Simulating Initial Steps of Platelet Aggregate Formation in a Cellular Blood Flow Environment
| Authors |
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| Publication date | 2023 |
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| Book title | Computational Science – ICCS 2023 |
| Book subtitle | 23rd International Conference, Prague, Czech Republic, July 3–5, 2023 : proceedings |
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| ISBN (electronic) |
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| Series | Lecture Notes in Computer Science |
| Event | 23rd International Conference on Computational Science, ICCS 2023 |
| Volume | Issue number | III |
| Pages (from-to) | 323-336 |
| Publisher | Cham: Springer |
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| Abstract |
The mechano-chemical process of clot formation is relevant in both hemostasis and thrombosis. The initial phase of thrombus formation in arterial thrombosis can be described by the mechanical process of platelet adhesion and aggregation via hemodynamic interactions with von Willebrand factor molecules. Understanding the formation and composition of this initial blood clot is crucial to evaluate differentiating factors between hemostasis and thrombosis. In this work a cell-based platelet adhesion and aggregation model is presented to study the initial steps of aggregate formation. Its implementation upon the pre-existing cellular blood flow model HemoCell is explained in detail and the model is tested in a simple case study of initial aggregate formation under arterial flow conditions. The model is based on a simplified constraint-dependent platelet binding process that coarse-grains the most influential processes into a reduced number of probabilistic thresholds. In contrast to existing computational platelet binding models, the present method places the focus on the mechanical environment that enables the formation of the initial aggregate. Recent studies highlighted the importance of elongational flows on von Willebrand factor-mediated platelet adhesion and aggregation. The cell-resolved scale used for this model allows to account for important hemodynamic phenomena such as the formation of a red blood cell free layer and platelet margination. This work focuses on the implementation details of the model and presents its characteristic behavior at various coarse-grained threshold values.
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| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.1007/978-3-031-36024-4_26 |
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