Impact of patient-specific LVOT inflow profiles on aortic valve prosthesis and ascending aorta hemodynamics

Bruening, Jan; Hellmeier, Florian; Yevtushenko, Pavlo; Kelm, Marcus; Nordmeyer, Sarah; Sündermann, Simon H.; Küehne, Titus; Goubergrits, Leonid

doi:10.1016/j.jocs.2017.11.005

Cited by 15 publications

(11 citation statements)

References 33 publications

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“…The WSS gives a measure of the interaction between blood and artery and correlates with exchange processes such as load acting on the endothelial cells (Bruening et al, 2018). However, the predisposition to high or low WSS-related indices and its relationship with the aortic morphology is still debated and other indices as the helicity has been introduced and discussed (Morbiducci et al, 2009(Morbiducci et al, , 2011(Morbiducci et al, , 2015.…”

Section: Discussionmentioning

confidence: 99%

A parametric model for studying the aorta hemodynamics by means of the computational fluid dynamics

Cilla

Casales

Peña

et al. 2020

Journal of Biomechanics

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Perturbed aorta hemodynamics, as for the carotid and the coronary artery, has been identified as potential predicting factor for cardiovascular diseases. In this study, we propose a parametric study based on the computational fluid dynamics with the aim of providing information regarding aortic disease. In particular, the blood flow inside a parametrized aortic arch is computed as a function of morphological changes of baseline aorta geometry. Flow patterns, wall shear stress, time average wall ManuscriptClick here to view linked References

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Section: Discussionmentioning

confidence: 99%

A parametric model for studying the aorta hemodynamics by means of the computational fluid dynamics

Cilla

Casales

Peña

et al. 2020

Journal of Biomechanics

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“…Indeed, velocity profiles in the LVOT are not plug-like (Garcia et al, 2011). Work by Bruening and colleagues shows that significant overestimation of the pressure drop can occur when assuming a plug-flow velocity profile opposed to a patient-specific flow profile from 4D velocity-encoded MRI (Bruening et al, 2018). However, differences between the full and truncated transient model are small in this study, and the added accuracy of the full model may therefore not outweigh the additional computational cost.…”

Section: Comparison Cfd Modelsmentioning

confidence: 72%

Estimation of valvular resistance of segmented aortic valves using computational fluid dynamics

Hoeijmakers

Soto

Waechter-Stehle

et al. 2019

Journal of Biomechanics

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Aortic valve stenosis is associated with an elevated left ventricular pressure and transaortic pressure drop. Clinicians routinely use Doppler ultrasound to quantify aortic valve stenosis severity by estimating this pressure drop from blood velocity. However, this method approximates the peak pressure drop, and is unable to quantify the partial pressure recovery distal to the valve. As pressure drops are flow dependent, it remains difficult to assess the true significance of a stenosis for low-flow low-gradient patients. Recent advances in segmentation techniques enable patient-specific Computational Fluid Dynamics (CFD) simulations of flow through the aortic valve. In this work a simulation framework is presented and used to analyze data of 18 patients. The ventricle and valve are reconstructed from 4D Computed Tomography imaging data. Ventricular motion is extracted from the medical images and used to model ventricular contraction and corresponding blood flow through the valve. Simplifications of the framework are assessed by introducing two simplified CFD models: a truncated time-dependent and a steady-state model. Model simplifications are justified for cases where the simulated pressure drop is above 10 mmHg. Furthermore, we propose a valve resistance index to quantify stenosis severity from simulation results. This index is compared to established metrics for clinical decision making, i.e. blood velocity and valve area. It is found that velocity measurements alone do not adequately reflect stenosis severity. This work demonstrates that combining 4D imaging data and CFD has the potential to provide a physiologically relevant diagnostic metric to quantify aortic valve stenosis severity.

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“…However, patient‐specific inflow profiles based on 4D MRI are not typically available. Further, 4D MRI data is challenging to use in CFD simulations because of low resolutions, high signal‐to‐noise ratio, and diagnostic variations arising from respiratory motion, changes in heart rate, and patient position . Thus, specifying physiological velocity conditions at the inlet is a nontrivial task, particularly in complex vascular geometries.…”

Section: Methodsmentioning

confidence: 99%

Suitability of lattice Boltzmann inlet and outlet boundary conditions for simulating flow in image‐derived vasculature

Feiger

Vardhan

Gounley

et al. 2019

Numer Methods Biomed Eng

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The lattice Boltzmann method (LBM) is a popular alternative to solving the Navier-Stokes equations for modeling blood flow. When simulating flow using the LBM, several choices for inlet and outlet boundary conditions exist. While boundary conditions in the LBM have been evaluated in idealized geometries, there have been no extensive comparisons in image-derived vasculature, where the geometries are highly complex. In this study, the Zou-He (ZH) and finite difference (FD) boundary conditions were evaluated in image-derived vascular geometries by comparing their stability, accuracy, and run times. The boundary conditions were compared in four arteries: a coarctation of the aorta, dissected aorta, femoral artery, and left coronary artery. The FD boundary condition was more stable than ZH in all four geometries. In general, simulations using the ZH and FD method showed similar convergence rates within each geometry. However, the ZH method proved to be slightly more accurate compared with experimental flow using three-dimensional printed vasculature. The total run times necessary for simulations using the ZH boundary condition were significantly higher as the ZH method required a larger relaxation time, grid resolution, and number of time steps for a simulation representing the same physiological time. Finally, a new inlet velocity profile algorithm is presented for complex inlet geometries. Overall, results indicated that the FD method should generally be used for large-scale blood flow simulations in image-derived vasculature geometries. This study can serve as a guide to researchers interested in using the LBM to simulate blood flow. KEYWORDS boundary conditions, finite difference, hemodynamics, image-derived vasculature, lattice Boltzmann method, Zou-He Int J Numer Meth Biomed Engng. 2019;35:e3198.wileyonlinelibrary.com/journal/cnm

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Impact of patient-specific LVOT inflow profiles on aortic valve prosthesis and ascending aorta hemodynamics

Cited by 15 publications

References 33 publications

A parametric model for studying the aorta hemodynamics by means of the computational fluid dynamics

A parametric model for studying the aorta hemodynamics by means of the computational fluid dynamics

Estimation of valvular resistance of segmented aortic valves using computational fluid dynamics

Suitability of lattice Boltzmann inlet and outlet boundary conditions for simulating flow in image‐derived vasculature

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