Yıldırım Canberk, Uçak Kağan, Madayen Ali, Gölcez Tansu, Ertürk Hakan, Baran Özgür Uğraş, Pekkan Kerem
Department of Biomedical Engineering, Koc University, 34060, Istanbul, Turkey.
Department of Mechanical Engineering, Koc University, Rumeli Feneri Campus, Sarıyer, 34450, Istanbul, Turkey.
Ann Biomed Eng. 2025 Sep 9. doi: 10.1007/s10439-025-03834-8.
The design and development of ventricular assist devices have heavily relied on computational tools, particularly computational fluid dynamics (CFD), since the early 2000s. However, traditional CFD-based optimization requires costly trial-and-error approaches involving multiple design cycles. This study aims to propose a more efficient VAD design and optimization framework that overcomes these limitations.
We developed a system- and component-level ventricle assist device optimization approach by coupling a lumped parameter cardiovascular physiology model with parametric turbomachinery, volute design, and blade path generation packages. The framework incorporates pump hydrodynamic losses and is validated against experimental data from six distinct blood pump designs and CFD simulations. The optimization framework allows for the specification of both physiology-related and device-related objective functions to generate optimized blood pump configurations over a large parameter space.
The optimization was applied to the U.S. Food and Drug Administration (FDA) benchmark blood pump as the baseline design. Results showed that an optimized FDA pump, maintaining the same cardiac output and aortic pressure, achieved a ~ 32% reduction in blade tip velocity compared to the baseline, resulting in an ~ 88% reduction in hemolysis. Additionally, an alternative design with a 40% reduction in blood-wetted area was generated while preserving the baseline pressure and flow.
The proposed optimization framework improves device development efficiency by shortening the design cycle and enabling hydrodynamically optimized pumps that perform well across diverse patient hemodynamics. The optimized pump designs are available as open-source resources for further research and development.
自21世纪初以来，心室辅助装置的设计与开发在很大程度上依赖于计算工具，尤其是计算流体动力学（CFD）。然而，传统的基于CFD的优化需要涉及多个设计周期的昂贵试错方法。本研究旨在提出一种更高效的心室辅助装置设计与优化框架，以克服这些局限性。
我们通过将集总参数心血管生理模型与参数化涡轮机械、蜗壳设计和叶片路径生成软件包相结合，开发了一种系统级和组件级的心室辅助装置优化方法。该框架纳入了泵的水力损失，并根据六种不同血泵设计的实验数据和CFD模拟进行了验证。该优化框架允许指定与生理相关和与装置相关的目标函数，以在大参数空间内生成优化的血泵配置。
该优化应用于美国食品药品监督管理局（FDA）的基准血泵作为基线设计。结果表明，优化后的FDA泵在维持相同心输出量和主动脉压力的情况下，与基线相比，叶片尖端速度降低了约32%，溶血减少了约88%。此外，还生成了一种替代设计，其血液接触面积减少了40%，同时保持了基线压力和流量。
所提出的优化框架通过缩短设计周期和实现跨不同患者血流动力学表现良好的流体动力学优化泵，提高了装置开发效率。优化后的泵设计作为开源资源可供进一步研发使用。
