肌筋膜疼痛的超声成像
用于肌筋膜疼痛的无创多模态超声成像生物标志物的开发和验证
The goal of this observational study is to develop and validate a biomarker for lumbar myofascial pain (MP) based on ultrasound obtained measurements of the lumbar muscles and fascia. The investigators will use advanced machine learning approaches and validation in a randomized controlled trial. The main questions it aims to answer are:
- Will the deep learning-based marker reliably identify subjects from the 4 different groups: healthy, MP without trigger points, MP with latent trigger points, and MP with active trigger points?
- Will the deep learning-based marker accurately classify/predict the severity of MP in subjects with cLBP?
Participants in the healthy group will be asked to do the following tasks:
- Consent/Enrollment
- Measure Height/Weight
- Complete Questionnaires on REDCap
- Participate in Ultrasound Imaging Experiment Sessions
Participants in the chronic low back pain group will be asked to do the following tasks:
- Consent/Enrollment
- Complete Questionnaires on REDCap
- Measure Height/Weight
- Undergo a Standardized Clinical Exam
- Participate in Ultrasound Imaging Experiment Sessions
研究概览
详细说明
The investigators propose to use multimodal ultrasound imaging to develop and validate a practical and inexpensive biomarker for lumbar myofascial pain, which shows sensitivity to change in relation to treatment. Myofascial pain (MP) is a frequent contributing factor to chronic low back pain (cLBP). It is associated with a range of tissue abnormalities, such as taught muscle bands, trigger points (TPs), and thoracolumbar fascia motion dysfunction, along with poor tissue elasticity. As a result, a composite biomarker for MP related to components of the syndrome is more likely to be plausible biologically, robust, and useful clinically for diagnosis and treatment. The investigators propose to study: 1. The echogenicity of latent and active trigger points, 2. The dynamic spatial-temporal tissue deformation quantified by strain tensors (compression, extension, and shear) in the thoracolumbar fascia and multifidus muscle, 3. The viscoelastic properties of the fascia and muscles measured by ultrasound shear wave elastography. In the R61 Phase (year 1 to 3) the investigators will use deep learning to integrate these measurements into a predictive biomarker and use established validation methods to test its ability to predict MP.
The investigators will determine the sensitivity and specificity of the biomarker to classify the myofascial components of pain, as well as the response to treatment (a diagnostic and predictive marker).
研究类型
注册 (实际的)
联系人和位置
学习地点
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Pennsylvania
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Pittsburgh、Pennsylvania、美国、15213
- Kauffman Medical Building
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参与标准
资格标准
适合学习的年龄
接受健康志愿者
有资格学习的性别
取样方法
研究人群
The investigators are including healthy normal and cLBP subjects from ages 20 to 70.
描述
Inclusion/Exclusion Criteria for Healthy Normals (n=40):
- No history of chronic low back pain, myofascial pain of the neck or shoulders, or fibromyalgia.
- Ages 20-70 to be age appropriate to the cLBP subjects. The investigators will recruit 10 subjects per age decile (10 subjects ages 30-39 yrs., etc.).
- Any clinically unstable systemic illness that is judged to interfere
- with the trial
- Non-ambulatory status
- Not able to complete the questionnaires.
Inclusion Criteria CLBP:
- Age range 20-70 so that the age distribution is likely to roughly match the healthy normals
- Predominantly axial cLBP meeting the NIH definition of cLBP (at least 3 months on a daily basis) with a MP component (determined by a standardized clinical exam)
- Average pain score of > 3/10, with low back pain being the primary pain site
- cLBP meeting Quebec Task Force Classification System categories I-III (from axial pain only to pain radiating beyond the knee without neurological signs).
Exclusion Criteria CLBP:
- Back surgery within the past year
- Active worker's compensation or litigation claims since these patients are more likely to have exaggerated pain behavior
- New pain treatments within 2 weeks of enrollment
- Any clinically unstable systemic illness that is judged to interfere with the trial
- Non-ambulatory status
- Not able to complete the questionnaires.
学习计划
研究是如何设计的？
设计细节
- 观测模型：COHORT
- 时间观点：PROSPECTIVE
队列和干预
团体/队列 |
干预/治疗 |
|---|---|
|
Healthy Normals
Participants with no chronic pain over a three-year timeframe. |
See above, this is only a phenotyping study but NIH required us to register it as a trial. |
|
MP without TPs
Participants with chronic low back pain who are classified as having myofascial pain and no trigger points. |
See above, this is only a phenotyping study but NIH required us to register it as a trial. |
|
MP with latent TPs
Participants with chronic low back pain who are classified as having myofascial pain and latent trigger points. |
See above, this is only a phenotyping study but NIH required us to register it as a trial. |
|
MP with active TPs
Participants with chronic low back pain who are classified as having myofascial pain and active trigger points. |
See above, this is only a phenotyping study but NIH required us to register it as a trial. |
研究衡量的是什么？
主要结果指标
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
|
Diagnosis of one of 3 MP-related categories
大体时间：Study Visit 1 (week 1)
|
Participants to be diagnosed as normal, MP with trigger points, or MP with tender points only, as determined by standardized clinical examinations. |
Study Visit 1 (week 1)
|
次要结果测量
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
|
Presence of Substantial MP
大体时间：Study Visit 1 (week 1) - Study Visit 2 (week 2)
|
The presence of substantial MP (e.g., # active TPs and pressure pain threshold below 6.5 N/cm2) as determined by the standardized clinical examinations. |
Study Visit 1 (week 1) - Study Visit 2 (week 2)
|
合作者和调查者
合作者
调查人员
- 首席研究员：Kang Kim, PhD、University of Pittsburgh
研究记录日期
研究主要日期
学习开始 (实际的)
初级完成 (实际的)
研究完成 (实际的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
此信息直接从 clinicaltrials.gov 网站检索，没有任何更改。如果您有任何更改、删除或更新研究详细信息的请求，请联系 register@clinicaltrials.gov. clinicaltrials.gov 上实施更改，我们的网站上也会自动更新.