A new open-source solver for early detection of atherosclerosis based on hemodynamics and LDL transport simulation

This article presents a new open-source solver within the OpenFOAM framework, to provide a cost-free alternative to commercial software for simulating blood flows and the transport of low-density lipoproteins (LDL) in arteries. The proposed algorithm utilizes the velocity field obtained from the hemodynamics computation to solve an advection-diffusion equation governing a passive scalar variable, that represents the cholesterol concentration in blood. Moreover, two customized boundary conditions, namely periodic pulsatile inflow and LDL blood-to-wall transfer law, as well as a non-Newtonian viscosity model, are included in the code to achieve more realistic results. The solver is first validated by reproducing two benchmark tests, the classical lid-driven cavity experiment including heat transport, and a constricted tube simulating a stenosed artery. The results obtained were in good agreement with existing literature and experimental measurements, thus confirming the accuracy and robustness of the proposed open-source solver. Finally, hemodynamics and LDL transport are computed in two arteries, one of them obtained by segmentation from an anonymized clinical patient. Stress and LDL concentration at the vessel's wall are employed to calculate significant descriptors revealing dangerous areas where atherosclerotic plaques could emerge. In the studied cases, the main branch of the artery, and especially the vicinity of the bifurcation, seem to be candidates to develop the illness. This conclusion is in line with medical in-vivo studies evincing that bifurcations are an usual place where plaques grow. This research introduces a freely available solver within the OpenFOAM platform, as an alternative to commercial software, for the simulation of blood flow and LDL transport through arteries. The model employs the velocity data obtained from the blood flow computation to solve an advection-diffusion equation for a passive scalar representing the cholesterol concentration. Patient-specific analyses can be performed with this tool to determine vessels at high risk of developing atherosclerotic plaques. image