These slides were presented at the NAFEMS World Congress 2025, held in Salzburg, Austria from May 19–22, 2025.

Abstract

Biomedical multiphysics applications like the Fluid-Structure Interaction (FSI) simulation of cerebral aneurysm pose a challenging task. Cerebral aneurysms are present in about 2-5% of the general population. The primary risk they pose is rupture, which can lead to subarachnoid hemorrhage, a condition associated with high levels of mortality and morbidity. Numerous studies have highlighted various medical, genetic, morphological, and fluid dynamic factors that influence the initiation, growth, and rupture of aneurysms. Treating aneurysms requires highly invasive procedures, which carry risks of complications. Therefore, it is crucial to make informed decisions regarding whether an aneurysm necessitates treatment, based on its proximity to rupture. Simulations can be a useful tool to support the decision-making process. Numerous studies utilizing computational fluid dynamics (CFD) have shown differences between ruptured and unruptured aneurysms in their fluid dynamic behavior. These phenomena serve as mechanical stimuli that are converted into biological signals, potentially leading to aneurysm growth and rupture. However, the geometry of the aneurysm influences these fluid dynamic parameters. Thus, the change in shape due to deformation of the soft tissue has to be considered also under certain circumstances. In literature, there are only a few computational studies focusing on structural mechanics of cerebral aneurysms. With the presented Fluid-Structure Interaction methodology we are not only able to assess the fluid dynamic behavior of soft tissues like cerebral aneurysms, but we can also assess structural mechanical phenomena in the blood vessel wall. With this we can understand the interaction of fluid mechanics and structural mechanics of aneurysms in more detail. With the automation of simulations of many cerebral aneurysms, it is possible to generate parameters and evaluate them statistically. With the help of univariate and multivariate regression analysis (General Linear Method, GLM) it is possible to derive regression functions, which can help assess the rupture risk of aneurysms, by considering geometry, fluid dynamic as well as structural mechanical parameters. This approach can help neurosurgeons in their decision making regarding the necessity of operative aneurysm treatment.