Evidence map›Paper›PMID 40926069›Full record

ArticleAnnals of biomedical engineering2025

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

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

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Article in Annals of biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Canberk Yıldırım *Department of Biomedical Engineering, Koc University, 34060, Istanbul, Turkey.
Kağan Uçak *Department of Mechanical Engineering, Koc University, Rumeli Feneri Campus, Sarıyer, 34450, Istanbul, Turkey.
Ali Madayen *Department of Mechanical Engineering, Middle East Technical University, 06800, Ankara, Turkey.
Tansu Gölcez *Department of Biomedical Engineering, Koc University, 34060, Istanbul, Turkey.
Hakan ErtürkDepartment of Mechanical Engineering, Bogazici University, 34342, Istanbul, Turkey.
Özgür Uğraş BaranDepartment of Mechanical Engineering, Middle East Technical University, 06800, Ankara, Turkey.
Kerem Pekkan *Department of Mechanical Engineering, Koc University, Rumeli Feneri Campus, Sarıyer, 34450, Istanbul, Turkey. kpekkan@ku.edu.tr.ORCID http://orcid.org/0000-0001-7637-4445

Funding

HORIZON EUROPE European Innovation Council HeartWise 101214454
6 · The paper itself

Abstract

purposeThe 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.

methodsWe 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.

resultsThe 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.

conclusionThe 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.

Indexed as

Heart-Assist DevicesModels, CardiovascularProsthesis DesignHumansHydrodynamicsUnited StatesUnited States Food and Drug AdministrationBenchmark devicesCardiovascular engineeringComputational fluid dynamicsFDA blood pumpLumped parameter modelingOptimizationVentricle assist devices

Identifiers

PMID40926069
PMCPMC12575595

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.