Multiphysics and multiscale modeling of microthrombosis in COVID-19

Area of Science:

• Biomedical Engineering
• Computational Biology
• Hematology

Background:

• Microvascular thrombosis is a critical factor in Coronavirus disease 2019 (COVID-19) progression.
• Limited access to patient blood samples hinders in vitro research on SARS-CoV-2 related thrombosis.
• Understanding the mechanisms of COVID-19 associated thrombosis is crucial for developing effective treatments.

Purpose of the Study:

• To develop and utilize a novel computational framework for predictive modeling of pathological thrombus formation in COVID-19 microvasculature.
• To quantify the contributions of various prothrombotic factors implicated in COVID-19.
• To identify potential therapeutic targets for anti-thrombotic treatment in COVID-19 patients.

Main Methods:

• Employed a multiscale and multiphysics computational framework integrating hemodynamics, coagulation factor transport and kinetics, and blood cell mechanics.
• Simulated pathological thrombus formation in microvasculature using data from COVID-19 patients.
• Analyzed the roles of stasis, coagulation factor levels, and inflammatory responses in microthrombus development.

Main Results:

• Antithrombin and factor V were identified as key coagulation factors promoting thrombosis in COVID-19.
• Recruitment of white blood cells (WBCs) to endothelial cells significantly exacerbates thrombogenesis and blood flow blockage.
• Observed flowing blood cell clusters may originate from detached WBCs, potentially forming new clots.

Conclusions:

• The study highlights antithrombin, factor V, and WBC recruitment as critical elements in COVID-19 microvascular thrombosis.
• Findings suggest potential targets for prioritizing anti-thrombotic therapies in COVID-19 management.
• The developed computational framework offers a powerful tool for understanding thrombosis mechanisms and informing therapeutic strategies.