Personalised haemodynamic coagulation cascade-based model in the left atria

Coagulation is a mechanism of the cardiovascular system that stops haemorrhage. While this process is beneficial, as clots allow to close wounds, if they go into the circulatory system they can cause stroke. Several studies have identified the left atria, and more specifically the left atrial appendage, as the main source of adverse thrombi, especially in the presence of atrial fibrillation and left atrial enlargement.

 

Therefore, to reduce the burden of stroke, we need to identify patients with a higher risk of developing thrombi. This is challenging, as there are several factors involved: first, it is known that thrombus formation is related to slow blood flow and stagnation. Second, there is a series of biochemical reactions in the form of a cascade, in which different enzymes are activated sequentially, which makes the clot stiffer. This coagulation cascade is not independent of the flow, as reaction rates are dependent on the local velocity and shear stress. To this end,  several attempts to model the coagulation cascade have been made, but introducing flow information to the coagulation cascade remains to be done. Coupling both factors will be a key step towards predicting and understanding thrombus formation. 

In the research group PhySense, led by Prof. Camara, we have developed in-house computational models of both the haemodynamics and the coagulation cascade separately. In this work, you will combine both models to obtain the distribution of the key blood coagulation proteins based on patient-specific left atrial geometries and flow patterns, by accounting for both their reactions using the coagulation cascade and their displacement due to the blood flow.

 

Requirements

·      Student of biomedical engineering (bachelor or master), or related degree.

·      Basic knowledge on hemodynamics and biochemistry.

·      Basic knowledge on numerical methods (finite differences or finite elements).

·      Matlab or Python programming. Experience with CFD software and visualization tools (i.e., Paraview) is a plus.

 

 

Contact: [email protected], [email protected], [email protected].