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非刚性图像配准全自动瞄准匹配准确度和精确度超过最佳手动丘脑底深部脑刺激治疗帕金森病靶向方式

  Fully automated targeting using non-rigid image registration matches accuracy and exceeds precision of best manual approaches to Subthalamic Deep Brain Stimulation targeting in Parkinson's disease

  Neurosurgery. Author manuscript; available in PMC 2015 Jun 1.

  Abstract

  Background

  Finding the optimal location for the implantation of the electrode in Deep Brain Stimulation (DBS) surgery is crucial for maximizing therapeutic benefit to the patient. Such targeting is challenging for several reasons including anatomical variability between patients as well as lack of consensus about the location of the optimal target.

  Objective

  To compare the performance of popular manual targeting methods against a fully automatic non-rigid image registration based approach.

  Methods

  In 71 Parkinson's disease STN-DBS implantations, an experienced functional neurosurgeon selected the target manually using three different approaches; indirect targeting using standard stereotactic coordinates, direct targeting based on the patient MRI, and indirect targeting relative to the red nucleus. Targets were also automatically predicted using a leave-one-out approach to populate the CranialVault atlas using non-rigid 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 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 non-rigid image registration based automatic predictions using the CranialVault atlas (2.70 mm). The CranialVault atlas method had statistically smaller variance than all manual approaches.

  Conclusions

  Fully automatic targeting based on non-rigid image registration using the CranialVault atlas is as accurate and more precise than popular manual methods for STN-DBS.

  Keywords: automatic targeting, deep brain stimulation, non-linear image registration, electrophysiological atlases, Parkinson's disease, subthalamic nucleus