Over one third of all musculoskeletal injuries in the United States involve connective tissue deterioration, resulting in an annual incidence of more than 10 million injuries. Despite this high prevalence, clinicians have limited tools to diagnose and prevent these injuries. With the help of tissue biomechanics and biomedical imaging, novel tools can be developed to improve the clinical care of patients most susceptible to joint injuries. Physical joint models can be used to simulate injury diagnosis tests for ligaments and tendons. However, materials capable of replicating tissue mechanics and available to be implemented in joint models are lacking. Diffusion Tensor Imaging (DTI), a Magnetic Resonance Imaging technique, can provide non-invasive assessments of brain and skeletal muscle but requires microstructural validation in tendons and ligaments. Therefore, the aim of this thesis was to (1) develop tissue-mimicking model materials for ligament and tendon, (2) assess the ability of DTI to detect mechanically-induced changes in tissue-mimicking fiber structures, and (3) noninvasively assess fatigue-induced damage in tendons using DTI.

In Aim 1, a material construct that is both adaptable to a physical knee model and capable of replicating the non-linear mechanical behavior of knee ligaments was developed with the use of helically architected acrylic yarn. The microstructure of different types of acrylic yarn were measured and then tested under uniaxial tension. While the fiber twist angle was similar amongst the four yarn types (range = 17.9 - 18.8°), one yarn was distinct with a low ply twist angle (15.2 ± 1.6 degrees) and high packing fraction (Φ = 0.32 ± 0.08). Looped-yarn constructs were made to modulate the sample’s toe length and stiffness. The load-displacement curve of the construct can be tuned by changing the loop length and number of loops, matching the load-displacement curve of specific knee ligaments. This aim shows how spun yarn can be used to replicate the mechanical behavior of knee ligaments, creating synthetic ligament constructs that could enable the construction of biomechanically realistic joints. These yarn constructs also have the potential to be used as microstructural imaging phantoms for tendons and ligaments.

Using the tissue-mimicking material developed in Aim 1, the ability of DTI to detect microstructural changes caused by mechanical loading in tissue-mimicking helical fiber constructs was assessed in Aim 2. Static and fatigue loading resulted in decreased sample diameter and a re-alignment of the macro-scale fiber twist angle similar with the direction of loading. However, the DTI measurements suggest microstructural differences in the effect of static versus fatigue loading that were not apparent at the bulk level. Specifically, static load resulted in an increase in diffusion anisotropy and a decrease in radial diffusivity suggesting radially-uniform fiber compaction, while fatigue loads resulted in increased diffusivity in all directions and a change in the alignment of the principal diffusion direction away from the constructs main axis suggesting fiber compaction and microstructural disruptions in fiber architecture. These results provide quantitative evidence of the ability of DTI to detect mechanically-induced changes in tissue microstructure that is not apparent at the bulk level, thus confirming it’s potential as a non-invasive measure of microstructure in helically architected collagen-based tissues such as ligament and tendon.

To validate the use of DTI as a non-invasive biomarker of tendon and ligament health, asessing the ability of DTI to detect fatigue-induced microstructural damage is necessary. Currently for Aim 3, DTI was conducted on 2 tendon samples before and after subjecting them to fatigue loading, and the changes in DTI metrics between the pre and post-fatigue scans were assessed. Regional changes in the DTI metrics of the tendons were observed after fatigue loading. Specifically, a decrease in diffusion anisotropy and an increase in diffusivity was observed in the central regions of the tendons, while a misalignment of the principal diffusion direction was observed in the outer regions of one of the tendons. These preliminary results suggest that DTI metrics are capable of detecting fatigue-induced microstructural changes in tendons. However, more tendons need to be assessed and the confirmation of collagen fiber disruptions in the tissue via microscopy are needed to validate these preliminary results. Once finished, this study will provide a comprehensive evaluation of the ability of DTI to detect fatigue-induced disruptions in the collagen fiber microstructure of tendons.