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

基本信息

批准号：
10704418
负责人：
Wayne K Goodman
金额：
$ 7.67万
依托单位：
BAYLOR COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
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/10704418
关键词：
Address Affect Algorithms Assessment tool Basic Science Beds Behavioral Blinded Boston Brain Brain region Classification Clinical Clinical Trials Deep Brain Stimulation Devices Disease Dose Electroencephalography Epilepsy Face Functional disorder Implant Lead Literature Mediating Mental Depression Modeling Monitor Outcome Patients Pattern Physiological Physiology Public Health Randomized Research Safety Source Spatial Distribution Symptoms System Technology Testing Validation Ventral Striatum Withdrawal capsule computerized depressive symptoms efficacy evaluation improved innovation insight nervous system disorder neural circuit neuropsychiatric disorder neuroregulation neurosurgery next generation novel novel strategies novel therapeutics open label response safety and feasibility therapeutic evaluation therapy development tractography treatment-resistant depression

项目摘要

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.

抽象的难治性抑郁症（TRD）的公共卫生负担促使深部脑的临床试验不幸的是，刺激（DBS）产生了不一致的结果。包括以下需求：(1) 更好地了解疾病的神经回路；(2) 精密 DBS 设备可以通过临床和生理验证的方式针对大脑网络；(3) 更深入地了解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 中的功效至关重要，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并使用下一代技术来治疗 TRD 患者具有引导能力的精准 DBS 可以参与这些目标网络并开发新疗法对于 TRD，我们使用 Boston Scientific (BS) Vercise DBS 系统，该系统提供分段可操纵引导。具有多个独立电流源，可实现真正的方向转向。我们将刺激场建模 (SFM) 与 MR 纤维束成像相结合来预测网络参与度。针对膝下扣带回 (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中枢。抑郁症网络和新兴的基础科学文献表明它们与抑郁症的双向调节有关我们还应用了颅内立体脑电图（sEEG）的范式转换方法。 DBS 植入后亚急性评估转向、SFM 和纤维束成像的临床可靠性，并在目标 1 中，癫痫监测中定义并针对介导抑郁症状的网络。 Unit (EMU)，我们研究 Vercise 选择性参与不同大脑网络的能力并进行比较诱发网络活动的空间分布和调制与 SFM 和纤维束描记术预测的结果。在目标 2 中，我们在 EMU 中进行了进一步的研究，以描绘与抑郁症相关的网络并显示我们使用各种任务来探究不同的症状。领域和新颖的评估工具（计算机化自适应测试和自动面部影响识别）来增强分类和模型算法以优化刺激模式。将目标 1 和 2 的结果结合在一起，以测试皮质边缘 DBS 在 12 中的治疗潜力 TRD 受试者，在为期 8 个月的开放标签试验中重点关注安全性、可行性和初步疗效随后随机、盲法撤回刺激以评估该提议的影响。包括对当前“引导”DBS 技术针对特定网络的生理验证、对刺激参数对网络生理学的影响，加深对病理生理学的理解抑郁症，也许最重要的是，治疗 TRD 的新方法这项研究也将成为先驱。与 BRAIN 优先事项一致的用于 DBS 疗法开发的新颖且高产量的测试床。