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A comprehensive MRI-based computational model of blood flow in compliant aorta using radial basis function interpolation.
Perinajová, Romana; van de Ven, Thijn; Roelse, Elise; Xu, Fei; Juffermans, Joe; Westenberg, Jos; Lamb, Hildo; Kenjeres, Sasa.
Afiliação
  • Perinajová R; Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands. romana.perinajova@gmail.com.
  • van de Ven T; J.M. Burgerscentrum Research School for Fluid Mechanics, Delft, The Netherlands. romana.perinajova@gmail.com.
  • Roelse E; Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands.
  • Xu F; Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands.
  • Juffermans J; Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands.
  • Westenberg J; J.M. Burgerscentrum Research School for Fluid Mechanics, Delft, The Netherlands.
  • Lamb H; Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
  • Kenjeres S; Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Biomed Eng Online ; 23(1): 69, 2024 Jul 23.
Article em En | MEDLINE | ID: mdl-39039565
ABSTRACT

BACKGROUND:

Properly understanding the origin and progression of the thoracic aortic aneurysm (TAA) can help prevent its growth and rupture. For a better understanding of this pathogenesis, the aortic blood flow has to be studied and interpreted in great detail. We can obtain detailed aortic blood flow information using magnetic resonance imaging (MRI) based computational fluid dynamics (CFD) with a prescribed motion of the aortic wall.

METHODS:

We performed two different types of simulations-static (rigid wall) and dynamic (moving wall) for healthy control and a patient with a TAA. For the latter, we have developed a novel morphing approach based on the radial basis function (RBF) interpolation of the segmented 4D-flow MRI geometries at different time instants. Additionally, we have applied reconstructed 4D-flow MRI velocity profiles at the inlet with an automatic registration protocol.

RESULTS:

The simulated RBF-based movement of the aorta matched well with the original 4D-flow MRI geometries. The wall movement was most dominant in the ascending aorta, accompanied by the highest variation of the blood flow patterns. The resulting data indicated significant differences between the dynamic and static simulations, with a relative difference for the patient of 7.47±14.18% in time-averaged wall shear stress and 15.97±43.32% in the oscillatory shear index (for the whole domain).

CONCLUSIONS:

In conclusion, the RBF-based morphing approach proved to be numerically accurate and computationally efficient in capturing complex kinematics of the aorta, as validated by 4D-flow MRI. We recommend this approach for future use in MRI-based CFD simulations in broad population studies. Performing these would bring a better understanding of the onset and growth of TAA.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aorta / Simulação por Computador / Imageamento por Ressonância Magnética / Hidrodinâmica Limite: Humans Idioma: En Revista: Biomed Eng Online Assunto da revista: ENGENHARIA BIOMEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aorta / Simulação por Computador / Imageamento por Ressonância Magnética / Hidrodinâmica Limite: Humans Idioma: En Revista: Biomed Eng Online Assunto da revista: ENGENHARIA BIOMEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Holanda