Ultrasound elestography for non-invasive assessment of tendon healing

University Of Rochester, Rochester NY

Investigators

Linked publications & trials

Abstract

Tendon injuries are very common and disrupt the transmission of forces from muscle to bone, leading to impaired function and quality of life. Successful restoration of tendon function after injury is a challenging clinical problem due to the pathological, scar-mediated manner in which tendons heal. Rather than regenerating native tendon tissue, tendons heal via bridging scar tissue composed of a disorganized collagen extracellular matrix (ECM). This scar tissue response results in mechanical properties that are inferior to native tendon, and increasing the risk of re-injury or rupture. Currently, there is no standard treatment in clinical use to modulate scar tissue formation and improve tendon healing. A major limitation to the identification and clinical translation of therapeutic candidates has been the reliance on terminal end-point metrics of healing in pre-clinical studies, which require a large number of animals and result in destruction of the tissue. There is currently no quantitative, non-destructive modality to assess tendon healing in mice. Therefore, our objective is to develop longitudinal, non-invasive metrics of tendon healing by combining ultrasound elasticity imaging and novel image registration methods. Ultrasound is an ideal modality to longitudinally assess tendon healing, as it is non-ionizing, and can be easily scaled between pre-clinical and clinical applications. Thus, we propose developing quantitative ultrasound outcomes of scar tissue volume, tendon excursion and tendon strain. To that end we will complete the following Specific Aims: Aim 1- Define, validate and correlate longitudinal ultrasound-based outcome measures of tendon healing with established-terminal endpoint outcomes of gliding function and mechanical properties. Aim 2- Demonstrate the sensitivity and specificity of US to longitudinally identify differences in healing using established models of scar-mediated and regenerative tendon healing. We will test the hypothesis that these metrics strongly correlate with terminal end-point parameters, and can therefore serve as faithful biomarkers of tendon healing. Development of this technology will permit the rapid screening of biological and pharmacological interventions to improve tendon healing, and identify promising therapeutic targets, in an efficient, cost-effective manner.