1 April 2016 In vitro flow assessment: from PC-MRI to computational fluid dynamics including fluid-structure interaction
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Initiation and development of cardiovascular diseases can be highly correlated to specific biomechanical parameters. To examine and assess biomechanical parameters, numerical simulation of cardiovascular dynamics has the potential to complement and enhance medical measurement and imaging techniques. As such, computational fluid dynamics (CFD) have shown to be suitable to evaluate blood velocity and pressure in scenarios, where vessel wall deformation plays a minor role. However, there is a need for further validation studies and the inclusion of vessel wall elasticity for morphologies being subject to large displacement. In this work, we consider a fluid-structure interaction (FSI) model including the full elasticity equation to take the deformability of aortic wall soft tissue into account. We present a numerical framework, in which either a CFD study can be performed for less deformable aortic segments or an FSI simulation for regions of large displacement such as the aortic root and arch. Both of the methods are validated by means of an aortic phantom experiment. The computational results are in good agreement with 2D phase-contrast magnetic resonance imaging (PC-MRI) velocity measurements as well as catheter-based pressure measurements. The FSI simulation shows a characteristic vessel compliance effect on the flow field induced by the elasticity of the vessel wall, which the CFD model is not capable of. The in vitro validated FSI simulation framework can enable the computation of complementary biomechanical parameters such as the stress distribution within the vessel wall.
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Jonas Kratzke, Jonas Kratzke, Fabian Rengier, Fabian Rengier, Christian Weis, Christian Weis, Carsten J. Beller, Carsten J. Beller, Vincent Heuveline, Vincent Heuveline, } "In vitro flow assessment: from PC-MRI to computational fluid dynamics including fluid-structure interaction", Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 97835C (1 April 2016); doi: 10.1117/12.2217336; https://doi.org/10.1117/12.2217336

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