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机器人辅助癫痫手术中的电极放置精度:基于 CT 的框架与基于 CT 或 MRI 的面部激光扫描的不同参考技术的比较。

Electrode placement accuracy in robot-assisted epilepsy surgery: A comparison of different referencing techniques including frame-based CT versus facial laser scan based on CT or MRI.

机构信息

Department of Neurosurgery, University Hospital Frankfurt - Goethe-University, Frankfurt am Main, Germany.

Department of Neurosurgery, University Hospital Frankfurt - Goethe-University, Frankfurt am Main, Germany.

出版信息

Epilepsy Behav. 2019 Feb;91:38-47. doi: 10.1016/j.yebeh.2018.11.002. Epub 2018 Nov 27.


DOI:10.1016/j.yebeh.2018.11.002
PMID:30497893
Abstract

BACKGROUND: Precise robotic or stereotactic implantation of stereoelectroencephalography (sEEG) electrodes relies on the exact referencing of the planning images in order to match the patient's anatomy to the stereotactic device or robot. We compared the accuracy of sEEG electrode implantation with stereotactic frame versus laser scanning of the face based on computed tomography (CT) or magnetic resonance imaging (MRI) datasets for referencing. METHODS: The accuracy was determined by calculating the Euclidian distance between the planned trajectory and the postoperative position of the sEEG electrode, defining the entry point error (EPE) and the target point error (TPE). The sEEG electrodes (n = 171) were implanted with the robotic surgery assistant (ROSA) in 19 patients. Preoperative trajectory planning was performed on three-dimensional (3D) MRI datasets. Referencing was accomplished either by performing (A) 1.25-mm slice CT with the patient's head fixed in a Leksell stereotactic frame (CT-frame, n = 49), fused with a 3D-T1-weighted, contrast enhanced- and T2-weighted 1.5 Tesla (T) MRI; (B) 1.25 mm CT (CT-laser, n = 60), fused with 3D-3.0-T MRI; (C) 3.0-T MRI T1-based laser scan (3.0-T MRI-laser, n = 56) or (D) in one single patient, because of a pacemaker, 3D-1.5-T MRI T1-based laser scan (1.5-T MRI-laser, n = 6). RESULTS: In (A) CT-frame referencing, the mean EPE amounted to 0.86 mm and the mean TPE amounted to 2.28 mm (n = 49). In (B) CT-laser referencing, the EPE amounted to 1.85 mm and the TPE to 2.41 mm (n = 60). In (C) 3.0-T MRI-laser referencing, the mean EPE amounted to 3.02 mm and the mean TPE to 3.51 mm (n = 56). In (D) 1.5-T MRI, surprisingly the mean EPE amounted only to 0.97 mm and the TPE to 1.71 mm (n = 6). In 3 cases using CT-laser and 1 case using 3.0 T MRI-laser for referencing, small asymptomatic intracerebral hemorrhages were detected. No further complications were observed. CONCLUSION: Robot-guided sEEG electrode implantation using CT-frame referencing and CT-laser-based referencing is most accurate and can serve for high precision placement of electrodes. In contrast, 3.0-T MRI-laser-based referencing is less accurate, but saves radiation. Most trajectories can be reached if alternative routes over less vascularized brain areas are used. This article is part of the Special Issue "Individualized Epilepsy Management: Medicines, Surgery and Beyond".

摘要

背景:精确的机器人或立体定向脑电图(sEEG)电极植入依赖于计划图像的精确参照,以便将患者的解剖结构与立体定向设备或机器人相匹配。我们比较了基于 CT 或 MRI 数据集的立体定向框架与激光扫描对面部进行参照时 sEEG 电极植入的准确性。

方法:通过计算计划轨迹与 sEEG 电极术后位置之间的欧几里得距离来确定准确性,定义进入点误差(EPE)和目标点误差(TPE)。机器人手术助手(ROSA)在 19 名患者中植入了 171 个 sEEG 电极。术前轨迹规划在三维(3D)MRI 数据集上进行。参照通过以下方式完成:(A)在患者头部固定在 Leksell 立体定向框架中进行 1.25-mm 切片 CT(CT-frame,n=49),与 3D-T1 加权、对比增强和 T2 加权 1.5T(T)MRI 融合;(B)1.25mm CT(CT-laser,n=60),与 3D-3.0T MRI 融合;(C)3.0T MRI T1 基础激光扫描(3.0-T MRI-laser,n=56);或(D)在一名因起搏器而无法使用立体定向框架和激光扫描的患者中,仅使用 3D-1.5T MRI T1 基础激光扫描(1.5-T MRI-laser,n=6)。

结果:在(A)CT-frame 参照中,EPE 的平均值为 0.86mm,TPE 的平均值为 2.28mm(n=49)。在(B)CT-laser 参照中,EPE 的平均值为 1.85mm,TPE 的平均值为 2.41mm(n=60)。在(C)3.0-T MRI-laser 参照中,EPE 的平均值为 3.02mm,TPE 的平均值为 3.51mm(n=56)。在(D)1.5-T MRI 中,令人惊讶的是,EPE 的平均值仅为 0.97mm,TPE 的平均值为 1.71mm(n=6)。在使用 CT-laser 和 1 例使用 3.0T MRI-laser 进行参照的 3 例病例中,发现了小的无症状性颅内出血。未观察到其他并发症。

结论:使用 CT 框架参照和 CT 激光参照的机器人引导 sEEG 电极植入术最为准确,可以实现电极的高精度放置。相比之下,3.0-T MRI 激光参照的准确性较低,但可减少辐射。如果使用经过较少血管化脑区的替代路径,大多数轨迹都可以到达。本文是“个体化癫痫管理:药物、手术及其他”特刊的一部分。

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[3]
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Oper Neurosurg (Hagerstown). 2025-3-1

[4]
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J Korean Neurosurg Soc. 2024-11

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[6]
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[7]
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[8]
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[9]
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[10]
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