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Trial-Based Hemolysis Modeling to Investigate Operating Modes of Continuous-Flow LVADs.

Patrick Borchers1, Steffen Leonhardt1, Marian Walter1

  • 1Chair for Medical Information Technology, Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany.

Artificial Organs
|October 13, 2025
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Summary

This study introduces a new, computationally efficient method to predict hemolysis in left ventricular assist devices (LVADs). The trial-based model helps optimize LVAD operation for reduced blood damage and enables online hemolysis prediction.

Keywords:
Lagrangian approachSputnik1axial‐flow pumphemolysis modelingin vitro trialsleft ventricular assist devicemodel identificationpower law modelspeed modulation

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Area of Science:

  • Biomedical Engineering
  • Cardiovascular Devices
  • Hemolysis Modeling

Background:

  • Computational fluid dynamics (CFD) for LVAD hemolysis prediction is computationally expensive.
  • Existing methods limit exploration of operating conditions and online prediction.
  • A CFD-free, trial-based approach is needed for online hemolysis modeling in LVADs.

Purpose of the Study:

  • To develop a CFD-free, trial-based methodology for online hemolysis prediction in continuous-flow LVADs.
  • To create a modified power law model for assessing LVAD operating modes and patient conditions.
  • To enable selection of low-hemolysis treatment strategies.

Main Methods:

  • A modified power law model was developed using LVAD hemolysis trial data.
  • The Lagrangian approach was used to model dynamic behavior.
  • The model was applied to the Sputnik1 LVAD and integrated with a cardiovascular system model.

Main Results:

  • The modified power law model showed good fit (R²=0.69) with low error (<0.7%) from the Lagrangian approach.
  • For the Sputnik1 LVAD, lower hemolysis was observed with reduced speed, systemic resistance, and left ventricular contractility.
  • Speed modulation generally increased hemolysis across various profiles.

Conclusions:

  • The proposed model effectively assesses LVAD operating modes and patient conditions for low-hemolysis strategies.
  • For Sputnik1 patients, maintaining low pump speed and systemic resistance is recommended.
  • Integrating the model with online flow sensing can enable real-time hemolysis prediction.