Efficient multi-fidelity computation of blood coagulation under flow

• DOI: 10.1371/journal.pcbi.1011583
• Publication Date: 2023-10-27T17:30:39Z
• Authors: Manuel Guerrero-H...; Manuel Garcia-Vil...; Alejandro Gonzalo; Pablo Martinez-Le...; Andrew M. Kahn; Elliot McVeigh; Javier Bermejo; Juan C. del Alamo; Oscar Flores
• Keywords: Fibrin; QH301-705.5; Medicina; Thrombin; Thrombosis; Blood flow; Serine proteases; Simulation and modeling; Aeronáutica; Blood; Humans; Biology (General); Aneurysms; Reaction kinetics; Blood Coagulation; Biología y Biomedicina; Research Article

Clot formation is a crucial process that prevents bleeding, but can lead to severe disorders when imbalanced. This regulated by the coagulation cascade, biochemical network controls enzyme thrombin, which converts soluble fibrinogen into fibrin fibers constitute clots. Coagulation cascade models are typically complex and involve dozens of partial differential equations (PDEs) representing various chemical species’ transport, reaction kinetics, diffusion. Solving these PDE systems computationally challenging, due their large size multi-scale nature. We propose multi-fidelity strategy increase efficiency simulations. Leveraging slower dynamics molecular diffusion, we transform governing PDEs ordinary (ODEs) evolution species concentrations versus blood residence time. then Taylor-expand ODE solution around zero-diffusivity limit obtain spatiotemporal maps in terms statistical moments time, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="M1"><mml:mover accent="true"><mml:msubsup><mml:mi>t</mml:mi> <mml:mi>R</mml:mi> <mml:mi>p</mml:mi></mml:msubsup> <mml:mo>¯</mml:mo></mml:mover></mml:math> , provide for id="M2"><mml:mover . replaces high-fidelity system N ODEs p time moments. The order ( ) allows balancing accuracy computational cost providing speedup over / compared models. Moreover, this becomes independent number meshes typical arterial cardiac chamber Using with = 9 an idealized aneurysm geometry pulsatile flow as benchmark, demonstrate favorable low-order 1 2. thrombin concentration departs from under 20% 1) 2% 2) after 20 cycles. These could enable new analyses scenarios extensive networks. Furthermore, it be generalized advance our understanding other reacting affected flow.