Nicole Mingardi
A network-based approach to investigate intravascular flow coherence in personalized computational models of human carotid bifurcation.
Rel. Umberto Morbiducci, Diego Gallo, Karol Calo'. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2022
Abstract
The blood flow patterns in carotid arteries are extremely complex, inspiring a lot of studies in the literature focused on the definition and application of different quantitative tools in order to describe the hemodynamics and to understand the risks associated with the onset/progression of vascular disease. This is because hemodynamics in the carotid arteries is characterized by a space-time heterogeneity due to the non-symmetrical nature of the carotid bifurcation, the presence of tortuosity and non-planar curvatures, and the compliance of the walls, which contribute to the development of anterograde and retrograde intravascular blood flow structures, with secondary flow components. The aim of this work is to delineate and interpret coherent large-scale flow structures in the carotid bifurcation by capturing the spatiotemporal evolution of correlated blood flow patterns and their anatomical length of persistence, thus contributing to the understanding of the organization patterns of hemodynamic flows.
To do that, an integrated computational hemodynamics and Complex Networks-based approach has been applied on 31 personalized hemodynamic models of carotid bifurcation of healthy subjects, obtained from MRI acquisitions
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