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临床试验/NCT05928884
NCT05928884已完成不适用

Development and Validation of a Noninvasive Multimodal Ultrasound-Based Imaging Biomarker for Myofascial Pain

University of Pittsburgh1 个研究点 分布在 1 个国家目标入组 124 人开始时间: 2023年10月1日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
入组人数
124
试验地点
1
主要终点
Diagnosis of one of four MP-related categories

研究概览

简要总结

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

详细描述

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).

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
20 Years 至 70 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • 未提供

排除标准

  • 未提供

结局指标

主要结局

Diagnosis of one of four MP-related categories

时间窗: Study Visit 1 (week 1)

Participants to be diagnosed as normal, MP without TPs, MP with latent TPs, and MP with active TPs as determined by standardized clinical examinations.

次要结局

  • Presence of Substantial MP(Study Visit 1 (week 1) - Study Visit 2 (week 2))

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Ajay Wasan, MD, Msc

Professor

University of Pittsburgh

研究点 (1)

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