Validation of numerical simulation methods in aortic arch using 4D Flow MRI

Shohei Miyazaki,Yasuo Takehara,Masataka Sugiyama,Teruyasu Nishino,Satoshi Yasukochi,Toyoki Furusawa,Keiichi Itatani

doi:10.1007/s00380-017-0979-2

Abstract

Computational fluid dynamics (CFD) are the gold standard in studying blood flow dynamics. However, CFD results are dependent on the boundary conditions and the computation model. The purpose of this study was to validate CFD methods using comparison with actual measurements of the blood flow vector obtained with four-dimensional (4D) flow magnetic resonance imaging (MRI). 4D Flow MRI was performed on a healthy adult and a child with double-aortic arch. The aortic lumen was segmented to visualize the blood flow. The CFD analyses were performed for the same geometries based on three turbulent models: laminar, large eddy simulation (LES), and the renormalization group k–ε model (RNG k–ε). The flow-velocity vector components, namely the wall shear stress (WSS) and flow energy loss (EL), of the MRI and CFD results were compared. The flow rate of the MRI results was underestimated in small vessels, including the neck vessels. Spiral flow in the ascending aorta caused by the left ventricular twist was observed by MRI. Secondary flow distal to the aortic arch was well realized in both CFD and MRI. The average correlation coefficients of the velocity vector components of MRI and CFD for the child were the highest for the RNG k–ε model (0.530 in ascending aorta, 0.768 in the aortic arch, 0.584 in the descending aorta). The WSS and EL values of MRI were less than half of those of CFD, but the WSS distribution patterns were quite similar. The WSS and EL estimates were higher in RNG k–ε and LES than in the laminar model because of eddy viscosity. The CFD computation realized accurate flow distal to the aortic arch, and the WSS distribution was well simulated compared to actual measurement using 4D Flow MRI. However, the helical flow was not simulated in the ascending aorta. The accuracy was enhanced by using the turbulence model, and the RNG k–ε model showed the highest correlation with 4D Flow MRI.

Highlights

The flow visualization methods used with recent imaging technologies have been applied to the circulatory system to reveal the pathophysiology of cardiovascular diseases
In the present Computational fluid dynamics (CFD) method, a flat velocity profile was used on the top of the extruded boundary face as the inlet boundary condition, and the inlet velocity profile was developed in the linear extruded tube toward the axial through-plane direction without forming helical flow
In the child, the correlation in ascending aorta (AAo) was worse because the helical flow, which is known to be affected by the age and size of the aortic valve [15], was stronger than that in the adult case

Summary

Introduction

The flow visualization methods used with recent imaging technologies have been applied to the circulatory system to reveal the pathophysiology of cardiovascular diseases. Computational fluid dynamics (CFD) are considered a gold standard method of blood flow visualization and are often used for analyzing blood flow in cases of aortic disease to evaluate the wall shear stress (WSS) [1–3] or in cases of congenital heart disease to evaluate the flow energy loss (EL) [4, 5]. Compared to in vivo measurements, including echocardiography or phase contrast MRI, CFD has various advantages. CFD allows testing of the effects of isolated factors, allowing blood flow evaluation without statistical study. CFD enables virtual surgery by modifying the vessel geometry into the intended post-operative geometry.

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