Funded Projects

Myofascial pain syndrome is a prevalent and debilitating condition and can aggravate other conditions such as sickle cell disease. This project will use total body imaging using positron emission tomography/computed tomography (TB-PET/CT) to identify and monitor this pain syndrome and potential treatments over time. The research will use TB-PET/CT to assess myofascial tissue effects of chronic low back pain and sickle cell disease pain. The first phase of the project will assess health changes observed by TB-PET/CT imaging in painful and non-painful myofascial tissues compared to healthy myofascial tissue. The second phase of the research will be a randomized, controlled longitudinal interventional study to evaluate the effectiveness of acupuncture on myofascial pain syndrome, using TB-PET/CT imaging to assess changes.

Pain in the muscles and surrounding connective tissue (myofascial pain) is a significant and poorly understood health concern affecting hundreds of millions of Americans. There is a great need for tools to assess changes to myofascial tissues in individuals with chronic pain as well as to measure the effect of commonly used therapies. This project will use three imaging tools to look at differences between shoulder tissue in people with myofascial pain compared to those without pain. Using a machine learning approach, this research aims to develop a biomarker signature for myofascial pain, which will be evaluated in a randomized controlled clinical trial based on its ability to predict patient responses to myofascial pain treatments.

Shoulder pain occurs in many patients who are recovering from a stroke. In addition to impairments in the ability to move, persistent shoulder pain contributes to depression, and often reduces quality of life. Although the cause of post-stroke shoulder pain is complex and not completely understood, it is thought to arise in part to damage of muscles and surrounding connective tissues (myofascial tissues) in the shoulder. This project will use advanced medical imaging techniques to create biomarkers of that can reliably identify myofascial tissues. The research will then test the ability of these biomarkers to monitor, and ultimately predict treatment responses in patients with post-stroke shoulder pain in the context of a randomized controlled clinical trial.

Pain in the muscles and surrounding connective tissue (myofascial pain) is a significant health concern affecting hundreds of millions of Americans.  Myofascial pain is primarily diagnosed by asking people about their amount of pain as well as through a physical examination. Both approaches are imprecise ways to diagnose the specific type of pain a patient is experiencing and what is causing it. This project aims to improve myofascial pain management and treatment by developing ways to measure changes to soft tissues (e.g., muscle, connective tissues, nerves, blood vessels) in people with myofascial pain compared with soft tissues in people who are not in pain. The project will develop an imaging biomarker that can distinguish healthy and diseased soft tissues that may contribute to myofascial pain syndrome. The project will then test the ability of these biomarkers to predict patient outcomes in a randomized controlled clinical trial.

Chronic pain is a major health burden associated with immense economic and social costs. Predictive biomarkers that can identify individuals at risk of developing severe and persistent pain, which is associated with worse disability and greater reliance on opioids, would promote aggressive, early intervention that could halt the transition to chronic pain. The applicant’s team uncovered evidence of a unique cortical biomarker signature that predicts pain susceptibility (severity and duration). This biomarker signature could be capable of predicting the severity of pain experienced by an individual minutes to months in the future, as well as the duration of pain (time to recovery). Analytical validation of this biomarker will be conducted in healthy participants using a standardized model of the transition to sustained myofascial temporomandibular pain. Specifically the biomarker signature will be tested for its ability to predict an individual’s pain sensitivity, pain severity, and pain duration and will perform initial clinical validation.