CRCNS: Hitting the spot: Optimizing Placement of Deep Brain Stimulation Electrode

CRCNS：切中要害：优化深部脑刺激电极的放置

• 批准号: 8550145
• 负责人: Ming L Cheng
• 金额: $ 31.41万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8550145
• 关键词: Action Potentials; Algorithms; Anatomy; Architecture; Area; Automation; Behavior; Behavioral; Benchmarking; Biological Factors; Biological Models; Biological Neural Networks; Biophysical Process; Brain; Caring; Chronic Disease; Climacteric; Clinical; Code; Collaborations; Communities; Complex; Computer software; Contralateral; Cues; Data; Data Analyses; Data Collection; Data Correlations; Databases; Deep Brain Stimulation; Dependence; Development; Devices; Dorsal; Educational Curriculum; Electrodes; Engineering; Experimental Designs; Family; Family member; Feedback; Frequencies; Functional disorder; Future; Hand; Home environment; Hostage; Human; Implanted Electrodes; Individual; Industry; Joystick; Lateral; Lead; Learning; Linear Models; Location; Manufacturer Name; Measures; Medical Students; Methods; Microelectrodes; Modeling; Motor; Movement; Neuroanatomy; Neurologic; Neurons; Neurosurgeon; Noise; Operative Surgical Procedures; Outcome; Parkinson Disease; Pathology; Patients; Pattern; Pharmaceutical Preparations; Physicians; Physiological; Physiology; Population; Positioning Attribute; Postoperative Period; Principal Investigator; Probability; Procedures; Process; Property; Recording of previous events; Research; Research Personnel; Sampling; Scientist; Shapes; Signal Transduction; Site; Spottings; Statistical Methods; Statistical Models; Structure; Structure of subthalamic nucleus; System; Techniques; Technology; Testing; Thalamic Nuclei; Therapeutic; Training; Treatment Efficacy; Tungsten; Universities; Variant; analog; arm; base; clinical efficacy; computerized data processing; cost; design; digital; extracellular; graduate student; implantation; improved; insight; neural model; neurophysiology; neurosurgery; next generation; programs; relating to nervous system; theories; tool; voltage

DESCRIPTION (provided by applicant): Intellectual Merit: Deep brain stimulation (DBS) is a highly promising therapy for Parkinson's disease (PD). Yet most patients do not get full therapeutic benefit from DBS due to its critical dependence on electrode location, a "sweet spot" in the dorsolateral posterior sensorimotor subunit of the sub-thalamic nucleus (STN), for therapeutic efficacy. PI Cheng was trained at a center where 70% of DBS patients obtained full therapeutic benefit, improving so markedly that they no longer require any PD medications. Such efficacy is atypical even in academic centers because DBS electrode placement is not standardized, scientific, or systematic. We propose to construct a neural modeling, estimation and control framework for STN, which will enable the development of a new surgical tool that will standardize DBS placement: an automated intraoperative closed-loop DBS localization system. Development of this transformative technology requires: 1) neurophysiologic characterization of the "sweet spot". In PD patients, microelectrode recordings will measure single unit spiking activity (action potentials) of STN neurons at different distances from the "sweet spot" and from within it. Point process models will be estimated from this data and will capture complex stochastic relationships between extrinsic (e.g. behavior) and intrinsic (local neural network activity) factors and STN spiking activity. Principled inferential methods will confirm the "sweet spot's" existence and characterize its electrophysiological properties; and computational conductance-based modeling will elucidate the ionic mechanisms underlying the "sweet spot's" physiology. 2) construction of neural estimation and control algorithms for STN DBS. Signal processing and control will derive a robust feature set from STN spiking activity which will reliably predict where the electrode is and will then guide the electrode to the sweet spot. This transformative project requires collaborations between physicians, scientists, mathematicians and engineers with expertise in neurosurgery, neurophysiology, neural signal processing, estimation and modeling, and control theory. For these reasons automation of DBS localization remains largely untapped, giving us the opportunity to lead the scientific development of this next-generation technology. Broader Impact: Due to cost, less than 10% of PD patients worldwide receive DBS. Automating surgical implantation and obviating complex postoperative DBS programming from suboptimal electrode placement would decrease cost, and thus increase patient access. Even greater societal impact, however, would come from improved DBS efficacy, which is life-changing for PD patients. DBS patients of Dr. Cheng have stated that they have been returned to their pre-PD status, and that not just their lives but also the lives of their family members, so long held hostage by a debilitating chronic disease process, have been returned to them. Our proposal attempts to extrapolate these benefits to the larger PD population. Even more importantly, DBS is a nascent procedure holding great promise for many future neurological and psychiatric indications. A technology that improves DBS targeting fidelity and efficacy would hold the potential to improve the lives of millions of patients and their families worldwide. This project will be integrated into curricula in the home and affiliated departments of the PIs. Coursework for signal processing and neuronal spike modeling in the senior undergraduate and graduate levels will gain from our proposal. A graduate level modern control theory course with applications to neural systems will also be developed and offered. Traditional courses in neuroanatomy and neurophysiology will be enhanced by our proposal's insights into the relationships between physiology, anatomy, and function. The PIs also plan to reach out to the academic community by providing representative samples of rare neurophysiological data and analysis code. When cultivated, such a database will provide a platform for investigators around the world to benchmark software algorithms, optimize analog and digital components for new hardware platforms that will process neural signals, and develop a more complete understanding of the mechanisms of DBS. PI Cheng has strong relationships with industry companies including Medtronic, the manufacturer of DBS hardware. We will leverage this to expedite the development and testing of our concept. Our project's outcome may thus have a substantial impact on how DBS systems are designed.

描述（申请人提供）：智力优势：脑深部电刺激（DBS）是一种非常有前途的治疗帕金森病（PD）的方法。然而，大多数患者并没有从DBS中获得充分的治疗效果，因为它严重依赖于电极位置，而电极位置是丘脑下核（STN）背外侧后感觉运动亚基的“最佳位置”。PI Cheng在一个中心接受培训，70%的DBS患者获得了完全的治疗效果，改善非常明显，他们不再需要任何PD药物。即使在学术中心，这种疗效也不是典型的，因为DBS电极的放置不是标准化的、科学的或系统的。我们建议构建STN的神经建模、估计和控制框架，这将有助于开发一种新的手术工具来标准化DBS放置：术中自动化闭环DBS定位系统。这种变革性技术的发展需要：1)“最佳点”的神经生理学特征。在PD患者中，微电极记录将测量STN神经元在距离“最佳点”不同距离处的单个峰值活动（动作电位）。点过程模型将根据这些数据进行估计，并将捕获外在（例如行为）和内在（局部神经网络活动）因素与STN尖峰活动之间复杂的随机关系。原理推理方法将证实“甜点”的存在并表征其电生理特性；基于计算电导的建模将阐明“最佳点”生理学背后的离子机制。2) STN DBS神经网络估计与控制算法的构建。信号处理和控制将从STN尖峰活动中获得一个鲁棒特征集，该特征集将可靠地预测电极的位置，然后将电极引导到最佳点。这个变革性的项目需要医生、科学家、数学家和工程师在神经外科、神经生理学、神经信号处理、估计和建模以及控制理论方面的专业知识进行合作。由于这些原因，DBS定位的自动化在很大程度上仍未得到开发，这使我们有机会领导下一代技术的科学发展。更广泛的影响：由于成本原因，全球只有不到10%的PD患者接受了DBS。自动化手术植入和避免复杂的术后DBS编程从次优电极放置将降低成本，从而增加患者的访问。然而，更大的社会影响将来自DBS疗效的提高，这将改变PD患者的生活。郑医生的DBS患者表示他们已经恢复到pd前的状态，不仅是他们的生活，还有他们的家庭成员的生活，他们长期以来一直被慢性疾病所束缚，现在都恢复了。我们的建议试图将这些益处推断到更大的PD人群中。更重要的是，DBS是一种新兴的治疗方法，对许多未来的神经和精神适应症有很大的希望。一项以提高DBS的保真度和疗效为目标的技术，将有可能改善全球数百万患者及其家属的生活。该项目将被纳入pi的家庭和附属部门的课程。信号处理和神经元尖峰建模的课程将从我们的建议中获益。此外，亦会开设研究生水平的现代控制理论课程，并将其应用于神经系统。传统的神经解剖学和神经生理学课程将通过我们对生理学，解剖学和功能之间关系的见解而得到加强。pi还计划通过提供罕见的神经生理学数据和分析代码的代表性样本来接触学术界。一旦建立起来，这样一个数据库将为世界各地的研究人员提供一个平台，以对软件算法进行基准测试，为处理神经信号的新硬件平台优化模拟和数字组件，并对DBS的机制有更全面的了解。PI Cheng与包括DBS硬件制造商美敦力在内的行业公司建立了牢固的关系。我们将利用这一点来加快我们概念的开发和测试。因此，我们项目的结果可能会对如何设计DBS系统产生实质性的影响。