Browsing by Author "Scott, Renn Patrick"

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Improving osseointegration of PEEK through surface textures
(Montana State University - Bozeman, College of Engineering, 2019) Scott, Renn Patrick; Chairperson, Graduate Committee: Cecily Ryan
PEEK (Polyetheretherketone) is one of the most promising alternatives to titanium in cortical bone implants due to being biologically inert and having an elastic modulus similar to that of bone. It also has favorable reactions conducive to common medical imaging methods such as X-ray and magnetic resonance imaging (MRI) as compared to commonly used metals such as titanium and stainless steel. However PEEK is not inherently osseoconductive, leading to longer healing times and a greater chance of infection. Many different methods exist for improving osteoblast growth, such as the addition of bio-active materials like hydroxyapatite. Manipulating the surface texture of PEEK could provide better environments for cells to attach and can be used as another layer with other techniques, making the tissue interface more robust. The main objective of this project is to observe cell adhesion to a textured surface to identify cell preference for surface geometry as a first step to improve full integration of non-resorbable implants into bone tissue. The methods explored were also chosen for their repeatability, reliability and lack of chemical modification compared to other successful surface modulation techniques. The surface textures were embossed into PEEK using micro-etched aluminum molds. Textures vary in their shape, spacing, size, depth and surface convexity/concavity. The cell adhesion was recorded through fluorescent confocal microscopy and the cell-substrate interaction was observed under electron microscopy. The results were that 25 micron and 10 micron features discouraged cell adhesion while 325 micron and 120 micron features encouraged cell adhesion with pillars performing better than holes. The best feature was the 325x40 micron square pillars. With a cell volume to surface area ratio of 5.13, a live cell count of 276.5, a dead cell count of 9.00, and a non-dimensional distance to feature of 0.67.