Computational Models of Perfusion Circuits for Organ Transplantation

Preclinical research of diagnostic and therapeutic technologies is required to explore, test and validate new methodologies before use in the human setting. Results from animal studies are often used as a model of human anatomy despite vastly different physiology in some cases. Similarly, the relevance of results derived from ex vivo human tissue experiments may be questioned based on concerns over the lack of oxygenated blood. In some cases, incorrect assumptions, derived from preclinical models, are incorporated into human trials impacting their value. This doctorate thesis will research and develop organ perfusion technology that can incorporate advanced sensing and imaging as well as computational models for inferring organ state and altering the perfusion system characteristics. Tissue monitoring will be investigated using sampling of perfusate (blood or artificial perfusion solution) in order to analyse biochemical markers of organ function. In-line optical sensors will enable continuous monitoring of oxygenation levels with access ports for mounting of external imaging and sensing technologies. Externally mounted cameras and tissue markers will allow mapping of the organ's surface using vision and the system will be used to develop new models than can infer tissue properties without interventional sensors by training to systems paring the extrinsic and internal sensing information.