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: 10883136
• 负责人: Wayne K Goodman
• 金额: $ 15.4万
• 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 2026-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10883136
• 关键词: Address; Affect; Algorithms; Amygdaloid structure; Assessment tool; Basic Science; Beds; Behavior; Behavioral; Bilateral; Biological Assay; Blinded; Boston; Brain; Brain region; Chronic; Classification; Clinical; Clinical Trials; Computer Models; 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; Regional Anatomy; Research; Safety; Severities; Site; Source; Spatial Distribution; Stream; Symptoms; System; Technology; Testing; Validation; Ventral Striatum; Withdrawal; Work; capsule; cognitive control; computerized; depressive symptoms; disability; efficacy evaluation; improved; innovation; insight; nervous system disorder; network models; neural circuit; neuropsychiatric disorder; neuroregulation; neurosurgery; next generation; novel; novel strategies; novel therapeutics; open label; rational design; 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.

摘要 难治性抑郁症（TRD）的公共卫生负担促使了脑深部的临床试验。 刺激（DBS），不幸的是，产生了不一致的结果。潜在的差距和机会 包括需要：（1）更好地了解疾病的神经回路;（2）精确的DBS设备， 可以以临床和生理学验证的方式瞄准大脑网络;以及（3）为了更深入地了解 刺激剂量-反应关系。这些需求是基于我们的总体假设，即网络- 引导神经调节对于DBS治疗TRD的疗效至关重要。该项目旨在解决未满足的需求 通过识别对治疗抑郁症至关重要的大脑网络， 具有转向能力的精密DBS，以参与这些目标网络并开发新的治疗方法 对于TRD。我们使用Boston Scientific（BS）Vercise DBS系统，该系统提供分段可控电极导线 具有多个独立的电流源，可实现真正的方向控制。此外，该系统 将刺激场建模（SFM）与MR纤维束成像集成以预测网络参与。我们利用一个 同时靶向膝下扣带回（SGC）和腹侧囊/腹侧纹状体的创新方法 (VC/VS），我们称之为皮质边缘DBS。这些目标是不同但部分重叠的枢纽 抑郁症网络和新兴的基础科学文献暗示它们在双向调节 抑郁回路我们还应用了一种范式转换的方法，使用颅内立体脑电图（sEEG） DBS植入后的亚急性期，以评价转向、SFM和纤维束成像的临床可靠性， 定义并瞄准介导抑郁症状的网络。在目标1中，癫痫监测 单位（EMU），我们调查的能力Vercise选择性地从事不同的大脑网络和比较 诱发网络活动和调制的空间分布与SFM和纤维束成像预测的空间分布一致。 在目标2中，我们在EMU中进行了进一步的研究，以描绘抑郁相关网络，并显示 网络定向刺激的行为变化。我们使用各种任务来探测不同的症状 领域和新的评估工具（计算机化自适应测试和自动面部表情 识别），以增强分类和模型算法，以优化刺激模式。在目标3中，我们 将目标1和目标2的结果结合起来，以测试12例皮质边缘DBS的治疗潜力。 TRD受试者，重点关注8个月开放标签试验的安全性、可行性和初步疗效， 随后随机、设盲撤回刺激以评估疗效。这项提议的影响 包括生理验证当前的“转向”DBS技术，以针对特定的网络，洞察到 刺激参数对网络生理学的影响， 抑郁症，也许最重要的是，治疗TRD的新方法。这项研究也将开创 一个新颖的和高产量的测试床DBS治疗的发展与大脑的优先事项一致。