The overall objective of this project is to systematically refine and validate our novel magnetic resonance imaging protocol for the non-invasive measurement of the biomechanical properties of healing soft tissues. This translational tool will be advantageous for pre-clinical and clinical trials to evaluate up-and-coming technologies for ligament and tendon repair. For this study we will focus on the anterior cruciate ligament (ACL) as a model of ligament injury. We have shown that magnetic resonance (MR) imaging measurements of ligament size (i.e., amount of tissue) and signal intensity (i.e., quality of tissue) correlate to the biomechanical properties of the ACL, and that the combination of ligament size and signal intensity further improved these predictions. Unfortunately, signal intensity is dependent on image acquisition parameters thus protocol, magnet, and hence institution dependent. However, T2* relaxation time is an MR tissue property that correlates to collagen organization in tissues that is not as acquisition dependent. We now have preliminary evidence to show that T2* relaxation times within a healing ligament provides a more reliable estimate of the structural properties. The next step is to refine and validate this T2* MR-based prediction method for use in longitudinal studies of ligament healing.
In Aim 1, we will obtain MR-measures of volume and T2* of the healing ACL following two repair strategies. These measures will be collected in the early proliferative, middle and later remodeling stages of healing in a cross sectional study to examine how robustly the model predicts the biomechanical properties across these stages of healing, and to incorporate time effects into the model if necessary.
In Aim 2, we will perform a longitudinal study of our MR-based approach to validate its utility for discriminating between two repair strategies known to produce differences in healing and to determine if scans obtained in the early stages of healing will predict the longer-term biomechanical properties. This finding would be very valuable as it would reduce the cycle time of both pre-clinical and clinical ligament healing studies. The project will take advantage of our well established pre-clinical model of bio-enhanced ACL repair. In this study, our MR based multi-regression prediction model will be refined in Aim 1 and validated in Aim 2. Primary outcome measures include the MR parameters (T2* relaxation time, signal intensity, volume) and the structural properties (failure load, linear stiffness) of the healing ACL. Secondary outcomes include the ACL material properties (failure stress, tangent modulus) and knee laxity. At study completion we will have refined our MR- based prediction models, validated its use for surgical repair studies, and be poised to use the MR technique as a primary outcome measure in clinical trials of ACL repair and reconstruction.
There remains a dire need for a non-invasive technique to evaluate the strength of healing ligaments and tendons in the body, which would allow physicians and researchers to assess new treatment strategies and to design rehabilitation protocols tailored to the current strength of the healing ligament or tendon. Our preliminary data support the use of our novel magnetic resonance imaging (MRI) technique to accurately predict the biomechanical properties of a healing ligament without harming any tissue. This proposal will refine and validate the MRI-based approach to predict the ligament properties over time during healing with the goal of using the novel method in clinical trials of new tissue repair strategies.
|Kiapour, Ata M; Cao, Jiaxue; Young, Mariel et al. (2018) The role of Gdf5 regulatory regions in development of hip morphology. PLoS One 13:e0202785|
|Sieker, Jakob T; Proffen, Benedikt L; Waller, Kimberly A et al. (2018) Transcriptional profiling of articular cartilage in a porcine model of early post-traumatic osteoarthritis. J Orthop Res 36:318-329|
|Beveridge, Jillian E; Machan, Jason T; Walsh, Edward G et al. (2018) Magnetic resonance measurements of tissue quantity and quality using T2 * relaxometry predict temporal changes in the biomechanical properties of the healing ACL. J Orthop Res 36:1701-1709|
|Sieker, Jakob T; Proffen, Benedikt L; Waller, Kimberly A et al. (2018) Transcriptional profiling of synovium in a porcine model of early post-traumatic osteoarthritis. J Orthop Res :|
|Beveridge, Jillian E; Walsh, Edward G; Murray, Martha M et al. (2017) Sensitivity of ACL volume and T2? relaxation time to magnetic resonance imaging scan conditions. J Biomech 56:117-121|
|Perrone, Gabriel S; Proffen, Benedikt L; Kiapour, Ata M et al. (2017) Bench-to-bedside: Bridge-enhanced anterior cruciate ligament repair. J Orthop Res 35:2606-2612|
|Biercevicz, Alison M; Akelman, Matthew R; Fadale, Paul D et al. (2015) MRI volume and signal intensity of ACL graft predict clinical, functional, and patient-oriented outcome measures after ACL reconstruction. Am J Sports Med 43:693-9|
|Biercevicz, Alison M; Proffen, Benedikt L; Murray, Martha M et al. (2015) T2* relaxometry and volume predict semi-quantitative histological scoring of an ACL bridge-enhanced primary repair in a porcine model. J Orthop Res 33:1180-7|
|Biercevicz, A M; Akelman, M R; Rubin, L E et al. (2015) The uncertainty of predicting intact anterior cruciate ligament degeneration in terms of structural properties using T(2)(*) relaxometry in a human cadaveric model. J Biomech 48:1188-92|