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帕金森病的适应性深部脑刺激:综述

Toward adaptive deep brain stimulation in Parkinson's disease: a review.

作者信息

Mohammed Ameer, Bayford Richard, Demosthenous Andreas

机构信息

Department of Electronic & Electrical Engineering, University College London, Torrington Place, London WC1E 7JE, UK.

Department of Natural Sciences, Middlesex University, The Burroughs, London NW4 6BT, UK.

出版信息

Neurodegener Dis Manag. 2018 Apr;8(2):115-136. doi: 10.2217/nmt-2017-0050. Epub 2018 Apr 25.

Abstract

Clinical deep brain stimulation (DBS) is now regarded as the therapeutic intervention of choice at the advanced stages of Parkinson's disease. However, some major challenges of DBS are stimulation induced side effects and limited pacemaker battery life. Side effects and shortening of pacemaker battery life are mainly as a result of continuous stimulation and poor stimulation focus. These drawbacks can be mitigated using adaptive DBS (aDBS) schemes. Side effects resulting from continuous stimulation can be reduced through adaptive control using closed-loop feedback, while those due to poor stimulation focus can be mitigated through spatial adaptation. Other advantages of aDBS include automatic, rather than manual, initial adjustment and programming, and long-term adjustments to maintain stimulation parameters with changes in patient's condition. Both result in improved efficacy. This review focuses on the major areas that are essential in driving technological advances for the various aDBS schemes. Their challenges, prospects and progress so far are analyzed. In addition, important advances and milestones in state-of-the-art aDBS schemes are highlighted - both for closed-loop adaption and spatial adaption. With perspectives and future potentials of DBS provided at the end.

摘要

临床深部脑刺激(DBS)目前被视为帕金森病晚期的首选治疗干预手段。然而,DBS存在一些重大挑战,如刺激引起的副作用和起搏器电池寿命有限。副作用和起搏器电池寿命缩短主要是持续刺激和刺激靶点不佳所致。使用自适应深部脑刺激(aDBS)方案可减轻这些缺点。通过闭环反馈的自适应控制可减少持续刺激产生的副作用,而通过空间自适应可减轻因刺激靶点不佳导致的副作用。aDBS的其他优点包括自动而非手动的初始调整和编程,以及根据患者病情变化进行长期调整以维持刺激参数。两者都能提高疗效。本综述重点关注推动各种aDBS方案技术进步的关键领域。分析了它们目前面临的挑战、前景和进展。此外,还突出了最先进的aDBS方案在闭环自适应和空间自适应方面的重要进展和里程碑。最后阐述了DBS的前景和未来潜力。

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