Closed-loop programming using external responses for deep brain stimulation in Parkinson's disease
Closed-loop programming using external responses for deep brain stimulation in Parkinson's disease
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DOI：
10.1016/j.parkreldis.2021.01.023
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发表时间：
2021-02-05
影响因子：
4.1
通讯作者：
Hattori, Nobutaka
中科院分区：
文献类型：
--
作者：
Sasaki, Fuyuko;Oyama, Genko;Hattori, Nobutaka
脑深部电刺激（DBS）是治疗帕金森病（PD）的有效方法。由于经验不足、时间限制以及DBS技术的最新进展，临床医生在调整DBS的刺激参数和配置时面临着各种挑战。我们的目的是评估闭环算法（CLA）的dbs编程方法的有效性，该方法使用基于外部运动传感器的运动评估在PD患者中。方法：在这项随机、双盲、交叉研究中，我们招募了12名接受双侧丘脑下核8环接触DBS导联植入的患者。参与者的DBS设置使用护理标准（SOC）和CLA方法进行编程。以随机交叉方式评估两种编程方法的临床效果。使用统一帕金森病量表第三部分（UPDRS-III）和基于传感器的基线评分（药物停用/刺激停用）以及两种编程方法对结果进行评估。还记录了每种编程方法所需的编程步骤数。结果：与基线相比，SOC和CLA设置显著提高了UPDRS-III评分和基于传感器的评分。SOC与CLA之间无统计学差异。与SOC相比，CLA设置显著减少了编程步骤。未观察到严重不良事件。结论：CLA可优化DBS设置，其治疗效果与SOC相似，并可减少编程步骤。自动优化DBS设置将减轻临床医生和患者的编程负担。
Introduction: Deep brain stimulation (DBS) is an established treatment for Parkinson's disease (PD). Clinicians face various challenges in adjusting stimulation parameters and configurations in clinical DBS settings owing to inexperience, time constraints, and recent advances in DBS technology that have expanded the number of possible contact configurations. We aimed to assess the efficacy of a closed-loop algorithm (CLA) for the DBS-programming method using external motion sensor-based motor assessments in patients with PD.Methods: In this randomized, double-blind, crossover study, we enrolled 12 patients who underwent eight-ring-contact DBS lead implantations bilaterally in the subthalamic nucleus. The DBS settings of the participants were programmed using a standard of care (SOC) and CLA method. The clinical effects of both programming methods were assessed in a randomized crossover fashion. The outcomes were evaluated using the Unified Parkinson's Disease Scale part III (UPDRS-III) and sensor-based scores for baseline (medication-off/stimulation-off) and both programming methods. The number of programming steps required for each programming method was also recorded.Results: The UPDRS-III scores and sensor-based scores were significantly improved by SOC and CLA settings compared to the baseline. No statistical difference was observed between SOC and CLA. The programming steps were significantly reduced in the CLA settings compared to those in the SOC. No serious adverse events were observed.Conclusion: CLA can optimize DBS settings prospectively with similar therapeutic benefits as that of the SOC and reduce the number of programming steps. Automated optimization of DBS settings would reduce the burden of programming for both clinicians and patients.