Wagle Shukla Aparna, Bange Manuel, Muthuraman Muthuraman
Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA.
Informatics for Medical Technology, Institute of Computer Science, University Augsburg, Augsburg, Germany.
NPJ Parkinsons Dis. 2025 Jul 1;11(1):195. doi: 10.1038/s41531-025-01015-x.
In Parkinson's disease (PD), several key factors influence patient selection for deep brain stimulation (DBS) as they directly affect long-term outcomes. A comprehensive interdisciplinary assessment is the first step to evaluating risks, benefits, and establishing appropriate goals. Patient-defined symptom priorities play a critical role in selecting the brain target for DBS. The entry of multiple manufacturers of hardware has spurred a rapid acceleration of technological progress. While innovations in programming such as sensing-based physiology-guided programming have introduced the concept of delivering an optimal or "Goldilocks dose", a precise, personalized therapy to address specific PD symptoms, image-guided programming acts like a "GPS," enabling faster determination of dose parameters. Emerging tools such as adaptive and automated programming offer clinicians the potential to provide optimal, energy-efficient stimulation. This review, integrating both old and well-established knowledge and new insights, provides a comprehensive summary of the multidimensional aspects of patient selection, target-specific benefits, advancements in hardware technology, and innovative strategies that are either currently available or on the horizon for DBS programming.
在帕金森病(PD)中,有几个关键因素会影响深部脑刺激(DBS)患者的选择,因为它们直接影响长期疗效。全面的跨学科评估是评估风险、益处以及确立适当目标的第一步。患者确定的症状优先级在选择DBS的脑靶点方面起着关键作用。多个硬件制造商的进入推动了技术进步的快速加速。虽然诸如基于传感的生理引导编程等编程创新引入了提供最佳或“恰到好处剂量”的概念,即一种针对特定PD症状的精确、个性化治疗,但图像引导编程就像一个“全球定位系统”,能够更快地确定剂量参数。诸如自适应和自动编程等新兴工具为临床医生提供了提供最佳、节能刺激的潜力。这篇综述整合了既有知识和新见解,全面总结了患者选择、靶点特异性益处、硬件技术进展以及DBS编程当前可用或即将出现的创新策略等多维度方面。