Funded Projects

The University of Michigan (UM) will lead a Mechanistic Research Center (MRC) as part of the broader BACPAC initiative that will take patients with chronic low back pain (cLBP) and use a patient-centric, SMART design study to follow these individuals longitudinally as they try several different evidence-based therapies while mechanistic studies are overlaid to draw crucial inferences about what treatments will work in what patient endotypes. Interventional Response Phenotyping describes the need in any precision medicine initiative to phenotype participants based on what therapies they do and do not respond to so that one can later link mechanistically distinct disease endophenotypes with those who preferentially respond to therapies targeting those mechanisms.

A complex network of different nerve cell subtypes connects to joints in different ways throughout body regions, such as the knee and the temporomandibular joint (TMJ) that connects the lower jaw and skull. This project aims to identify disease-specific pain symptoms using clinically relevant rat models of TMJ and knee osteoarthritis – and compare findings with disease-specific pain symptoms in human patients with the same conditions. This research may lead to a better understanding of how different nerve cell subtypes contribute to joint pain as well as how these nerve cell subtypes change with age and disease.

Every year, more than 330,000 Americans are hospitalized for hip fractures. Rapid surgical intervention and pain treatment is critical to recover mobility and reduce other health complications. Ultrasound-guided regional anesthesia techniques are an effective alternative to opioid medication, but require specialized training for use in the emergency department. This project will develop and validate an easy-to-use ultrasound-based regional anesthesia guidance system, to ultimately improve access to non-opioid-pain treatment for hip fracture pain.

The University of California, San Francisco, as part of the Back Pain Consortium (BACPAC) Research Program, has established a Core Center for Patient-centric Mechanistic Phenotyping in Chronic Low Back Pain (REACH). The main goal of REACH is to define different subtypes (phenotypes) of chronic low back pain as well as to identify underlying pain mechanisms that can lead to effective, personalized treatments for patients across all population subgroups. To achieve this goal, REACH is, or will be, participating in several clinical trials, and it is imperative that the patients participating in these trials reflect the diversity of the U.S. population. Therefore, this project seeks to adapt methods that have successfully improved minority participation in other settings as well as to develop and deploy digital strategies that can promote recruitment and engagement of patients from marginalized populations.

Digital health interventions, such as virtual reality (VR) applications, have become available for the treatment and monitoring of numerous health conditions, including pain management. A current HEAL-funded study is evaluating the role of a therapeutic VR approach for chronic low back pain. However, racial and ethnic disparities exist in patient access and response to such VR applications, as well as in the incidence and reporting of pain. For example, non-Hispanic Blacks and Hispanics are more likely to report severe pain than non-Hispanic Whites, yet are less likely to have access to digital health information and interventions. To address these disparities, this project will develop a framework to advance diversity and inclusion in digital health trials and will seek to increase the proportion of non-Hispanic Black and Hispanic participants in the ongoing VR trial by tailoring recruitment materials and using novel artificial intelligence-driven cohort building tools.

 Non-Invasive Brain Stimulation (NIBS) has been successfully applied for the treatment of chronic pain (CP) in some disease states, where treatment induced changes in brain activity revert maladaptive plasticity associated with the perception/sensation of CP [25-28]. However, the most common NIBS methods, e.g., transcranial direct current stimulation, have shown limited, if any, efficacy in treating neuropathic pain. It has been postulated that limitations in conventional NIBS techniques’ focality, penetration, and targeting control limit their therapeutic efficacy . Electrosonic Stimulation (ESStim™) is an improved NIBS modality that overcomes the limitations of other technologies by combining independently controlled electromagnetic and ultrasonic fields to focus and boost stimulation currents via tuned electromechanical coupling in neural tissue . This proposal is focused on evaluating whether our noninvasive ESStim system can effectively treat CP in carpal tunnel syndrome (CTS), both as a lone treatment and in conjunction with physical therapy (PT). Investigators hypothesize ESStim can be provided synergistically with PT, as both can encourage plasticity-dependent changes which could maximally improve a CTS patient’s pain free mobility. In parallel with the CTS treatments, the team will build multivariate linear and generalized linear regression models to predict the CTS patient outcomes related to pain, physical function, and psychosocial assessments as a function of baseline disease characteristics. The computational work will be used to develop an optimized CTS ESStim dosing model. 

The goal of this proposal is to conduct a randomized controlled trial to evaluate the comparative effectiveness of conservative behavioral and nonopioid pharmacological treatments (Phase I) and, among nonresponders, the benefits of nonsurgical procedural interventions (Phase II). Aim 1 will evaluate the effectiveness of individual and combined online cognitive behavioral therapy (painTRAINER) and pharmacologic treatment (duloxetine) in improving pain and function for knee osteoarthritis (KOA) patients compared with standard of care. Aim 2 will determine if genicular nerve radiofrequency ablation or intra-articular injection of hyaluronic acid and steroid is more effective in improving outcomes than local anesthetic nerve block or standard of care and help establish the role of these interventional treatments in the overall management of pain in KOA patients. Aim 3 will test whether clinical and psychosocial phenotypes predict short- and long-term treatment response.

This project will use a variety of technologies to create a comprehensive, 3D map of how sensory neurons activate knee joints in both mice and humans. The research will use imaging techniques and molecular approaches that measure gene expression. The findings will help create a comprehensive gene expression profile map of individual cells in the nerve fibers leading to the knee, as well as describe how nerve cells and joint cells interact at the most fundamental level. This research will generate a rich anatomical and molecular resource to understand the molecular basis of joint pain and guide the development of novel pain-relieving strategies.

Identifying optimal chronic low back pain treatments on a patient-specific basis is an important and unresolved challenge. Tailoring interventions according to patient movement characteristics is one option. This research is characterizing patients based on spinal motion during functional tasks and daily activities and will use artificial intelligence to objectively characterize motions of the spine during both clinical assessments and day-to-day life. During clinical assessments, participants will be asked to perform functional tasks while wearing motion sensors. Data collected from the sensors will be used to identify tasks of interest, such as activities of daily living and aberrant/painful motions. An artificial intelligence approach will then interpret data collected continuously during assessment in patients’ homes over a 7-day testing period. Ultimately, this data could be used to help clinicians tailor treatments that are responsive to a patient’s real-world functional impairments.

Identifying optimal chronic low back pain treatments on a patient-specific basis is an important and unresolved challenge. Tailoring interventions according to patient movement characteristics is one option. This research is characterizing patients based on spinal motion during functional tasks and daily activities and will use artificial intelligence to objectively characterize motions of the spine during both clinical assessments and day-to-day life. During clinical assessments, participants will be asked to perform functional tasks while wearing motion sensors. Data collected from the sensors will be used to identify tasks of interest, such as activities of daily living and aberrant/painful motions. An artificial intelligence approach will then interpret data collected continuously during assessment in patients’ homes over a 7-day testing period. Ultimately, this data could be used to help clinicians tailor treatments that are responsive to a patient’s real-world functional impairments.

This project will examine the association between end plate pathology and chronic low back pain (cLBP) and improve patient selection by developing and translating new imaging tools, technologies, and/or methods (iTTM) that provide accurate, noninvasive measures of end plate pathologies. A search for clinically relevant biomarkers of end plate pathology will focus on novel imaging measures of end plate bone marrow lesion (BML) severity with IDEAL MRI and cartilage endplate (CEP) fibrosis/damage with UTE MRI, assess interactions with paraspinal muscles, and identify metrics that associate with pain, disability, and degeneration. The research will refine imaging and post-processing methodologies by leveraging and expanding existing cross-sectional cohorts and then deploy and validate the new end plate iTTM to other BACPAC sites to test the most promising metrics’ clinical utility. These studies will provide validated iTTM that are useful for addressing the end plates pathology’s role in cLBP, identifying sub-phenotypes, discovering pain mechanisms, uncovering treatment targets, and selecting patients.

Patients with chronic low back pain, often have depressive and anxiety symptoms and use opioids all of which are associated with stigma. In turn stigma leads to decreased treatment seeking and adherence, increased depression and pain, and poor treatment outcomes. Intersection of these health-related stigmas may have synergistic effects. This study aims to enhance the findings of a clinical trial to test antidepressant medication and Enhanced Fear Avoidance Rehabilitation in patients with chronic low back pain and high levels of depression and anxiety. The effects of these intersecting types of stigma on the efficacy of the interventions will be evaluated to better understand the needs of the patient population and to inform development of a stigma reducing intervention that can be implemented care providers.