Finite Element Modeling of Endovascular Intervention Enables Hemodynamic Characterization of Intracranial Aneurysm Treatment Strategies
Damiano, Robert J.
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Intracranial aneurysms (IAs) are localized dilations in cerebral blood vessels which occur in up to roughly 5% of the general population. Conventional aneurysm treatment strategies like surgical clipping are invasive, lengthy, and risky. On the other hand, endovascular interventions like coiling are minimally-invasive and have been successfully used as an alternative to surgical clipping. Recently, flow diversion has emerged as a novel endovascular strategy to treat previously difficult-to-treat IAs. Despite their high clinical success rates, post-treatment complications such as aneurysm recurrence in coiled IAs and incomplete occlusion or delayed rupture in flow diverter (FD)-treated IAs have been reported in the literature. Since endovascular devices work primarily by modifying aneurysmal flow, treatment outcomes likely depend on the specific device(s) and intervention strategy used for each patient-specific case. Therefore, assessment of the effects of endovascular devices on post-treatment hemodynamics could be crucial in understanding the mechanisms by which specific treatment strategies affect treatment outcomes. This work focused on finite element modeling of coils and flow diverters as well as their deployment, which enabled a robust means of simulating post-treatment hemodynamics in patient-specific aneurysms via computational fluid dynamics (CFD). In Chapter 2, a new finite element method (FEM)-based coiling technique is introduced as well as an efficient deployment strategy for overlapping FDs using the previously established high fidelity virtual stenting method (HiFiVS) for FDs. In Chapter 3, these modeling strategies were used to investigate four endovascular treatment strategies in a patient-specific IA: coiling (1-8 coils), single FD, FD with adjunctive coils (1-8 coils), and overlapping FDs. Post-treatment hemodynamics was simulated via CFD and qualitative and quantitative flow characteristics were analyzed. In Chapter 4, three patient-specific clinical FD intervention cases were recapitulated in silico and their post-treatment hemodynamics were analyzed and compared with the real clinical outcomes. The results of these studies elucidate new insights to the effects of coiling and flow diversion on post-treatment hemodynamics. In addition, our findings highlight the potential for virtual intervention, in conjunction with CFD, to be used as a tool in treatment planning. These tools could help asses, before treatment, the impact of various intervention strategies for each patient-specific case, in hopes of improving treatment outcomes.