Optimized FDA Blood Pump: A Case Study in System-Level Customized Ventricular Assist Device Designs.

Authors

Canberk Yıldırım, Kağan Uçak, Ali Madayen, Tansu Gölcez, Hakan Ertürk, Özgür Uğraş Baran, Kerem Pekkan

Published in

Annals of biomedical engineering. Sep 09, 2025. Epub Sep 09, 2025.

Abstract

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.

PMID:
40926069
Bibliographic data and abstract were imported from PubMed on 10 Sep 2025.

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