A model of fluid-structure and biochemical interactions for applications to subclinical leaflet thrombosis

Aaron Barrett1, Jordan A Brown2, Margaret Anne Smith2

  • 1Department of Mathematics, University of Utah, Salt Lake City, Utah, USA.

Insights

Subclinical leaflet thrombosis (SLT) simulation models can now predict clot formation on bioprosthetic aortic valves. This advancement aids in understanding thrombosis mechanisms and preventing strokes after valve replacement.

Area of Science:

  • Biomedical Engineering
  • Cardiovascular Research
  • Computational Fluid Dynamics

Background:

  • Subclinical leaflet thrombosis (SLT) is a complication of bioprosthetic aortic valve replacement, increasing stroke risk and potentially causing valve deterioration.
  • Clinical imaging of SLT is challenging, necessitating advanced modeling techniques to understand its mechanisms and predict patient risk.

Purpose of the Study:

  • To develop and validate a computational model for simulating leaflet thrombosis in bioprosthetic aortic valves.
  • To incorporate fluid-structure interaction and a simplified thrombosis model to capture clot deposition on moving leaflets.

Main Methods:

  • Developed a simulation model combining fluid-structure interaction with a simplified thrombosis model for clot deposition on moving leaflets.
  • Adapted the model for deposition/absorption on other moving boundaries.
  • Presented convergence results and quantified the model's impact on valve opening and pressures.

Main Results:

  • The model successfully simulates leaflet thrombosis by incorporating surface adhesion and fluid-structure interaction feedback.
  • Demonstrated the model's ability to quantify changes in valve mechanics and hemodynamics due to thrombosis.
  • Validated the model's convergence and predictive capabilities.

Conclusions:

  • The developed modeling approach represents a significant advancement in simulating thrombosis on moving boundaries, particularly for bioprosthetic heart valves.
  • This tool can aid in understanding SLT mechanisms, predicting patient risk, and potentially improving bioprosthetic valve design and patient management.
  • The model's adaptability extends its utility to other applications involving deposition or absorption on dynamic surfaces.

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