DEEP BRAIN STIMULATION FOR DEPRESSION USING DIRECTIONAL CURRENT STEERING AND INDIVIDUALIZED NETWORK TARGETING

使用定向电流引导和个性化网络目标进行深部脑刺激治疗抑郁症

• 批准号: 9564230
• 负责人: Wayne K Goodman
• 金额: $ 210.81万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9564230
• 关键词: Address; Affect; Algorithms; Amygdaloid structure; Anatomy; Assessment tool; Basic Science; Beds; Behavior; Behavioral; Bilateral; Biological Assay; Blinded; Boston; Brain; Brain region; Chronic; Classification; Clinical; Clinical Trials; Computer Simulation; Data; Data Set; Deep Brain Stimulation; Device or Instrument Development; Devices; Diffusion; Dimensions; Disease; Dose; Double-Blind Method; Ecological momentary assessment; Electrodes; Electroencephalography; Engineering; Epilepsy; Europe; Excision; Face; Functional disorder; Goals; Health Care Costs; Implant; Individual; Inpatients; Investigation; Lead; Literature; Mediating; Mental Depression; Modeling; Monitor; Negative Valence; Network-based; Neurocognitive; Outcome; Outpatients; Patients; Pattern; Physiological; Physiology; Placebo Effect; Positive Valence; Process; Public Health; Randomized; Research; Severities; Site; Source; Spatial Distribution; Stream; Symptoms; System; Technology; Testing; Validation; Ventral Striatum; Withdrawal; Work; base; capsule; cognitive control; computerized; depressive symptoms; design; disability; improved; innovation; insight; nervous system disorder; network models; neuropsychiatric disorder; neuroregulation; next generation; novel; novel strategies; novel therapeutics; open label; response; safety and feasibility; success; therapeutic evaluation; therapy development; tractography; treatment-resistant depression

ABSTRACT The public health burden of Treatment Resistant Depression (TRD) has prompted clinical trials of deep brain stimulation (DBS) that have, unfortunately, produced inconsistent outcomes. Potential gaps and opportunities include a need: (1) to better understand the neurocircuitry of the disease; (2) for precision DBS devices that can target brain networks in a clinically and physiologically validated manner; and (3) for greater insight into stimulation dose-response relationships. These needs are based on our overarching hypothesis that network- guided neuromodulation is critical for the efficacy of DBS in TRD. This project aims to address the unmet need of TRD patients by identifying brain networks critical for treating depression and to use next generation precision DBS with steering capability to engage these targeted networks and develop a new therapy for TRD. We use the Boston Scientific (BS) Vercise DBS system, which offers a segmented steerable lead with multiple independent current sources that allows true directional steering. Moreover, this system integrates stimulation field modeling (SFM) with MR tractography to predict network engagement. We use an innovative approach of targeting both subgenual cingulate (SGC) and ventral capsule/ventral striatum (VC/VS), which we term corticomesolimbic DBS. These targets are hubs in distinct yet partially overlapping depression networks and emerging basic science literature implicates them in bidirectional modulation of depression circuits. We also apply a paradigm-shifting approach using intracranial stereo-EEG (sEEG) subacutely after DBS implant to evaluate the clinical reliability of steering, SFMs, and tractography and to define and then target the networks mediating symptoms of depression. In Aim 1, in the Epilepsy Monitoring Unit (EMU), we investigate the capability of Vercise to selectively engage distinct brain networks and compare the spatial distribution of evoked network activity and modulation with that predicted by SFM and tractography. In Aim 2, we conduct further studies in the EMU to delineate depression-relevant networks and show behavioral changes with network-targeted stimulation. We use a variety of tasks to probe different symptom domains and novel assessment tools (Computerized Adaptive Testing and Automated Facial Affect Recognition) to enhance classification and model algorithms to optimize stimulation patterns. In Aim 3, we bring the results from Aims 1 and 2 together, to test the therapeutic potential of corticomesolimbic DBS in 12 subjects with TRD, with a focus on safety, feasibility, and preliminary efficacy in a 8-month open label trial with a subsequent randomized, blinded withdrawal of stimulation to assess efficacy. The impact of this proposal includes physiological validation of current “steering” DBS technology to target specific networks, insights into effects of stimulation parameters on network physiology, an improved understanding of the pathophysiology of depression, and, perhaps most importantly, a novel approach for treating TRD. This research will also pioneer a novel and high-yield test bed for DBS therapy development consistent with BRAIN priorities.

抽象的 抗治疗抑郁症（TRD）的公共卫生燃烧促使大脑的临床试验 不幸的是，刺激（DB）产生了不一致的结果。潜在的差距和机会 包括：（1）更好地了解该疾病的神经记录； （2）对于精确的DBS设备 可以以临床和物理验证的方式针对大脑网络； （3）更深入地了解 刺激剂量反应关系。这些需求基于我们的总体假设，即网络 - 引导神经调节对于DBS在TRD中的效率至关重要。该项目旨在满足未满足的需求 通过确定对治疗抑郁和使用下一代至关重要的大脑网络来确定大脑网络的 精密DB具有转向能力，可参与这些有针对性的网络并开发新的疗法 对于trd。我们使用波士顿科学（BS）Vercise DBS系统，该系统提供了分段的可协调线索 具有多个独立的电流来源，可实现真正的方向转向。而且，这个系统 将刺激现场建模（SFM）与MR拖拉术相结合，以预测网络参与。我们使用一个 靶向亚基扣带（SGC）和腹囊/腹侧纹状体的创新方法 （vc/vs），我们称其为皮质溶胶DBS。这些目标是枢纽，但部分重叠了 抑郁网络和新兴的基础科学文献实现了它们的双向调制 抑郁电路。我们还使用颅内立体声EEG（SEEG）采用范式移动方法 DBS植入物后，次要评估转向，SFM和拖拉术的临床可靠性以及 定义并针对介导抑郁症状的网络。在AIM 1中，在癫痫监测中 单位（EMU），我们调查了Vercise选择性参与不同大脑网络的能力并进行比较 SFM和Tractography预测的诱发网络活动和调制的空间分布。 在AIM 2中，我们在EMU中进行进一步的研究，以描绘与抑郁症相关的网络并显示 行为随着网络为目标的刺激而变化。我们使用各种任务来探测不同的症状 域和新颖的评估工具（计算机化自适应测试和自动化面部影响 识别）以增强分类和建模算法以优化刺激模式。在AIM 3中，我们 将目标1和2的结果融合在一起，以测试12个在12中的皮质溶质DBS的治疗潜力 具有TRD的受试者，重点是安全，可行性和初步效率，在8个月的开放标签试验中 随后的随机盲目戒断刺激以评估效率。该提议的影响 包括对当前“转向” DB技术的物理验证，以针对特定网络，洞察力 刺激参数对网络生理学的影响，对病理生理的理解得到了改善 抑郁症，也许最重要的是一种治疗TRD的新方法。这项研究也将开拓 DBS治疗开发的新型和高收益测试床与大脑优先级一致。