Fluid–structure interaction simulations outperform computational fluid dynamics in the description of thoracic aorta haemodynamics and in the differentiation of progressive dilation in Marfan syndrome patients

Pons, Roser; Guala, Andrea; Rodríguez-Palomares, José F.; Cajas, Juan Carlos; Dux-Santoy, Lydia; Teixidó-Turà, Gisela; Molins, José J.; Vázquez, Mariano; Evangelista, Arturo; Martorell, Jordi

doi:10.1098/rsos.191752

Cited by 31 publications

(25 citation statements)

References 52 publications

(70 reference statements)

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“…Beyond anisotropy and hyperelasticity of the aTAA, another aspect to be taken into account is the presence of pre-stress in the vessel. A number of studies dedicated to aTAA assumed the diastolic phase as unloaded (Pons et al, 2020 ), although it is reasonable to consider stresses induced by the diastolic pressure (Moireau et al, 2012 ; Bäumler et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Fully-Coupled FSI Computational Analyses in the Ascending Thoracic Aorta Using Patient-Specific Conditions and Anisotropic Material Properties

et al. 2021

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Computational hemodynamics has become increasingly important within the context of precision medicine, providing major insight in cardiovascular pathologies. However, finding appropriate compromise between speed and accuracy remains challenging in computational hemodynamics for an extensive use in decision making. For example, in the ascending thoracic aorta, interactions between the blood and the aortic wall must be taken into account for the sake of accuracy, but these fluid structure interactions (FSI) induce significant computational costs, especially when the tissue exhibits a hyperelastic and anisotropic response. The objective of the current study is to use the Small On Large (SOL) theory to linearize the anisotropic hyperelastic behavior in order to propose a reduced-order model for FSI simulations of the aorta. The SOL method is tested for fully-coupled FSI simulations in a patient-specific aortic geometry presenting an Ascending Thoracic Aortic Aneurysm (aTAA). The same model is also simulated with a fully-coupled FSI with non-linear material behavior, without SOL linearization. Eventually, the results and computational times with and without the SOL are compared. The SOL approach is demonstrated to provide a significant reduction of computational costs for FSI analysis in the aTAA, and the results in terms of stress state distribution are comparable. The method is implemented in ANSYS and will be further evaluated for clinical applications.

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Section: Introductionmentioning

confidence: 99%

Fully-Coupled FSI Computational Analyses in the Ascending Thoracic Aorta Using Patient-Specific Conditions and Anisotropic Material Properties

et al. 2021

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“…Error analyses provided by the state of the art confirm the performances of the hyperelastic anisotropic models ( 36 , 37 ). Nevertheless, it is worth underlining that, even if the fiber-based models are suitable to cope with the hyperelastic and anisotropic nature of the aortic tissue, different groups still adopt linearized approaches to model the tissue behavior in numerical approaches, also to reduce the model complexity, and lighten the computational load ( 38 – 40 ). The linearization approach can be justified by the assumption of small deformations occurring between the systolic and diastolic phases in the cardiac cycle.…”

Section: Introductionmentioning

confidence: 99%

On the Role and Effects of Uncertainties in Cardiovascular in silico Analyses

Celi

Vignali

Capellini

et al. 2021

Front. Med. Technol.

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The assessment of cardiovascular hemodynamics with computational techniques is establishing its fundamental contribution within the world of modern clinics. Great research interest was focused on the aortic vessel. The study of aortic flow, pressure, and stresses is at the basis of the understanding of complex pathologies such as aneurysms. Nevertheless, the computational approaches are still affected by sources of errors and uncertainties. These phenomena occur at different levels of the computational analysis, and they also strongly depend on the type of approach adopted. With the current study, the effect of error sources was characterized for an aortic case. In particular, the geometry of a patient-specific aorta structure was segmented at different phases of a cardiac cycle to be adopted in a computational analysis. Different levels of surface smoothing were imposed to define their influence on the numerical results. After this, three different simulation methods were imposed on the same geometry: a rigid wall computational fluid dynamics (CFD), a moving-wall CFD based on radial basis functions (RBF) CFD, and a fluid-structure interaction (FSI) simulation. The differences of the implemented methods were defined in terms of wall shear stress (WSS) analysis. In particular, for all the cases reported, the systolic WSS and the time-averaged WSS (TAWSS) were defined.

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“…Each used a uniform value of E throughout the aorta, requiring multiple FSI simulations for its calibration. Lantz et al (2011) and Boccadifuoco et al (2018) used several literature values of E in the physiological range, whereas Pons et al (2020) iteratively adjusted E by calibrating the pulse wave velocity (PWV) using estimations from 4D-Flow MRI. Comparisons against MRI data found that FSI failed to accurately capture wall movement throughout the aorta when uniform E was observed.…”

Section: Introductionmentioning

confidence: 99%

“…MRI-based techniques have been developed but typically employ a rigid-wall assumption (Bozzi et al, 2017;Madhavan and Kemmerling, 2018;Youssefi et al, 2017). Several MRI-based FSI studies of healthy aortae have appeared in the literature, including those of Lantz et al (2011), Boccadifuoco et al (2018) and Pons et al (2020). Each used a constant value of E throughout the aorta, requiring multiple FSI simulations for its calibration.…”

Section: Introductionmentioning

confidence: 99%

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A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics

Stokes

Bonfanti

Li³

et al. 2021

Preprint

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We present a novel, cost-efficient methodology to simulate aortic haemodynamics in a patient-specific, compliant aorta using an MRI data fusion process. Based on a previously-developed Moving Boundary Method, this technique circumvents the high computational cost and numerous structural modelling assumptions required by traditional Fluid-Structure Interaction techniques. Without the need for Computed Tomography (CT) data, the MRI images required to construct the simulation can be obtained during a single imaging session. Black Blood MR Angiography and 2D Cine-MRI data were used to reconstruct the luminal geometry and calibrate wall movement specifically to each region of the aorta. 4D-Flow MRI and non-invasive pressure measurements informed patient-specific inlet and outlet boundary conditions. Simulated wall movement closely matched 2D Cine-MRI measurements throughout the aorta, and physiological pressure and flow distributions in CFD were achieved within 3.3% of patient-specific targets. Excellent agreement with 4D-Flow MRI velocity data was observed. Conversely, a rigid-wall simulation under-predicted peak flow rate and systolic maximum velocities whilst predicting a mean Time-Averaged Wall Shear Stress (TAWSS) 13% higher than the compliant simulation. The excellent agreement observed between compliant simulation results and MRI is testament to the accuracy and efficiency of this MRI-based technique.

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Fluid–structure interaction simulations outperform computational fluid dynamics in the description of thoracic aorta haemodynamics and in the differentiation of progressive dilation in Marfan syndrome patients

Abstract: Cite this article: Pons R et al. 2020 Fluidstructure interaction simulations outperform computational fluid dynamics in the description of thoracic aorta haemodynamics and in the differentiation of progressive dilation in Marfan syndrome patients. R. Soc. open sci. 7: 191752. http://dx.

Cited by 31 publications

References 52 publications

Fully-Coupled FSI Computational Analyses in the Ascending Thoracic Aorta Using Patient-Specific Conditions and Anisotropic Material Properties

Fully-Coupled FSI Computational Analyses in the Ascending Thoracic Aorta Using Patient-Specific Conditions and Anisotropic Material Properties

On the Role and Effects of Uncertainties in Cardiovascular in silico Analyses

A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics

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