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Updated: Jun 1, 2026

A Microfluidic Flow Chamber Model for Platelet Transfusion and Hemostasis Measures Platelet Deposition and Fibrin Formation in Real-time
Published on: February 14, 2017
Blood coagulation dynamics: mathematical modeling and stability results.
Adélia Sequeira1, Rafael F Santos, Tomás Bodnár
1Department of Mathematics and CEMAT/IST, Instituto Superior Tecnico, Technical University of Lisbon, Lisboa, Portugal. adelia.sequeira@math.ist.utl.pt
This study revisits a mathematical model of blood coagulation and fibrinolysis, integrating biochemical, physiologic, and rheological factors. Numerical simulations in a stenosed vessel provide insights into clot formation and stability.
Area of Science:
- Biophysics
- Biochemistry
- Physiology
Background:
- The hemostatic system maintains blood fluidity but can initiate clot formation upon injury.
- Tissue Factor (TF) triggers the coagulation cascade, leading to clot formation, growth, and lysis.
- Existing mathematical models lack rigor and comprehensive experimental data integration.
Purpose of the Study:
- To revisit and refine a mathematical model of coagulation and fibrinolysis in flowing blood.
- To integrate biochemical, physiological, and rheological factors into a comprehensive model.
- To simulate clot formation and growth in an idealized stenosed blood vessel.
Main Methods:
- Development and application of a mathematical model for coagulation and fibrinolysis.
- Three-dimensional numerical simulations in a stenosed blood vessel model.
- Analysis of clot formation, growth, and stability using computational methods.
Main Results:
- The model integrates key biochemical, physiological, and rheological aspects of hemostasis.
- Numerical simulations demonstrate clot formation and growth dynamics in a stenosed vessel.
- Stability analysis was performed for a simplified clot model in quiescent plasma.
Conclusions:
- The revisited mathematical model offers a more comprehensive approach to studying blood coagulation.
- Numerical simulations provide valuable insights into the complex process of clot formation in flow.
- Further development is needed for models that fully integrate experimental data for enhanced predictive power.
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