Multi-phase CFD modelling of biological tissue flows with applications in liver surgery

Computational Fluid Dynamics (CFD) has been used extensively in medicine to model the flow of blood in large arteries and veins and in the heart, but our understanding of the spatial propagation of body fluids on the microscopic level is more limited. The purpose of this PhD project is to enable the study of these processes by developing multi-phase CFD models for flow, diffusion and permeability in healthy and diseased biological tissues. Model development and validation will be guided by in-silico modelling as well as 4D dynamic data obtained by Magnetic Resonance Imaging (MRI) and indicator-dilution experiments.
Specifically, the project will produce a set of spatiotemporal models for tissue flow in several organs and diseases (such as brain, muscle, liver and cancer) that provide an accurate fit to measured data. Numerical solutions will be provided for the forward problem of generating 4D data from a given flow fields and boundary conditions, and for the inverse problem of mapping the flow fields based on measured data. A set of simplified digital tissues and organs will be coupled to models of the MRI scanner to provide a ground truth for the in-silico evaluation of these solutions under realistic experimental conditions.
This entirely novel approach to analysing and interpreting 4D dynamic MRI data will not only significantly improve upon the accuracy of current 1D models but can also reveal new insights on the way nutrients are delivered to healthy and diseased biological tissue. Furthermore, this will increase our understanding of how disease affects the function and structure of organs, and may in time improve patient outcomes by better diagnosis and more personalised treatment planning. In a final stage we will assess how application of these methods can improve survival of patients with liver cancer through better predictions of surgical risk. This will be achieved by exploring the clinical utility by developing a planning system for liver surgery that accounts for spatial patterns of tissue flow propagation.
This project involves a collaboration between academic supervisors from various backgrounds (Medical Imaging, Physics and Civil Engineering), and an industrial sponsor in the multinational pharmaceutical company, Bayer AG. The student will have a unique opportunity to gain in-depth knowledge of the theoretical and numerical basis of multi- phase CFD modelling and data assimilation techniques, but also about their applications in medicine - a major growth area for CFD. The industrial sponsor will provide an opportunity for a temporary placement in Berlin where the student will learn how to translate research ideas into patient benefit. Additionally, the student will, in collaboration with the industrial supervisor, package the models proposed in this project up into a prototype software tool and use this to explore the opportunities for future commercialisation.