrating and organizing complex data; and (5) Neuroengineering approaches, including hardware, robotics, and information theory studies.
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