DEVICE DESIGN AND FINITE ELEMENT MODELING TO BETTER UNDERSTAND THE RESPONSE OF ARTICULAR CARTILAGE TO CYCLICAL COMPRESSIVE LOADING

Articular cartilage provides low friction load support between opposing surfaces in major joints throughout the body. A central feature of cartilage is that it can withstand countless cycles of loading, and thus it is critical to understand the biological response to mechanical forces at the organism, tissue, and cellular scales. Despite decades of research, many important questions regarding the mechanobiology of articular cartilage remain unanswered and this limits our capacity to understand the drivers of osteoarthritis (OA) - a chronic degenerative joint disease that plagues one in five adults of advanced age. One barrier to a more complete understanding of cartilage is the challenges associated with measuring the response to mechanical stimuli in a holistic manner. In this dissertation, I introduce a novel device (the MagnaSquish) that applies cyclical compression to cartilage explants in a manner that allows for free swelling in between cycles to study both axial and lateral strain. Next, I utilize convolution neural networks to perform morphometric measurements with high resolution images to improve the accuracy of our novel vision-based strain pipeline. I then leverage the full two-dimensional profiles to provide boundary conditions for image-driven finite element models of cartilage under load. This approach not only establishes an anatomically correct initial state, but also enables the time evolution of strain during dynamic compression to influence the readouts of the numerical simulation. Finally, I seek to harness the lessons learned during construction and use of the MagnaSquish to re-design the machine in a manner that is consistent with the open-source hardware movement by utilizing only off-the-shelf and 3D-printed parts. The goal of MagnaSquish 2.0 is to democratize biomechanics studies and put these important tools into the hands of researchers who can investigate novel hypotheses in future studies. Together, the work of this dissertation establishes a pipeline that brings together the related fields of biomechanics and mechanobiology to better understand the response of cartilage to cyclical loading at the tissue and cellular scales.