Electrophysiological Biomarkers to Optimize DBS for Depression

电生理生物标志物优化 DBS 治疗抑郁症

• 批准号: 10604638
• 负责人: Helen S Mayberg
• 金额: $ 12.37万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10604638
• 关键词: Address; Anatomy; Base of the Brain; Biological Markers; Brain; Caring; Characteristics; Clinical; Clinical Trials; Deep Brain Stimulation; Devices; Diffusion; Electroencephalography; Electrophysiology (science); Event-Related Potentials; Failure; Feasibility Studies; Frequencies; Future; Goals; Human; Implant; Individual; Lead; Long-Term Effects; Machine Learning; Measurement; Mediating; Mental Depression; Methods; Modeling; Monitor; Outcome; Patients; Phase; Policies; Positron-Emission Tomography; Procedures; Publishing; Randomized Controlled Trials; Signal Transduction; Site; System; Testing; Time; antidepressant effect; base; clinical implementation; connectome; data-driven model; evidence base; live stream; neural circuit; neuroregulation; novel; patient population; response; tractography; treatment strategy; treatment-resistant depression; white matter

PROJECT SUMMARY Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) white matter is an emerging new treatment strategy for treatment resistant depression (TRD) with published studies demonstrating sustained long-term antidepressant effects in 40-60% of implanted patients. Converging evidence from positron emission tomography (PET), electroencephalography (EEG) and diffusion tractography (DTI) strongly suggests that DBS mediates its clinical benefits by direct modulation of the SCC--a key hub in an aberrant neural circuit. Despite encouraging sustained long-term effects in this notoriously difficult to treat patient population, randomized controls trials of SCC DBS and other DBS targets for TRD are now on hold as initial results failed to meet predefined clinical endpoints. While this proposal cannot address those failures directly, a clear necessary next step for effective future testing and eventual dissemination of this treatment is the need to develop brain-based biomarkers to guide lead placement and to titrate stimulation parameters during ongoing care. In the absence of such biomarkers to guide DBS use, there will continue to be variability in the implementation of clinical procedures during testing, leading to ambiguous and possibly misleading trial outcomes, and subsequent abandonment of a potentially useful treatment. To overcome these limitations, we propose to develop and test objective methods for reliable device configuration in individuals by optimizing DBS-SCC treatment with respect to human functional anatomy and key electrophysiological variables. We will leverage the capabilities of a novel bi-directional neuromodulation system (Medtronic RC+S) that allows live streaming of oscillatory activity at the site of stimulation to define novel control strategies to guide programming decisions for DBS delivery. Ongoing measurements of SCC local field potentials (LFPs) will be combined with electroencephalography (EEG) and event related potential studies (ERP) performed as part of an experimental clinical trial of subcallosal cingulate DBS for TRD to identify an oscillatory signal that (1) is sensitive to changes in frequency and current parameters at the tractography defined optimal target and (2) tracks with depression state over time. Connectome-based and machine learning approaches will be used to define the most robust network biomarker and its response characteristics. Once defined, the control policy will be tested in a second phase feasibility study where parameters for initial stimulation will be selected based on the depression brain state biomarker and adjustments made to correct drift from the predefined target signal. If successful, the data- driven model and control strategy will enable objective, rational clinical programming of DBS stimulation for depression and provide a new model and approach for target identification, stimulation initiation and long-term monitoring and management of patients receiving this treatment. .

项目概要 胼胝体下扣带回 (SCC) 白质的深部脑刺激 (DBS) 是一种新兴的治疗方法 治疗难治性抑郁症 (TRD) 的策略已发表的研究表明持续长期 40-60% 的植入患者具有抗抑郁作用。来自正电子发射的汇聚证据 断层扫描 (PET)、脑电图 (EEG) 和扩散纤维束成像 (DTI) 强烈表明 DBS 通过直接调节 SCC（异常神经回路中的关键枢纽）来调节其临床益处。 尽管对这个众所周知难以治疗的患者群体产生了令人鼓舞的持续长期影响， SCC DBS 和 TRD 的其他 DBS 目标的随机对照试验因初步结果失败而被搁置 以满足预定的临床终点。虽然该提案不能直接解决这些失败问题，但明确 为了有效地进行未来测试并最终传播这种治疗方法，下一步必要的步骤是： 开发基于大脑的生物标志物来指导引线放置并在持续过程中滴定刺激参数 关心。在缺乏此类生物标志物来指导 DBS 使用的情况下，DBS 的使用将继续存在差异。 在测试过程中实施临床程序，导致试验不明确且可能具有误导性 结果，以及随后放弃可能有用的治疗。为了克服这些限制，我们 建议通过优化来开发和测试个人可靠设备配置的客观方法 DBS-SCC 治疗涉及人体功能解剖学和关键电生理变量。我们将 利用新型双向神经调节系统 (Medtronic RC+S) 的功能，该系统允许实时 刺激部位的振荡活动流，以定义新颖的控制策略来指导编程 星展银行交付的决定。 SCC 局部场电位 (LFP) 的持续测量将与 作为实验的一部分进行脑电图 (EEG) 和事件相关电位研究 (ERP) 用于 TRD 的胼胝体下扣带回 DBS 的临床试验，用于识别 (1) 对变化敏感的振荡信号 纤维束成像的频率和电流参数定义了最佳目标和 (2) 抑郁轨迹 随着时间的推移状态。基于连接组和机器学习的方法将用于定义最稳健的 网络生物标志物及其响应特征。一旦定义，控制策略将在第二秒内进行测试 阶段可行性研究，根据抑郁症大脑选择初始刺激参数 状态生物标志物以及为纠正与预定义目标信号的漂移而进行的调整。如果成功，数据- 驱动模型和控制策略将使 DBS 刺激的临床规划客观、合理 抑郁症并为目标识别、刺激启动和长期治疗提供新的模型和方法 监测和管理接受这种治疗的患者。 。