A simplified mesoscale 3D model for characterizing fibrinolysis under flow conditions Article Swipe
Rémy Petkantchin
,
Alexandre Rousseau
,
Omer Eker
,
Karim Zouaoui Boudjeltia
,
Franck Raynaud
,
Bastien Chopard
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.05.09.539942
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.05.09.539942
One of the routine clinical treatments to eliminate ischemic stroke thrombi is injecting a biochemical product into the patient’s bloodstream, which breaks down the thrombi’s fibrin fibers: intravenous or intravascular thrombolysis. However, this procedure is not without risk for the patient; the worst circumstances can cause a brain hemorrhage or embolism that can be fatal. Improvement in patient management drastically reduced these risks, and patients who benefited from thrombolysis soon after the onset of the stroke have a significantly better 3-month prognosis, but treatment success is highly variable. The causes of this variability remain unclear, and it is likely that some fundamental aspects still require thorough investigations. For that reason, we conducted in vitro flow-driven fibrinolysis experiments to study pure fibrin thrombi breakdown in controlled conditions and observed that the lysis front evolved non-linearly in time. To understand these results, we developed an analytical 1D lysis model in which the thrombus is considered a porous medium. The lytic cascade is reduced to a second-order reaction involving fibrin and a surrogate pro-fibrinolytic agent. The model was able to reproduce the observed lysis evolution under the assumptions of constant fluid velocity and lysis occurring only at the front. For adding complexity, such as clot heterogeneity or complex flow conditions, we propose a 3-dimensional mesoscopic numerical model of blood flow and fibrinolysis, which validates the analytical model’s results. Such a numerical model could help us better understand the spatial evolution of the thrombi breakdown, extract the most relevant physiological parameters to lysis efficiency, and possibly explain the failure of the clinical treatment. These findings suggest that even though real-world fibrinolysis is a complex biological process, a simplified model can recover the main features of lysis evolution.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.05.09.539942
- https://www.biorxiv.org/content/biorxiv/early/2023/05/24/2023.05.09.539942.full.pdf
- OA Status
- green
- References
- 64
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4376108516
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4376108516Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2023.05.09.539942Digital Object Identifier
- Title
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A simplified mesoscale 3D model for characterizing fibrinolysis under flow conditionsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-05-09Full publication date if available
- Authors
-
Rémy Petkantchin, Alexandre Rousseau, Omer Eker, Karim Zouaoui Boudjeltia, Franck Raynaud, Bastien ChopardList of authors in order
- Landing page
-
https://doi.org/10.1101/2023.05.09.539942Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2023/05/24/2023.05.09.539942.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2023/05/24/2023.05.09.539942.full.pdfDirect OA link when available
- Concepts
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Fibrinolysis, Thrombolysis, Lysis, Thrombus, Fibrin, Coagulation, Choke, Medicine, Cardiology, Stroke (engine), Intensive care medicine, Internal medicine, Mechanics, Physics, Immunology, Myocardial infarction, Quantum mechanics, ThermodynamicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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64Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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