Computational modeling and imaging of hemodynamics in intracranial aneurysms

Computational fluid dynamics (CFD) has gained increasing attention for modeling patient-specific intracranial aneurysms to improve rupture risk assessment. This thesis employs an open-source FEniCS-based finite element code to simulate blood flow in intracranial aneurysms and compute key hemodynamic parameters, including wall shear stress, oscillatory shear index, and low shear area. The main contributions are: (i) a retrospective analysis of six aneurysms with known rupture sites, validated against particle image velocimetry measurements, (ii) a numerical evaluation of wall shear stress using different finite element spaces and introducing a novel boundary-flux assessment method, (iii) the development of denoising techniques for magnetic resonance imaging velocity acquisitions, which could be employed in future studies to improve the accuracy and reliability of patient-specific simulations. This work advances computational hemodynamics and medical imaging, offering potential benefits for future clinical applications.