Non-invasive Prediction of Peak Systolic Pressure Drop across Coarctation of Aorta using Computational Fluid Dynamics

Aslan, Seda; Mass, Paige; Loke, Yue-Hin; Warburton, Linnea; Liu, Xiaolong; Hibino, Narutoshi; Olivieri, Laura; Krieger, Axel

doi:10.1109/embc44109.2020.9176461

Cited by 6 publications

(7 citation statements)

References 17 publications

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“…Therefore, the use of pressure measured by alternative techniques is preferable in order to obtain a full non-invasive methodology. 3 Our stochastic analysis was performed considering only one uncertain parameter, a, which acts on the resistance of the systems. A previous study has shown that the capacitance C can also affect hemodynamic quantities of interest, such as flows, pressures, and WSS.…”

Section: Discussionmentioning

confidence: 99%

“…In this context, the pressure drop across the CoA district can be derived from the numerical solution of the Navier-Stokes equations with the use of Magnetic Resonance Imaging (MRI) velocity field data. 3,11,17,23 Advances in image acquisition and numerical simulations have resulted in increasingly realistic patientspecific models. To make a digital twin of the patient, we need the geometric accuracy, and input and output boundary conditions.…”

Section: Introductionmentioning

confidence: 99%

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Effects of Uncertainty of Outlet Boundary Conditions in a Patient-Specific Case of Aortic Coarctation

et al. 2021

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Computational Fluid Dynamics (CFD) simulations of blood flow are widely used to compute a variety of hemodynamic indicators such as velocity, time-varying wall shear stress, pressure drop, and energy losses. One of the major advances of this approach is that it is non-invasive. The accuracy of the cardiovascular simulations depends directly on the level of certainty on input parameters due to the modelling assumptions or computational settings. Physiologically suitable boundary conditions at the inlet and outlet of the computational domain are needed to perform a patient-specific CFD analysis. These conditions are often affected by uncertainties, whose impact can be quantified through a stochastic approach. A methodology based on a full propagation of the uncertainty from clinical data to model results is proposed here. It was possible to estimate the confidence associated with model predictions, differently than by deterministic simulations. We evaluated the effect of using three-element Windkessel models as the outflow boundary conditions of a patient-specific aortic coarctation model. A parameter was introduced to calibrate the resistances of the Windkessel model at the outlets. The generalized Polynomial Chaos method was adopted to perform the stochastic analysis, starting from a few deterministic simulations. Our results show that the uncertainty of the input parameter gave a remarkable variability on the volume flow rate waveform at the systolic peak simulating the conditions before the treatment. The same uncertain parameter had a slighter effect on other quantities of interest, such as the pressure gradient. Furthermore, the results highlight that the fine-tuning of Windkessel resistances is not necessary to simulate the post-stenting scenario.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effects of Uncertainty of Outlet Boundary Conditions in a Patient-Specific Case of Aortic Coarctation

et al. 2021

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“…The governing Equations of cardiac blood flow are the Navier-Stokes Equations. In order to analyze the effect of the septal defect on cardiac flow, the convective-diffusion equation is used to express the dimensionless oxygen content [8,15].…”

Section: Numerical Algorithm and Boundary Conditionsmentioning

confidence: 99%

where ρ is the blood density; u the velocity of blood flow; p the dimensionless local pressure of blood (0 < p < 1; 0: the diastolic pressure; 1: systolic pressure); S the strain rate tensor of blood; μ the viscosity of blood; α the diffusion coefficient of blood oxygen content; C b the dimensionless blood oxygen content (−1 < C b < 1; −1: the oxygen content in the superior/inferior vena cava; 1: the oxygen content in the pulmonary vein).…”

Section: Numerical Algorithm and Boundary Conditionsmentioning

confidence: 99%

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Simulation of Cardiac Flow under the Septal Defect Based on Lattice Boltzmann Method

Wang

Zhang

et al. 2022

Entropy

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In this paper, the lattice Boltzmann method was used to simulate the cardiac flow in children with aseptal defect. The inner wall model of the heart was reconstructed from 210 computed tomography scans. By simulating and comparing the cardiac flow field, the pressure field, the blood oxygen content, and the distribution of entropy generation before and after an operation, the effects of septal defect on pulmonary hypertension(PH), cyanosis, and heart load were analyzed in detail. It is found that the atrial septal defect(ASD) of the child we analyzed had a great influence on the blood oxygen content in the pulmonary artery, which leads to lower efficiency of oxygen binding in the lungs and increases the burden on the heart. At the same time, it also significantly enhanced the entropy generation rate of the cardiac flow, which also leads to a higher heart load. However, the main cause of PH is not ASD, but ventricular septal defect (VSD). Meanwhile, it significantly reduced the blood oxygen content in the brachiocephalic trunk, but rarely affects the blood oxygen contents in the downstream left common carotid artery, left subclavian artery, and descending aorta are not significantly affected by VSD. It causes severe cyanosis on the face and lips.

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Virtual Planning and Patient-Specific Graft Design for Aortic Repairs

Aslan,

Liu,

et al. 2023

Cardiovasc Eng Tech

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Non-invasive Prediction of Peak Systolic Pressure Drop across Coarctation of Aorta using Computational Fluid Dynamics

Cited by 6 publications

References 17 publications

Effects of Uncertainty of Outlet Boundary Conditions in a Patient-Specific Case of Aortic Coarctation

Effects of Uncertainty of Outlet Boundary Conditions in a Patient-Specific Case of Aortic Coarctation

Simulation of Cardiac Flow under the Septal Defect Based on Lattice Boltzmann Method

Virtual Planning and Patient-Specific Graft Design for Aortic Repairs

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