CRCNS: Model-Based Characterization of spinal cord stimulation for pain

CRCNS：基于模型的脊髓刺激疼痛表征

• 批准号: 9916849
• 负责人: SCOTT F LEMPKA
• 金额: $ 35.81万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9916849
• 关键词: Adult; American; Analgesics; Anatomy; Brain; Clinical; Complex; Computer Simulation; Cross-Over Studies; Detection; Diabetes Mellitus; Double-Blind Method; Effectiveness; Electrodes; Elements; Engineering; Fiber; Future; Goals; Health; Heart Diseases; Implant; Instruction; Intervention; Knowledge; Link; Location; Malignant Neoplasms; Measurement; Measures; Medical Imaging; Modeling; Nature; Neurons; Neurostimulation procedures of spinal cord tissue; Opioid Analgesics; Outcome; Outcome Measure; Pain; Pain Measurement; Pain Threshold; Pain intensity; Pain management; Pain quality; Pathway interactions; Patients; Physiologic pulse; Physiological; Placebo Effect; Placebos; Population; Postoperative Period; Principal Investigator; Protocols documentation; Quality of life; Randomized; Refractory; Research; Sales; Sensory; Source; Spinal; Spinal Cord; Spine pain; Stimulus; Techniques; Technology; Testing; Therapeutic; Time; United States; Work; base; central pain; chronic pain; clinical implementation; conditioned pain modulation; conditioning; conventional therapy; cost; electric field; improved; individualized medicine; innovation; interpatient variability; opioid epidemic; overtreatment; pain inhibition; pain model; pain perception; pain processing; pain reduction; pain relief; pain sensitivity; pain signal; placebo controlled study; pressure; prevent; programs; relating to nervous system; response; somatosensory; success; vibration

Program Director/Principal Investigator (Last, First, Middle}: Lempka, Scott F PROJECT SUMMARY (See instructions}: Chronic pain is a major health problem in the United States and costs the nation upwards of $635 billion a year- more than cancer, heart disease and diabetes combined. Due to its debilitating nature and widespread impact, chronic pain is complex and challenging to treat. Unfortunately, conventional treatments have limited effectiveness for many people with severe chronic pain. Opioid analgesics are frequently prescribed despite the lack of evidence supporting their long-term use to treat chronic pain, and the associated opioid epidemic threatening the United States. Nonpharmacologic approaches, such as complementary and neurostimulation therapies, may offer better alternatives for chronic pain management. Spinal cord stimulation (SCS) is one type of neurostimulation therapy that can be considered for patients who are refractory to other treatment options. However, the outcomes of SCS and other neurostimulation therapies remain mixed. These variable outcomes can be contributed to a potential "placebo" effect and a poor understanding of their mechanisms of action. The goal of this project is to identify the anti-nociceptive effects of SCS by conducting a placebo-controlled study in patients undergoing SCS for chronic pain management. Spinal and supraspinal pain processing will be assessed with outcome measures related to several aspects of pain and quantitative sensory testing of pain sensitivity. These measurements will be combined with patient-specific computational models of SCS that will include: 1) electric-field models to estimate the direct neural response to SCS and 2) spinal cord circuit models to estimate the effects of SCS on pain processing. Therefore, this project will implement a systematic, well-controlled, patient-specific approach to investigate segmental spinal and central pain-processing mechanisms and the placebo effect associated with SCS. This approach is necessary to improve our understanding of chronic pain and how to treat it. II will apply cutting-edge computational modeling techniques to answer critical scientific questions within a clinical setting. The results of this project will improve scientific understanding of neurostimulation for chronic pain, help optimize and individualize current technologies, and innovate future therapies that improve clinical outcomes. RELEVANCE (See instructions): Neurostimulalion therapies, such as spinal cord stimulation, can provide nonpharmacologic treatment options to the millions of Americans suffering from pain. However, these neurostimulation therapies can fail to provide adequate pain relief in a large number of people. Therefore, this project will combine detailed computational models with measures of pain modulation in patients to investigate therapeutic mechanisms of neurostimulation and provide knowledge necessary to improve its effectiveness for pain management.

项目主任/主要研究者（最后，第一，中间）：Lempka，Scott F 项目总结（见说明）： 慢性疼痛是美国的一个主要健康问题，每年花费超过6350亿美元。 超过癌症、心脏病和糖尿病的总和。由于其衰弱的性质， 慢性疼痛是一种复杂且具有挑战性的治疗方法。不幸的是， 治疗对于许多患有严重慢性疼痛的人来说效果有限。阿片类镇痛药是 尽管缺乏证据支持其长期用于治疗慢性疼痛， 相关的阿片类药物流行威胁着美国。非药物方法，如 补充疗法和神经刺激疗法可能为慢性疼痛管理提供更好的替代方案。 脊髓刺激（SCS）是一种可以考虑用于患者的神经刺激治疗 对其他治疗方案无效的患者。然而，SCS和其他神经刺激的结果 治疗方法仍然是混合的。这些可变的结果可能会导致潜在的“安慰剂”效应， 对它们的作用机制缺乏了解。这个项目的目标是确定抗伤害性 通过在接受SCS治疗慢性疼痛的患者中进行安慰剂对照研究， 管理脊柱和棘上疼痛处理将通过与以下相关的结局指标进行评估： 疼痛的几个方面和疼痛敏感性的定量感觉测试。这些测量将是 结合SCS的患者特异性计算模型，包括：1）电场模型， 估计对SCS的直接神经反应和2）脊髓回路模型，以估计SCS的影响 关于疼痛处理因此，本项目将实施一个系统的、控制良好的、患者特异性的 一种研究节段性脊髓和中枢疼痛处理机制及安慰剂效应的方法 与SCS有关。这种方法对于提高我们对慢性疼痛的理解以及如何 II将应用尖端的计算建模技术来回答关键的科学问题 在临床环境中。该项目的结果将提高对神经刺激的科学理解 对于慢性疼痛，帮助优化和个性化当前的技术，并创新未来的治疗方法， 改善临床结果。 相关性（参见说明）： 神经刺激疗法，如脊髓刺激，可以提供非药物治疗， 数百万遭受痛苦的美国人的选择。然而，这些神经刺激疗法可能会失败， 以在大量的人中提供足够的疼痛缓解。因此，本项目将联合收割机详细 计算模型与患者的疼痛调制措施，以研究治疗机制 并提供必要的知识，以提高其疼痛管理的有效性。