1. Nenad Filipović, Univerzitet u Kragujevcu, Serbia
Atherosclerosis is an inflammatory disease that is characterized by the accumulation of lipids and formation of plaque within the arterial wall. This process develops in arterial walls with discrete nature between cells, molecular biomarkers, which indicate that discrete modelling approach like Agent Based Model (ABM) can be used for simulation of complex process for plaque development.
The US images obtained during clinical examination for a set of patients are annotated by the clinical experts and used to train a convolutional neural network. Afterwards, for a particular patient, the collection of longitudinal and transversal US images is imported into the deep learning module and the 3D reconstruction module to create the patient-specific geometry. Blood flow through a curve blood vessel with stenosis was modeled using 3D finite element method (FEM). Fluid dynamics computation is performed by PAK solver, giving velocity and pressure field, as well as wall shear stress distribution. ABM method was applied on the arterial wall taken into account cell mitosis and ECM production in the intima including lipid cells. The change of the shape of the cross-sections of the arterial wall is presented in three specific moments in time (baseline, after 3 months and after 6 months).
Specific carotid artery patient from US was modeled with coupled FEM and ABM method. First results show good agreement between proposed method and clinical measurements in the follow up 3D US image reconstruction. The integrated model ABM and FEM can help to predict the evolution of atherosclerotic plaque which is very significant for appropriate diagnostics and vascular treatment planning.
The research presented in this study was part of the project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 755320-2 - TAXINOMISIS.
Ključne reči :
SIMPOZIJUM B - Biomaterijali i nanomedicina