25584 Blood flow modeling in brain vasculature during neuro-interventional procedures
Begeleider(s): dr. ir. Danilo Babin

Richtingen: Master of Science in Biomedical Engineering, International Master of Science in Biomedical Engineering

Probleemstelling:

There is an ongoing trend towards less invasive medical procedures. This is best illustrated in the fields of cardiology and vascular surgery, where treatment is nowadays more often based on catheter-based procedures rather than open surgery: e.g. treatment of occluded blood vessels using coronary angioplasty or the stenting of peripheral arteries. This trend is also observable in neurology: for example, catheter-based coiling of brain aneurysms is now preferred above surgical clipping when possible. Sometimes, there is even no surgical alternative and one can only rely on minimally invasive procedures, such as mechanical thrombectomy (the removal of a blood clot during acute ischemic stroke).

The main risk during neuro-interventional procedures is thrombogenic: due to manipulation of a catheter inside the brain vasculature, a blood clot can be generated which then causes occlusion of a blood vessel downstream. It is well known from cardiovascular research that the risk of thrombus formation can be related to the blood fluid dynamics, e.g. shear stress.


Doelstelling:

Blood flow can be modeled using dedicated simulation software (Ansys Fluent). The goal of this thesis is to determine blood flow properties inside normal cerebral vasculature, and during catheter procedures. This can then be used to assess the thrombogenic risk during these procedures, and suggest mechanisms to reduce this risk.

The student should first study the literature regarding the technical aspects of neuro-interventional procedures, the assessment of thrombogenic risk in intravascular procedures, and blood flow modeling. A macroscopic model of cerebral vasculature will then be developed based on angiography data. For the microscopic properties, a model can be developed based on available histologic data of brain vasculature. Blood flow will then be modeled during catheter-based procedures with different properties: arterial or venous access, different catheter materials, etc. The flow properties derived from these simulations will then be used to assess thrombogenic risk.