40 Participants Needed

Multi-modal Imaging for Myofascial Pain Syndrome

Age: 18+
Sex: Any
Trial Phase: Academic
Sponsor: Washington University School of Medicine
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)

Trial Summary

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

What data supports the effectiveness of the treatment Multi-modal Imaging for Myofascial Pain Syndrome?

Research shows that ultrasound imaging can help identify myofascial trigger points, which are key in diagnosing myofascial pain syndrome. This suggests that imaging techniques, like those used in the treatment, could be effective in managing this condition by providing a more accurate diagnosis.12345

How does the multi-modal imaging treatment for myofascial pain syndrome differ from other treatments?

This treatment is unique because it uses advanced imaging techniques like MRI to better understand and visualize the muscle structures involved in myofascial pain syndrome. Unlike traditional methods, this approach aims to provide detailed insights into the muscle's microstructure, potentially leading to more accurate diagnosis and targeted treatment.678910

What is the purpose of this trial?

The goal of this study is to develop new imaging biomarkers for quantitative assessments of myofascial pain.

Eligibility Criteria

This trial is for healthy volunteers who currently have mild or no chronic pain in their neck and shoulder, can perform daily activities without limitation due to pain, and understand the study's purpose. They must be able to give informed consent.

Inclusion Criteria

Healthy Volunteer
I have never had chronic pain in my neck or shoulder that stopped me from daily activities or work.
I understand the study's purpose and agree to participate.
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Timeline

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Imaging

Participants undergo multi-modal imaging including MRI, sEMG, and fiber-optic imaging

1 day
1 visit (in-person)

Follow-up

Participants are monitored for safety and effectiveness after imaging

2-4 weeks

Treatment Details

Interventions

  • Multi-modal, multi-parametric, multiscale imaging
Trial Overview The study aims to develop new ways of imaging muscles and fascia (the connective tissue around muscles) to better understand myofascial pain. It involves advanced imaging techniques that look at the muscle-fascia unit in different ways.
Participant Groups
1Treatment groups
Experimental Treatment
Group I: Multi-modal imaging of myofascial painExperimental Treatment1 Intervention
Participants with and without myofascial-related pain disease will receive multi-modal, multi-parametric, multi-scale imaging, including magnetic resonance imaging, surface electromyography, and fiber-optic imaging and sensing.

Find a Clinic Near You

Who Is Running the Clinical Trial?

Washington University School of Medicine

Lead Sponsor

Trials
2,027
Recruited
2,353,000+

National Center for Complementary and Integrative Health (NCCIH)

Collaborator

Trials
886
Recruited
677,000+

Findings from Research

A study involving 201 participants and 1344 ultrasound images demonstrated that convolutional neural networks (CNN) can effectively identify muscles with myofascial trigger points (MTrPs) compared to traditional texture analysis methods, achieving a higher F1-score of 0.7299.
The research highlights the challenges in accurately diagnosing myofascial pain syndrome and suggests that while deep learning techniques show promise, there are still limitations to their effectiveness in clinical settings.
Myofascial Trigger Point Identification in B-Mode Ultrasound: Texture Analysis Versus a Convolutional Neural Network Approach.Koh, RGL., Dilek, B., Ye, G., et al.[2023]
Kinesio taping significantly reduces pain intensity and improves range of motion in patients with myofascial pain syndrome, based on a meta-analysis of 20 randomized controlled trials involving 959 patients.
While kinesio taping shows effectiveness in pain relief and mobility, it does not appear to have a significant impact on overall disability or functional improvement.
Evidence for kinesio taping in management of myofascial pain syndrome: a systematic review and meta-analysis.Zhang, XF., Liu, L., Wang, BB., et al.[2022]
Imaging studies have shown that myofascial trigger points exhibit distinct biomechanical properties and blood flow patterns compared to healthy tissue, indicating a potential objective way to assess myofascial pain syndrome.
Ultrasound-based imaging methods are currently favored for evaluating myofascial pain syndrome due to their efficacy, cost-effectiveness, and ease of use, although more research is needed to improve diagnostic accuracy and reproducibility.
Assessment of Myofascial Trigger Points via Imaging: A Systematic Review.Mazza, DF., Boutin, RD., Chaudhari, AJ.[2023]

References

Myofascial Trigger Point Identification in B-Mode Ultrasound: Texture Analysis Versus a Convolutional Neural Network Approach. [2023]
Evidence for kinesio taping in management of myofascial pain syndrome: a systematic review and meta-analysis. [2022]
Assessment of Myofascial Trigger Points via Imaging: A Systematic Review. [2023]
Fibromyalgia and myofascial pain syndrome: Two sides of the same coin? A scoping review to determine the lexicon of the current diagnostic criteria. [2019]
Assessment of Myofascial Trigger Points Using Ultrasound. [2016]
Potential Role of MRI Imaging for Myofascial Pain: A Scoping Review for the Clinicians and Theoretical Considerations. [2021]
A process model for direct correlation between computed tomography and histopathology application in lung cancer. [2021]
Rapid musculoskeletal magnetic resonance imaging using integrated parallel acquisition techniques (IPAT)--initial experiences. [2019]
Potential of PET-MRI for imaging of non-oncologic musculoskeletal disease. [2020]
10.United Statespubmed.ncbi.nlm.nih.gov
Molecular imaging of musculoskeletal diseases. [2012]
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