Electrophysiological Biomarkers to Optimize DBS for Depression

项目总结 摘要扣带回白质深部电刺激是一种新兴的治疗方法。 治疗难治性抑郁症(TRD)的策略与已发表的研究表明持续的长期 40%-60%的植入患者有抗抑郁作用。来自正电子发射的聚合证据 体层摄影术(PET)、脑电图术(EEG)和扩散束成像(DTI)强烈提示 DBS通过直接调节SCC来调节其临床益处--SCC是异常神经回路的关键枢纽。 尽管在这个出了名的难以治疗的患者群体中鼓励持续的长期效果， 由于初步结果失败，SCC、DBS和其他DBS靶向TRD的随机对照试验现已暂停 以满足预定义的临床终点。虽然这项提案不能直接解决这些问题，但一个明确的 未来有效测试和最终推广这种治疗方法的必要下一步是需要 开发基于大脑的生物标志物，以指导导线放置并在进行中滴定刺激参数 关心。在缺乏这种生物标志物来指导DBS使用的情况下， 在测试期间执行临床程序，导致不明确的和可能误导的试验 结果，以及随后放弃潜在有用的治疗。为了克服这些限制，我们 建议开发和测试客观方法，通过优化实现个人可靠的设备配置 DBS-SCC治疗与人体功能解剖和关键电生理变量有关。我们会 利用新型双向神经调节系统(美敦力RC+S)的功能，允许现场 在刺激部位流动振荡活动，以定义指导编程的新控制策略 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(EEG)和事件相关电位(ERP)研究 扣带回双侧扣带回治疗TRD的临床研究 在显影的频率和电流参数中定义了最佳目标和(2)带有凹陷的轨道 随着时间的推移，状态。将使用基于Connectome和机器学习的方法来定义最健壮的 网络生物标记物及其响应特征。一旦定义，控制策略将在一秒钟内进行测试 阶段可行性研究，将根据抑郁的大脑选择初始刺激的参数 状态生物标记物和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- 驱动的模型和控制策略将使DBS刺激的临床规划客观、合理 为靶点识别、刺激启动和长效治疗提供了新的模型和方法 对接受这种治疗的患者进行监测和管理。 。

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. .