Fan Tingting, Wang Jinhang, Wang Xu, Chen Xi, Zhao Dongliang, Xie Fengjie, Chen Guangxin
School of Biomedical Engineering, Capital Medical University, Beijing, China.
Beijing Institute of Heart, Lung, and Blood Vessel Diseases, Beijing, China.
Front Bioeng Biotechnol. 2025 Jun 3;13:1602190. doi: 10.3389/fbioe.2025.1602190. eCollection 2025.
Aneurysm, as life-threatening vascular pathologies, are significantly influenced by hemodynamic factors in their development. The combine of numerical simulation and experiment have laid the foundation for high-precision hemodynamic analysis, while the integration of deep learning technologies has significantly enhanced computational efficiency. However, current researches still face challenges such as limitations in biomimetic materials, and incomplete understanding of mechano-biological coupling mechanisms. In this review, we systematize traditional and emerging methodologies characterizing hemodynamic perturbations across the pathophysiological continuum of aneurysmal expansion, rupture, and thrombosis progression. This review aims to (1) elucidate mechanistic underpinnings of aneurysm destabilization, (2) inspire people to establish standardized quantification protocols for hemodynamic analysis, and (3) pave the way for patient-specific risk stratification enabling data-driven clinical interventions.
动脉瘤作为危及生命的血管病变，其发展受到血流动力学因素的显著影响。数值模拟与实验的结合为高精度血流动力学分析奠定了基础，而深度学习技术的整合则显著提高了计算效率。然而，目前的研究仍面临诸如仿生材料的局限性以及对机械生物学耦合机制理解不完整等挑战。在这篇综述中，我们系统地梳理了传统和新兴方法，这些方法描绘了动脉瘤扩张、破裂和血栓形成进展的病理生理连续过程中的血流动力学扰动。本综述旨在：（1）阐明动脉瘤失稳的机制基础；（2）激发人们建立血流动力学分析的标准化量化方案；（3）为基于数据驱动的临床干预实现患者特异性风险分层铺平道路。
