Computational models of subcallosal cingulate deep brain stimulation

 描述（由申请人提供）：重度抑郁症（MDD）影响至少10%的世界人口，并在全球范围内列为残疾年损失的第二大原因。大约三分之一的抑郁症患者未能达到缓解;因此， 抑郁症患者人数众多，目前的治疗是不够的。胼胝体下扣带白色物质（SCCWM）的脑深部电刺激（DBS）在治疗难治性抑郁症（TRD）方面取得了成功，但这种疗法在被认为是临床疗法之前仍然需要科学的发展。总体研究目标是确定理论上的最佳刺激参数，并在长期内前瞻性评价初治患者的临床结局。 第一个目标是开发基于图像的计算模型的电场SCCWM DBS。我们将使用磁共振（MR）图像来定义头部的几何形状和电气特性，并使用计算机断层扫描来确定DBS阵列的位置。将对6例患者进行建模：2例应答者、2例变为应答者的无应答者和2例无应答者。这一目标将生成有史以来最解剖和电气详细的DBS电场模型之一，然后将代表用于定义DBS精确模型所需的详细程度的“黄金标准”。 第二个目的是评估SCCWM DBS的神经反应。我们假设靶和非靶白色物质束将在小钳、钩束、扣带束和投射到皮质下结构的短中线纤维中发现。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，并且多变量统计分析将用于将纤维激活（或缺乏激活）与对刺激的响应相关联。这一目标的结果将是识别潜在的目标白色物质途径，这些途径是刺激时引发抗抑郁作用所必需和/或足够的。 第三个目的是确定优化理论的刺激参数， SCCWM DBS的效率和选择性。高效是指使用最少的电能来激活目标神经元，选择性是指激活目标神经元而不是非目标神经元的能力。可能的电极配置和刺激波形的空间太大而无法通过蛮力处理，因此我们使用数值优化算法来优化六个模型患者中的刺激参数。这一目标将建立一个衡量标准，以提高SCCWM DBS的疗效，我们将在未来的工作中进行测试。 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患者中产生抗抑郁作用的理解。

 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.