动脉瘤
主动脉
腔内修复术
印章(徽章)
计算流体力学
支架
地质学
放射科
机械
医学
外科
腹主动脉瘤
物理
艺术
视觉艺术
作者
Willa Li,Žiga Donik,Seth Sankary,Nguyen T. Nguyen,Sanjeev Dhara,Janez Kramberger,Kathleen D. Cao,Nhung Nguyen,Luka Pocivavsek
标识
DOI:10.1016/j.bpj.2022.11.2843
摘要
Aortic aneurysms are pathological dilations of the aorta due to a weakened vessel wall that can quickly become fatal if ruptured. One option for surgical intervention is to perform endovascular aneurysm repair (EVAR) which consists of deploying an expandable endograft across the aneurysm so that blood is redirected through the lumen of the endograft rather than permitted to flow into the aneurysmal sac to cause further pressurization and dilation. The endograft relies upon non-surgical adhesion to the aortic wall at its seal zone to fix the device in place. While EVAR has shown favorable short-term outcomes, long-term durability is impaired due to instability at the seal zone. Specifically, endoleaks often develop in the gap between the undersurface of the stent graft and the vessel wall--termed the bird-beak region--and are clinically presumed to be due to a mismatch between the geometry of the aorta and the endograft. However, we currently lack a rigorous biomechanical understanding of how this geometric incompatibility contributes to endoleak formation and propagation. To investigate the stability of seal zone mechanics, we simulated endograft deployment in computational models of idealized aortic models with different degrees of curvature to replicate bird-beak regions of various sizes. We will then perform computational fluid dynamics (CFD) analyses to characterize the fluid behavior and pressure profile at the seal zone as a function of increasing bird-beak size. These first steps will form the foundation for our future studies where we aim to couple CFD with fluid-structure-fracture simulations to more robustly model the mechanics of endoleaks. By harnessing the power of computational methods, our project seeks to deepen our biomechanical understanding of how endograft selection may affect device failure rates in EVAR patients.
科研通智能强力驱动
Strongly Powered by AbleSci AI