Pain assessment is a pressing clinical problem in need of better measurement tools. Proposed solutions include electroencephalography and event-related potentials (EEG/ERP), autonomic measures such as heart-rate and heart-rate variability, and analysis of facial expressions. All of these promising modalities could potentially combine into one streamlined test by establishing the protocols that give the highest information content for the lowest clinical-time burden. In addition these markers should be validated in generalized clinical settings and should bear/bare some relationship to pathophysiological mechanisms of pain. This proposal utilizes the experience of fMRI-based pain studies from the University of Colorado Affective Neuroscience Laboratory and WAVi, a commercialized brain-assessment platform. The WAVi platform presently incorporates all of these above-mentioned modalities into their clinic-friendly system for other purposes, including a combination of ERP and reaction time that is highly sensitive to concussion.
The aims of this project are to similarly develop a scalable WAVi-based test for acute musculoskeletal pain that is readily accessible to clinicians; to use the fMRI to validate, interpret, and improve the WAVi markers; and to create a dynamic data asset to help longitudinally predict transition to chronic pain and test interventions. Accomplishing these aims will assist clinicians on the front lines of pain assessment and treatment, not to replace clinical judgments, but to serve as a component in a multi-modal assessment. The platform needs to be scalable into a wide variety of settings, with simple objective readouts for clinicians: ? to aid the diagnosis and management of acute pain, including opioid decisions ? to help assess the extent of potential tissue injury. ? to identify risk of transition to chronic pain, actionable through more aggressive interventions (control of inflammation, prevent reinjury, etc.). ? to identify successful interventions. ? to help patients whose pain is not believed (CRPS, fibromyalgia, chronic fatigue). This study will focus on data collected from clinical settings currently using the WAVi system, on patients when in pain and at the presumably pain-free final visit, with a subset of patients also receiving an fMRI.
This project will help create a clinically-accessible test for pain assessment, provide insight into pathophysiological mechanisms of pain, and structure an in-vivo dataset to explore both acute-chronic pain transitions and interventional outcomes.
