Speaker
Description
Cerebral aneurysms (CAs), saccular dilations in the cerebral arteries affecting 3.2\% of the world's population, are a leading cause of stroke. Prone to rupture, they often cause subarachnoid bleeding, resulting in high mortality and severe disability. Endovascular coiling, a minimally invasive procedure, prevents rupture by altering blood flow and triggering clot formation within the aneurysm. Despite its widespread use, coiling can fail, leading to aneurysm recurrence.
To better understand treatment outcomes, we develop a mathematical model to simulate thrombosis growth in coiled aneurysms in silico. Using our discrete-elastic rod (DER) model, patient-specific aneurysms are virtually embolized with coils, capturing their physical properties like natural curvature and flexibility. Blood flow dynamics are simulated via the lattice Boltzmann method in the parallelizable framework waLBerla, incorporating the non-Newtonian behavior of blood through the Carreau-Yasuda model and dynamic inflow conditions from a 1D arterial model.
Clot formation is modeled using advection-diffusion-reaction equations to transport clotting factors and platelets. A simplified coagulation cascade reduces model complexity and addresses parameter uncertainties. Clotting occurs near walls when concentration and shear-rate thresholds are met. The resulting thrombus, represented as a porosity field, integrates into the simulation via volume-averaged Navier-Stokes equations (VANSE), which impose resistance on blood flow.
Virtual angiography evaluates clot effectiveness, with outcomes classified using the \linebreak Raymond-Roy occlusion grading scale to predict long-term treatment success and aneurysm recurrence. Our work offers insights into the interplay between coil placement, blood flow, and thrombus formation, advancing endovascular treatment strategies.
