Computational Models of Perfusion Circuits for Organ Transplantation

在用于人类环境之前，需要对诊断和治疗技术进行临床前研究，以探索、测试和验证新的方法。动物研究的结果经常被用作人体解剖学的模型，尽管在某些情况下，生理学差异很大。同样，基于对缺乏含氧血液的担忧，体外人体组织实验结果的相关性可能会受到质疑。在某些情况下，来自临床前模型的不正确假设被纳入影响其价值的人体试验。这篇博士论文将研究和开发能够结合先进的传感和成像技术的器官灌注技术，以及用于推断器官状态和改变灌流系统特征的计算模型。组织监测将通过对灌流液(血液或人工灌注液)的采样进行调查，以分析器官功能的生化标志物。直插式光学传感器将通过用于安装外部成像和传感技术的接入端口，实现对氧合水平的持续监测。外部安装的摄像头和组织标记器将允许使用视觉绘制器官表面的地图，该系统将被用于开发新的模型，通过训练系统切割外部和内部传感信息，可以在没有介入传感器的情况下推断组织属性。

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.