Utilizing 7-Tesla Subthalamic Nucleus Connectivity in Deep Brain Stimulation for Parkinson Disease

丘脑底核 脑深部刺激 帕金森病 医学 刺激 神经科学 功能连接 核心 心理学 疾病 内科学
作者
Varvara Mathiopoulou,Niels Rijks,Matthan W.A. Caan,Luka C. Liebrand,Francisca Ferreira,Rob M.A. de Bie,Pepijn van den Munckhof,P. Richard Schuurman,Maarten Bot
出处
期刊:Neuromodulation [Elsevier BV]
卷期号:26 (2): 333-339 被引量:15
标识
DOI:10.1016/j.neurom.2022.01.003
摘要

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a highly effective surgical treatment for patients with advanced Parkinson disease (PD). Combining 7.0-Tesla (7T) T2- and diffusion-weighted imaging (DWI) sequences allows for selective segmenting of the motor part of the STN and, thus, for possible optimization of DBS.7T T2 and DWI sequences were obtained, and probabilistic segmentation of motor, associative, and limbic STN segments was performed. Left- and right-sided motor outcome (Movement Disorders Society Unified Parkinson's Disease Rating Scale) scores were used for evaluating the correspondence between the active electrode contacts in selectively segmented STN and the clinical DBS effect. The Bejjani line was reviewed for crossing of segments.A total of 50 STNs were segmented in 25 patients and proved highly feasible. Although the highest density of motor connections was situated in the dorsolateral STN for all patients, the exact partitioning of segments differed considerably. For all the active electrode contacts situated within the predominantly motor-connected segment of the STN, the average hemi-body Unified Parkinson's Disease Rating Scale motor improvement was 80%; outside this segment, it was 52% (p < 0.01). The Bejjani line was situated in the motor segment for 32 STNs.The implementation of 7T T2 and DWI segmentation of the STN in DBS for PD is feasible and offers insight into the location of the motor segment. Segmentation-guided electrode placement is likely to further improve motor response in DBS for PD. However, commercially available DBS software for postprocessing imaging would greatly facilitate widespread implementation.
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