Atherosclerosis is the main cause of mortality and morbidity in the western world. Atherosclerosis is a chronic disease defined by life-long processes, with multiple actors playing a role at different biological and time scales. Patient-specific in silico models and simulations can help to understand better the mechanisms of atherosclerosis formation, potentially improving patient management. A conceptual and computational multiscale framework for the modelling of atherosclerosis formation at its early stage was created from the integration of a fluid mechanics model and a biochemical model. The fluid mechanics model describes the interaction between arterial endothelium and blood flow using an artery-specific approach. The low density lipoprotein (LDL) oxidation and consequent immune reaction leading to chronic inflammatory process at the basis of plaque formation was described in the biochemical model. The integration of these modelling approaches led to the creation of a computational framework, an effective tool for the modelling of atherosclerosis plaque development. The model presented in this study was able to capture key features of atherogenesis such as the location of pro-atherogenic areas and to reproduce the formation of plaques detectable from in vivo observations. This framework is being currently tested at University College Hospital (UCH).
Di Tomaso, G., Pichardo-Almarza, C., Agu, O., & Díaz-Zuccarini, V. (2015). A multiscale and Patient-specific computational framework of atherosclerosis formation and progression: A case study in the aorta and peripheral arteries. In Procedia Computer Science (Vol. 51, pp. 1118–1127). Elsevier B.V. https://doi.org/10.1016/j.procs.2015.05.281