Development of a parallel multiscale 3D model for thrombus growth under flow

Abstract

Thrombus growth is a complex and multiscale process involving interactions spanning length scales from individual micron-sized platelets to macroscopic clots at the millimeter scale. Here, we describe a 3D multiscale framework to simulate thrombus growth under flow comprising four individually parallelized and coupled modules: a data-driven Neural Network (NN) that accounts for platelet calcium signaling, a Lattice Kinetic Monte Carlo (LKMC) simulation for tracking platelet positions, a Finite Volume Method (FVM) simulator for solving convection-diffusion-reaction equations describing agonist release and transport, and a Lattice Boltzmann (LB) flow solver for computing the blood flow field over the growing thrombus. Parallelization was achieved by developing in-house parallel routines for NN and LKMC, while the open-source libraries OpenFOAM and Palabos were used for FVM and LB, respectively. Importantly, the parallel LKMC solver utilizes particle-based parallel decomposition allowing efficient use of cores over highly heterogeneous regions of the domain. The parallelized model was validated against a reference serial version for accuracy, demonstrating comparable results for both microfluidic and stenotic arterial clotting conditions. Moreover, the parallelized framework was shown to scale essentially linearly on up to 64 cores. Overall, the parallelized multiscale framework described here is demonstrated to be a promising approach for studying single-platelet resolved thrombosis at length scales that are sufficiently large to directly simulate coronary blood vessels.