4.6 Article

Fully Automated Targeting Using Nonrigid Image Registration Matches Accuracy and Exceeds Precision of Best Manual Approaches to Subthalamic Deep Brain Stimulation Targeting in Parkinson Disease

期刊

NEUROSURGERY
卷 76, 期 6, 页码 756-763

出版社

OXFORD UNIV PRESS INC
DOI: 10.1227/NEU.0000000000000714

关键词

Automatic targeting; Deep brain stimulation; Electrophysiological atlases; Nonlinear image registration; Parkinson disease; Subthalamic nucleus

资金

  1. NIH [R01 EB006136]

向作者/读者索取更多资源

BACKGROUND: Finding the optimal location for the implantation of the electrode in deep brain stimulation (DBS) surgery is crucial for maximizing the therapeutic benefit to the patient. Such targeting is challenging for several reasons, including anatomic variability between patients as well as the lack of consensus about the location of the optimal target. OBJECTIVE: To compare the performance of popular manual targeting methods against a fully automatic nonrigid image registration-based approach. METHODS: In 71 Parkinson disease subthalamic nucleus (STN)-DBS implantations, an experienced functional neurosurgeon selected the target manually using 3 different approaches: indirect targeting using standard stereotactic coordinates, direct targeting based on the patient magnetic resonance imaging, and indirect targeting relative to the red nucleus. Targets were also automatically predicted by using a leave-one-out approach to populate the CranialVault atlas with the use of nonrigid image registration. The different targeting methods were compared against the location of the final active contact, determined through iterative clinical programming in each individual patient. RESULTS: Targeting by using standard stereotactic coordinates corresponding to the center of the motor territory of the STN had the largest targeting error (3.69 mm), followed by direct targeting (3.44 mm), average stereotactic coordinates of active contacts from this study (3.02 mm), red nucleus-based targeting (2.75 mm), and nonrigid image registration-based automatic predictions using the CranialVault atlas (2.70 mm). The CranialVault atlas method had statistically smaller variance than all manual approaches. CONCLUSION: Fully automatic targeting based on nonrigid image registration with the use of the CranialVault atlas is as accurate and more precise than popular manual methods for STN-DBS.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据