DBS-Expert: Automated Deep Brain Stimulation Programming Using Functional Mapping

DBS-Expert：使用功能映射进行自动深部脑刺激编程

• 批准号: 8454774
• 负责人: Dustin A. Heldman
• 金额: $ 28.38万
• 依托单位: GREAT LAKES NEUROTECHNOLOGIES
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-28 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8454774
• 关键词: Address; Adverse effects; Affect; Algorithms; Anatomy; Bradykinesia; Caring; Clinic; Clinical; Clinical Research; Computer software; Consumption; Country; Deep Brain Stimulation; Development; Diagnostic; Disease Management; Dyskinetic syndrome; Electric Stimulation; Electrophysiology (science); Expert Systems; Freedom; Frequencies; Future; Gait; General Practitioners; Hand; Home environment; Implant; Intelligence; Lead; Manufacturer Name; Maps; Measures; Modeling; Motion; Motor; Movement Disorders; NIH Program Announcements; Neurologist; Nurses; Outcome; Output; Parkinson Disease; Patients; Phase; Physiologic pulse; Postoperative Period; Process; Severities; Shapes; Site; Software Tools; Specialized Center; Surveys; Symptoms; System; Technology; Therapeutic; Time; Tissues; Tremor; Width; base; cost efficient; design; electric field; experience; improved; neurotechnology; programs; prototype; response; sensor; software development; success; tool

DESCRIPTION (provided by applicant): The objective is to design, build, and clinically assess DBS-Expert, an expert system for optimizing the postoperative programming of deep brain stimulation (DBS) systems in patients with movement disorders such as Parkinson's disease (PD). DBS-Expert will use motion sensor based assessments to develop a functional map and algorithms for navigating the programming parameter space that maximize symptomatic benefits while minimizing side effects and battery consumption. The clinical utility of DBS for the treatment of movement disorders such as PD is well been established. However, there is a great disparity in outcomes among DBS recipients due to varied postoperative management, particularly concerning DBS programming optimization. Most programmers have only a cursory understanding of electrophysiology and lack the expertise or time required to determine an optimal set of DBS parameters (contact, polarity, frequency, pulse width, and amplitude) out of the thousands of possible combinations. DBS-Expert will remove the guesswork from programming and take the responsibility out of the hands of the clinicians by providing an expert system that efficiently determines appropriate DBS settings. DBS-Expert will be designed for use by a general practitioner or nurse rather than by a neurologist or neurophysiologist with years of experience in DBS programming and disease management. For the first postoperative programming session, the DBS-Expert will perform an automated monopolar survey. The patient will wear our existing motion sensor unit and perform motor assessments at various DBS settings. Stimulation will be incrementally increased from zero at each contact until symptoms stop improving as measured by a motion sensor unit or side effects appear. The monopolar survey will help determine the functional anatomy around the lead site and narrow the search space for determining an optimal set of programming parameters. This therapeutic window will be valuable at the initial postoperative programming session as well as all future adjustment sessions. In Phase I, we aim to demonstrate technical feasibility by developing software for automated functional mapping of the DBS programming parameter space and clinical feasibility by developing algorithms that efficiently navigate the programming parameter space and output settings that reduce symptoms, side effects, and battery usage as well or better than would an expert clinician programmer. Ten subjects with PD and a DBS implant will participate in a clinical study in which the DBS-Expert prototype guides the subjects through assessments as part of a constant-current monopolar review. A functional map will be developed and algorithms will determine an optimal set of DBS settings. Subject symptom severities, side effects, and battery usage will be compared to that of an experience DBS programmer. The final DBS-Expert system resulting from Phase I and II development will greatly expand the accessibility of DBS for patients not located near specialized centers by removing the programming burden from a few expert clinicians thereby equalizing care across the country. PUBLIC HEALTH RELEVANCE: The clinical utility of deep brain stimulation (DBS) for the treatment of movement disorders such as Parkinson's disease has been well established; however, there is a great disparity in outcomes among DBS recipients due to varied postoperative management, particularly concerning the choosing of an optimal set of programming parameters from the thousands of possible combinations. The proposed system will use motion sensor based assessments to develop a functional map and algorithms to determine a set of programming parameters that maximize symptomatic benefits while minimizing side effects and battery consumption.

描述（由申请人提供）：目标是设计、构建和临床评估 DBS-Expert，这是一个专家系统，用于优化帕金森病 (PD) 等运动障碍患者的深部脑刺激 (DBS) 系统术后编程。 DBS-Expert 将使用基于运动传感器的评估来开发功能图和算法，用于导航编程参数空间，从而最大限度地提高症状效益，同时最大限度地减少副作用和电池消耗。 DBS 的临床应用 帕金森病等运动障碍的治疗方法已经很成熟。然而，由于术后管理的不同，特别是在 DBS 编程优化方面，DBS 接受者之间的结果存在很大差异。大多数程序员对电生理学只有粗略的了解，并且缺乏从数千种可能的组合中确定一组最佳 DBS 参数（接触、极性、频率、脉冲宽度和幅度）所需的专业知识或时间。 DBS-Expert 将消除编程中的猜测，并通过提供有效确定适当 DBS 设置的专家系统，将责任从临床医生手中移开。 DBS-Expert 专为全科医生或护士设计，而不是由在 DBS 编程和疾病管理方面拥有多年经验的神经科医生或神经生理学家使用。对于第一次术后编程会议，DBS-专家将执行自动单极调查。患者将佩戴我们现有的运动传感器装置，并在各种 DBS 设置下进行运动评估。每次接触时刺激将从零逐渐增加，直到运动传感器单元测量到症状停止改善或出现副作用。单极调查将有助于确定引导部位周围的功能解剖结构，并缩小搜索空间，以确定一组最佳的编程参数。这个治疗窗口对于最初的术后规划课程以及所有未来的调整课程都很有价值。在第一阶段，我们的目标是通过开发用于 DBS 编程参数空间自动功能映射的软件来证明技术可行性，并通过开发有效导航编程参数空间和输出设置的算法来证明临床可行性，从而减少症状、副作用和电池使用，甚至比专业临床医生程序员更好。十名患有 PD 和 DBS 植入物的受试者将参加一项临床研究，其中 DBS-Expert 原型将指导受试者进行评估，作为恒流单极审查的一部分。将开发功能图，算法将确定一组最佳 DBS 设置。受试者症状的严重程度、副作用和电池使用情况将与经验丰富的 DBS 程序员进行比较。第一阶段和第二阶段开发产生的最终 DBS-Expert 系统将通过消除少数专家临床医生的编程负担，从而极大地扩大 DBS 对于不在专科中心附近的患者的可及性，从而使全国范围内的护理均等。 公共健康相关性：深部脑刺激 (DBS) 在治疗帕金森病等运动障碍方面的临床效用已得到充分证实；然而，由于不同的术后管理，尤其是从数千种可能的组合中选择一组最佳编程参数，DBS 接受者的结果存在很大差异。所提出的系统将使用基于运动传感器的评估来开发功能图和算法，以确定一组编程参数，以最大限度地提高症状效益，同时最大限度地减少副作用和电池消耗。

项目成果

Computer-Guided Deep Brain Stimulation Programming for Parkinson's Disease.

• DOI: 10.1111/ner.12372
• 发表时间: 2016-02
• 期刊: Neuromodulation : journal of the International Neuromodulation Society
• 作者: Heldman DA;Pulliam CL;Urrea Mendoza E;Gartner M;Giuffrida JP;Montgomery EB Jr;Espay AJ;Revilla FJ
• 通讯作者: Revilla FJ