Osteochondral allograft transplantation is a surgical repair technique that replaces damaged cartilage with osteochondral grafts, consisting of bone and cartilage, from a cadaveric donor. These grafts are stored for a minimum of 14 days before transplantation in order to complete routine screening and storage methods are used to ensure chondrocytes (cartilage cells) remain viable over this time. We have developed a fluorescent staining method to identify changes in chondrocyte metabolism concurrently with viability and recently developed a grading system to describe certain visual features. In this multidisciplinary project, the student will develop a machine learning algorithm to classify chondrocytes using an existing bank of images and participate in bench top experiments to gather data at additional storage time points. The results from this project will contribute to understanding how chondrocytes respond to prolonged storage and support efforts to increase the quantity and quality of fresh osteochondral allografts available for clinical use.
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