Algorithms for programming deep brain stimulation systems

描述（由申请人提供）：特发性震颤（ET）是美国最常见的运动障碍，影响40岁以上所有成人的4%。对于那些 运动症状对药物治疗无效，并严重影响他们的日常生活，脑深部电刺激（DBS）被认为是唯一的治疗选择。尽管DBS技术取得了最新进展，但由于DBS电极导线放置不当，很大一部分植入DBS植入物的ET患者的震颤控制不足，而其他患者在1-2年后将失去治疗效果，部分原因是神经刺激器程控选项不灵活。对于植入式DBS导线设计存在强烈且不断增长的临床需求，该设计可以使临床医生能够更好地在大脑内塑造电场，特别是在刺激不稳定的情况下。 DBS电极导线放置不当会导致低阈值副作用。我们最近对径向分段DBS电极导线的研究显示了有希望的结果，但了解如何在此类电极导线上编程刺激设置仍然是使这些电极导线在临床环境中实用的关键挑战。我们提议的研究将整合高场磁共振成像、计算建模和电生理学，以开发一种经过实验验证的计算编程算法，该算法有助于通过高维DBS电极阵列临床确定受试者特定的神经刺激器设置。具体而言，我们将：1）开发可以简化具有径向分段电极阵列的丘脑深部脑刺激引线的编程过程的计算算法; 2）量化计算算法可以准确预测通过非人类灵长类动物中丘脑中的不良靶向DBS阵列的电流引导的程度;和3）比较在刺激非人灵长类动物的小脑丘脑与丘脑皮层通路期间在初级运动皮层（M1）中诱导的层特异性神经元动力学。

DESCRIPTION (provided by applicant): Essential tremor (ET) is the most common movement disorder in the United States, affecting 4% of all adults over the age of 40. For individuals whose motor symptoms are refractory to medication and significantly impair their daily living, deep brain stimulation (DBS) is considered to be the only therapeutic option. Despite recent advances in DBS technology, a significant portion of ET patients with DBS implants will receive inadequate tremor control because of poorly placed DBS leads, while others will lose efficacy of the therapy after 1-2 years due in part to inflexible neurostimulator programming options. There is a strong and growing clinical need for implantable DBS lead designs that can enable clinicians to better sculpt electric fields within the brain, especially in cases where stimulation through a poorly placed DBS lead results in low-threshold side-effects. Our recent studies with a radially-segmented DBS lead have shown promising results, but knowing how to program the stimulation settings on such a lead remains a critical challenge towards making these leads practical in a clinical setting. Our proposed study will integrate high-field magnetic resonance imaging, computational modeling, and electrophysiology to develop an experimentally-validated computational programming algorithm that facilitates clinical determination of subject-specific neurostimulator settings through high-dimensional DBS electrode arrays. Specifically, we will: 1) develop a computational algorithm that can simplify the programming process of thalamic deep brain stimulation leads with radially-segmented electrode arrays; 2) quantify the degree to which the computational algorithms can accurately predict current steering through poorly targeted DBS arrays in the thalamus in non-human primates; and 3) compare the layer-specific neuronal dynamics induced in primary motor cortex (M1) during stimulation of the cerebellothalamic versus thalamocortical pathway in non-human primates.