Nguyen, Thien-Tam

Abstract Brain arteriovenous malformations (AVMs) result from abnormal growth of vascular structures. AVMs pose a significant rupture risk, and its treatment is challenging due to the complex hemodynamics within the tangled nidus. Currently, investigating AVM hemodynamics remains a challenge due to the low resolution of clinical imaging modalities. In this study, a high-fidelity Computational Fluid Dynamics (CFD) simulation of a brain AVM from a KRAS-mutated mouse model is developed from micro-CT images. Brain AVMs were induced in mice through systemic delivery of AAV-BR1-CAG vector encoding KRASG12V-GFP transgene to cerebral endothelial cells. High-resolution microCT imaging at 6.551 𝜇𝑚 pixel size captured the complex vascular anatomy. The cerebral arteries were reconstructed using the 3D Slicer and Blender software. The curvilinear immersed boundary (CURVIB) method was employed with approximately 65 million grid points and spatial resolution of 0.7−2.3 𝜇𝑚. Our preliminary results reveal heterogeneous flow distribution through the nidus, with blood channeling through two primary pathways. The extremely low Reynolds number (0.038) indicates viscous-dominated flow characteristic of microcirculation. Our work presents the first high-resolution CFD simulation of brain AVM in the literature, providing a foundation for investigating flow-mediated vascular remodeling, rupture risk assessment, and therapeutic intervention planning in future.