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An accelerated thrombosis model for computational fluid dynamics simulations in rotary blood pumps

Christopher Blum, Sascha Groß-Hardt, Ulrich Steinseifer, Michael Neidlin
doi: https://doi.org/10.1101/2021.08.30.458209
Christopher Blum
aDepartment of Cardiovascular Engineering, Institute of Applied Medical Engineering, Medical Faculty, RWTH Aachen University, Aachen, Germany
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Sascha Groß-Hardt
benmodes GmbH, Aachen, Germany
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Ulrich Steinseifer
aDepartment of Cardiovascular Engineering, Institute of Applied Medical Engineering, Medical Faculty, RWTH Aachen University, Aachen, Germany
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Michael Neidlin
aDepartment of Cardiovascular Engineering, Institute of Applied Medical Engineering, Medical Faculty, RWTH Aachen University, Aachen, Germany
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  • For correspondence: neidlin@ame.rwth-aachen.de
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Abstract

Purpose Thrombosis is one of the major complications in blood-carrying medical devices and a better understanding to influence design of such devices is desirable. Over the past years many computational models of thrombosis have been developed. However, open questions remain about the applicability and implementation within a pump development process. The aim of the study was to develop and test a computationally efficient model for thrombus risk prediction in rotary blood pumps.

Methods We used a two-stage approach to calculate thrombus risk. At the first stage, the velocity and pressure fields were computed by computational fluid dynamic (CFD) simulations. At the second stage, platelet activation by mechanical and chemical stimuli was determined through species transport with an Eulerian approach. The model was implemented in ANSYS CFX and compared with existing clinical data on thrombus deposition within the HeartMate II.

Results Our model shows good correlation (R2>0.94) with clinical data and identifies the bearing and outlet stator region of the HeartMate II as the location most prone to thrombus formation. The calculation of platelet activation requires an additional 10-20 core hours of computation time.

Discussion The concentration of activated platelets can be used as a surrogate marker to determine risk regions of thrombus deposition in a blood pump. Model expansion, e.g. by including more chemical species can easily be performed. We make our model openly available by implementing it for the FDA benchmark blood pump.

Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Open access funding enabled and organized by Projekt DEAL.

Conflict of interest All of the authors have nothing to disclose.

Availability of data and material The raw data can be retrieved by request from the authors.

Code availability The implementation of the thrombus model in the FDA benchmark blood pump geometry is available on https://doi.org/10.5281/zenodo.5116063.

Authors’ contributions All authors contributed to the study conception and design. CB developed the numerical model, performed the simulations, gathered, analysed and discussed the results. SGH, MN and US were involved in the analysis and discussion of the results. MN supervised the project. MN and CB wrote the manuscript based on the input of all co-authors. All co-authors read and approved the final version of the manuscript.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://doi.org/10.5281/zenodo.5116063

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted September 01, 2021.
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An accelerated thrombosis model for computational fluid dynamics simulations in rotary blood pumps
Christopher Blum, Sascha Groß-Hardt, Ulrich Steinseifer, Michael Neidlin
bioRxiv 2021.08.30.458209; doi: https://doi.org/10.1101/2021.08.30.458209
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An accelerated thrombosis model for computational fluid dynamics simulations in rotary blood pumps
Christopher Blum, Sascha Groß-Hardt, Ulrich Steinseifer, Michael Neidlin
bioRxiv 2021.08.30.458209; doi: https://doi.org/10.1101/2021.08.30.458209

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