Computational modelling of perfusion to the heart

Blood supply (perfusion) to the heart can be approximated by a set of partial-differential equations (PDE) that model tissue as a sponge-like material. The student will expand our existing model solver to allow for validation using imaging data.
Master

Perfusion, i.e. blood supply, to the heart can be approximated by a poroelasticity model that treats tissue as a sponge-like material. We have developed a finite element solver for poroelasticity based on the FEniCS project. This modelling framework allows us to study the effects of normal contraction of the heart, as well as the effects of disease, on blood distribution within the heart (or other organs), and vice versa. This is particularly relevant for the successful interpretation and prediction of outcomes of for example infarct or long-term remodelling leading to heart failure. The student will expand this solver to allow for validation of perfusion models using perfusion SPECT imaging data.

Goal

The goal is to expand our existing poroelasticity solver framework to include code that allows for validation of perfusion models using perfusion SPECT imaging data.

Learning outcome

The student will gain experience in biophysical modelling from the PDE system to model validation, application of finite elements to solve PDEs, as well as software development

Qualifications

  • programming in Python
  • basic understanding of partial-differential equations
  • experience with finite elements and/or FEniCS is beneficial but not required
  • keen interest in biological systems.

Supervisors

Alexandra Diem

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