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，并伴有 失去活动范围，虚弱，有时还有自主神经症状。影响了85%以上的一般 在他们的生活中的某个时候，肌筋膜疼痛一直是医疗保健访问，缺勤， 和残疾养恤金-这是一个重大的健康问题和经济负担。但尽管 肌筋膜疼痛的高发病率和巨大的经济成本，潜在的病理生理学仍然主要是 未知因此，肌筋膜疼痛的临床诊断和治疗主要是经验性的。客观和 不存在通过成像、肌电图、实验室检查或肌肉活检获得的定量生物标志物 用于评估肌筋膜疼痛。为了应对这一挑战，我们建议制定和 转换多模态、多参数、多尺度成像方法，以全面评估不同的 触发点局部和区域性肌筋膜疼痛的病理生理学方面 整个肌筋膜组织，基于此，我们将鉴定最敏感的候选生物标志物， 特异性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 反应和预测临床结果的随机临床试验。具体而言，在R61阶段（技术 开发和观察研究），我们将开发无创磁共振和电生理 成像生物标志物和微创光纤成像生物标志物平行（目的1），然后识别 候选生物标志物最能区分不同状态（健康、潜伏和活跃）相关 在一项观察性临床研究中（目的2），我们先前的研究和初步研究提供了 为拟议的生物标志物开发和临床试验提供了坚实的前提。在R33阶段（干预性 研究），我们的研究团队，包括成像，肌筋膜疼痛，定量分析和临床 试验-将检查在R61阶段确定的成像生物标志物监测反应的能力 到局部化学注射治疗并在随机临床试验中预测临床结果。拟议 研究将创造有关肌筋膜疼痛的重要知识，并有助于建立定量成像 这些生物标志物可以指导我们选择适当的疼痛管理并减少阿片类药物成瘾。