Computational models of subcallosal cingulate deep brain stimulation

 描述(由申请人提供)：严重抑郁障碍(MDD)影响着至少10%的世界人口，在全球范围内排名第二，是导致因残疾而死亡的第二大原因。大约三分之一的抑郁症患者未能得到缓解；因此，对于 抑郁症患者数量显著，目前的治疗方法还不够。扣带下白质深部脑刺激(DBS)在治疗难治性抑郁症(TRD)方面取得了成功，但该疗法仍需要科学的发展才能被认为是临床治疗。总的研究目标是确定理论上最优的刺激参数，并在长期内前瞻性评估从头开始患者的临床结果。第一个目标是开发基于图像的SCCWM DBS电场计算模型。我们将使用磁共振(MR)图像来定义头部的几何和电学属性，并使用计算机断层扫描来确定DBS阵列的位置。六名患者将被建模：两名应答者，两名成为应答者的非应答者，以及两名非应答者。这一目标将产生有史以来最详细的DBS电场模型之一，它将代表定义精确DBS模型所需细节级别的“黄金标准”。第二个目的是评估SCCWM DBS的神经反应。我们假设靶白质束和非靶白质束将在小钳子、钩状束、扣带束和投射到皮质下结构的中线短纤维中发现。轴突将使用电缆理论建模，轴突的轨迹将通过在扩散加权MR图像上进行概率纤维束成像来定义，多变量统计分析将用于将纤维激活(或不激活)与对刺激的反应相关联。这一目标的结果将是识别潜在的靶向白质通路，这些通路对于在刺激时产生抗抑郁效应是必要的和/或充分的。第三个目标是确定优化理论上的刺激参数 SCCWM DBS的效率和选择性。所谓有效，指的是用最少的电能激活目标神经元，而选择性，指的是激活目标神经元而不是非靶元素的能力。可能的电极配置和刺激波形的空间太大，难以用蛮力处理，因此我们使用数值优化算法对六个模型患者的刺激参数进行优化。这一目标将为提高SCWM DBS的有效性建立一个衡量标准，我们将在未来的工作中对其进行测试。这项研究的成功完成将促进我们对某些皮质和/或皮质下纤维通路的激活如何在TRD患者中产生抗抑郁效果的理解。

 DESCRIPTION (provided by applicant): Major depressive disorder (MDD) affects at least 10 % of the world population and globally ranks as the second leading cause of years lost to disability. Approximately a third of depressed patients fail to achieve remission; therefore, for a marked number of depressed individuals, currents treatments are not adequate. Deep brain stimulation (DBS) of the subcallosal cingulate white matter (SCCWM) has had success in treating, treatment resistant depression (TRD), but this therapy still requires scientific evolutio before it can be considered a clinical therapy. The overall research objective is to determine the theoretically optimal stimulation parameters, and in the long-term, evaluate prospectively the clinical outcomes in de novo patients. The first aim is to develop image-based computational models of the electric field in SCCWM DBS. We will use magnetic resonance (MR) images to define the geometry and electrical properties of the head, and computed tomography scans to determine the location of the DBS array. Six patients will be modeled: two responders, two non-responders that became responders, and two non-responders. This aim will generate one of the most anatomical and electrically detailed DBS electric field models ever created, which will then represent a "gold standard" for defining the level of detail necessary for accurate models of DBS. The second aim is to evaluate the neural response to SCCWM DBS. We hypothesize that target and non- target white matter tracts will be found amongst forceps minor, the uncinate fasciculus, the cingulum bundle, and short midline fibers projecting to subcortical structures. Axons will be modeled using cable theory, the trajectory of the axons will be defined by conducting probabilistic tractrography on a diffusion-weighted MR image, and multivariate statistical analyses will be used to correlate fiber activation (or lack of activation) with a response to stimulation. The outcome of this aim will be the identification of potential target white matter pathways that are necessary and/or sufficient for eliciting an antidepressant effect when stimulated. The third aim is to identify stimulation parameters that optimize the theoretical efficiency and selectivity of SCCWM DBS. By efficient, we mean using the least amount of electrical energy to activate target neural elements, and by selective, we mean the ability to activate target neural elements over non-target elements. The space of possible electrode configurations and stimulus waveforms is too large to be tackled by brute- force, so we use a numerical optimization algorithm to optimize stimulation parameters in the six model patients. This aim will establish a metric for improving the efficacy of SCCWM DBS, which we will test in future work. Successful completion of this research will advance our understanding of how activation of certain cortical and/or subcortical fiber pathways can produce an antidepressant effect in patients with TRD.