Toward a realistic reconstruction and determination of blood flow pattern in complex vascular network: 3D, non-Newtonian, multi-branch simulation based on CFD and GMDH algorithm

Abstract

Determination of flow pattern within a tissue is a complicated and crucial task for several purposes including drug delivery and clinical treatments. However, as the vasculature composes of a complex network of interconnected vessels with a wide range of geometrical properties; even its realistic reconstruction is still challenging. Additionally, direct CFD simulation of a network of thousands of connected tubes with various configurations is a sophisticated process. In the present study, a novel approach is proposed to reconstruct the 3D vascular system using the angiography data. The network can be extended to reach any particular sizing level from main vessels to microvessels. Moreover, to determine the flow field throughout the vasculature, the CFD tool is utilized to generate a database of pressure and velocity distribution for a wide variety of branching scenarios. The obtained database is used as the training set of data by the GMDH algorithm to determine the connection between the input and output parameters. Finally, the combination of the trained GMDH algorithm and the reconstructed vasculature is incorporated to simulate the blood flow. According to the results, the proposed algorithm has an excellent capability to create the vascular system and predict the flow field within the tissue.