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DBStar:一个用于患者定制深部脑刺激平台成像分析的开源工具包。

DBStar: An Open-Source Tool Kit for Imaging Analysis with Patient-Customized Deep Brain Stimulation Platforms.

作者信息

Lauro Peter M, Lee Shane, Ahn Minkyu, Barborica Andrei, Asaad Wael F

机构信息

The Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.

Department of Neuroscience, Brown University, Providence, Rhode Island, USA.

出版信息

Stereotact Funct Neurosurg. 2018;96(1):13-21. doi: 10.1159/000486645. Epub 2018 Feb 7.

Abstract

BACKGROUND/OBJECTIVES: To create an open-source method for reconstructing microelectrode recording (MER) and deep brain stimulation (DBS) electrode coordinates along multiple parallel trajectories with patient-specific DBS implantation platforms to facilitate DBS research.

METHODS

We combined the surgical geometry (extracted from WayPoint Planner), pre-/intra-/postoperative computed tomography (CT) and/or magnetic resonance (MR) images, and integrated them into the Analysis of Functional NeuroImages (AFNI) neuroimaging analysis environment using functions written in Python. Electrode coordinates were calculated from image-based electrode surfaces and recording trajectory depth values. Coordinates were translated into appropriate trajectories, and were tested for proximity to patient-specific or atlas-based anatomical structures. Final DBS electrode coordinates for 3 patient populations (ventral intermediate nucleus [VIM], subthalamic nucleus [STN], and globus pallidus pars interna [GPi]) were calculated. For STN cases, MER site coordinates were then analyzed to see whether they were inside or outside the STN.

RESULTS

Final DBS electrode coordinates were described for VIM, STN, and GPi patient populations. 115/169 (68%) STN MER sites were within 1 mm of the STN in AFNI's Talairach and Tournoux (TT) atlas.

CONCLUSIONS

DBStar is a robust tool kit for understanding the anatomical location and context of electrode locations, and can easily be used for imaging, behavioral, or electrophysiological analyses.

摘要

背景/目的:创建一种开源方法,用于在患者特异性脑深部电刺激(DBS)植入平台上沿着多条平行轨迹重建微电极记录(MER)和DBS电极坐标,以促进DBS研究。

方法

我们结合了手术几何结构(从WayPoint Planner中提取)、术前/术中/术后计算机断层扫描(CT)和/或磁共振(MR)图像,并使用用Python编写的函数将它们集成到功能神经影像分析(AFNI)神经影像分析环境中。电极坐标根据基于图像的电极表面和记录轨迹深度值计算得出。坐标被转换为适当的轨迹,并测试其与患者特异性或基于图谱的解剖结构的接近程度。计算了3组患者群体(腹中间核[VIM]、丘脑底核[STN]和内侧苍白球[GPi])的最终DBS电极坐标。对于STN病例,随后分析MER位点坐标以确定它们是否在STN内部或外部。

结果

描述了VIM、STN和GPi患者群体的最终DBS电极坐标。在AFNI的Talairach和Tournoux(TT)图谱中,115/169(68%)的STN MER位点距离STN在1毫米以内。

结论

DBStar是一个强大的工具包,用于了解电极位置的解剖位置和背景,并且可以轻松用于成像、行为或电生理分析。

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