Development and identification of magnetic resonance, electrophysiological, and fiber-optic imaging biomarkers of myofascial pain

肌筋膜疼痛的磁共振、电生理学和光纤成像生物标志物的开发和鉴定

• 批准号: 10580406
• 负责人: Song Hu
• 金额: $ 228.45万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10580406
• 关键词: Absenteeism; Address; Affect; Aftercare; Articular Range of Motion; Biological; Biological Markers; Biomechanics; Biopsy; Blood capillaries; Bupivacaine; Chemicals; Clinic; Clinical; Clinical Management; Clinical Research; Clinical Trials; Confounding Factors (Epidemiology); Development; Diffusion; Economic Burden; Edema; Electromyography; Electrophysiology (science); Enrollment; Fascia; Fiber; Fiber Optics; Fibrosis; Financial Hardship; Financial cost; Functional disorder; Funding; General Population; Generations; Hair; Health; Health Care Visit; Human; Image; Imaging Techniques; Incidence; Infiltration; Inflammation; Injection of therapeutic agent; Injections; Injury; Intervention Studies; Ischemia; Knowledge; Laboratories; Logistic Regressions; Magnetic Resonance; Magnetic Resonance Elastography; Magnetic Resonance Imaging; Masks; Measurement; Measures; Modeling; Monitor; Muscle; Muscle Fibers; Myofascial Pain Syndromes; Neck; Neck Pain; Needles; Observational Study; Opiate Addiction; Optics; Outcome; Pain; Pain management; Participant; Patient Recruitments; Patient imaging; Patients; Pensions; Peripheral; Phase; Randomized; Randomized Clinical Trials; Relaxation; Research; Resolution; Saline; Sarcomeres; Shoulder; Shoulder Pain; Smooth Muscle; Surface; Symptoms; System; Testing; Thinness; Time; Tissues; Translating; Uterus; axon injury; base; biomarker development; candidate marker; cerebral oxygenation; clinical diagnosis; imaging approach; imaging biomarker; improved; mechanical properties; metabolic imaging; minimally invasive; multimodality; muscle stiffness; non-opioid analgesic; novel marker; optical imaging; pain patient; pain scale; predict clinical outcome; predictive modeling; prevent; quantitative imaging; randomized trial; research clinical testing; response; second harmonic; spectrograph; technology development; tool; treatment response; trigger point

PROJECT SUMMARY Myofascial pain is a type of pain that originates in the muscle and surrounding fascia and is accompanied by a loss of range of motion, weakness, and sometimes autonomic symptoms. Affecting more than 85% of the general population sometime in their lives, myofascial pain has been a leading cause of health-care visits, absenteeism, and invalidity pensions—representing a significant health concern and economic burden. However, despite the high incidence of myofascial pain and substantial financial cost, the underlying pathophysiology remains largely unknown. As a result, clinical diagnosis and management of myofascial pain are largely empirical. Objective and quantitative biomarkers acquired by imaging, electromyography, laboratory tests, or muscle biopsy do not exist in the clinic for the assessment of myofascial pain. To address this unmet challenge, we propose to develop and translate a multi-modal, multi-parametric, multi-scale imaging approach to comprehensively assess the different aspects of the pathophysiology underlying myofascial pain both locally at the trigger point and regionally across the entire myofascial tissue, based on which we will identify candidate biomarker(s) that are most sensitive and specific to distinguish different states of myofascial pain and then test the biomarker’s ability to monitor treatment responses and predict clinical outcomes in a randomized clinical trial. Specifically, in the R61 phase (technology development & observational study), we will develop noninvasive magnetic resonance and electrophysiological imaging biomarkers and minimally invasive fiber-optic imaging biomarkers in parallel (Aim 1), and then identify candidate biomarkers that are best capable of differentiating different states (healthy, latent, and active) related to myofascial pain in an observational clinical study (Aim 2). Our prior research and preliminary studies provide strong premises for the proposed biomarker development and clinical testing. In the R33 Phase (interventional study), our research team—consisting of expertise in imaging, myofascial pain, quantitative analysis, and clinical trial—will examine the ability of the imaging biomarker(s) identified in the R61 phase for monitoring the responses to local chemical injection treatment and predicting clinical outcomes in a randomized clinical trial. The proposed research will create vital knowledge about myofascial pain and contribute to the creation of quantitative imaging biomarkers that may guide our choices of appropriate pain management and reduce opioid addiction.

项目摘要 肌筋膜疼痛是一种起源于肌肉和周围筋膜的疼痛，伴随着 运动范围丧失，无力，有时甚至是自主症状。影响一般的85％以上 人口在他们一生中的某个时候，肌筋膜疼痛一直是医疗探访，旷工， 和无效的养老金 - 代表了重大的健康问题和经济负担。但是，要求 肌筋膜疼痛和大量经济成本的高度事件，基本的病理生理学仍然很大程度上仍然是 未知。结果，肌筋膜疼痛的临床诊断和治疗在很大程度上是经验的。目标和 不存在由成像，肌电图，实验室测试或肌肉活检获得的定量生物标志物 在评估肌筋膜疼痛的诊所中。为了应对这一未满足的挑战，我们建议开发和 翻译一种多模式，多参数，多尺度成像方法，以全面评估不同 在触发点和区域跨区域的肌筋膜疼痛的病理生理学方面 整个肌筋膜组织，我们将确定最敏感和最敏感的候选生物标志物 特定于区分肌筋膜疼痛的不同状态，然后测试生物标志物监测治疗的能力 反应并预测一项随机临床试验中的临床结果。具体而言，在R61阶段（技术 开发与观察性研究），我们将开发无创磁共振和电生理学 并行成像生物标志物和微创光纤成像生物标志物（AIM 1），然后识别 候选生物标志物最能区分不同状态（健康，潜在和活跃）相关的候选生物标志物 在一项检查临床研究中肌筋膜疼痛（AIM 2）。我们先前的研究和初步研究提供 拟议的生物标志物开发和临床测试的强大前提。在R33阶段（介入） 研究），我们的研究团队 - 对成像，肌筋膜疼痛，定量分析和临床方面的专业知识的保留 试验 - 将检查在R61阶段鉴定的成像生物标志物的能力 在一项随机临床试验中进行局部化学注射治疗并预测临床结果。提议 研究将创造有关肌筋膜疼痛的重要知识，并有助于创建定量成像 可以指导我们选择适当疼痛管理并减少阿片类药物成瘾的生物标志物。