Computational fluid dynamic simulations of aortic coarctation comparing the effects of surgical‐ and stent‐based treatments on aortic compliance and ventricular workload

Coogan, Jessica S.; Chan, Frandics P.; Taylor, Charles A.; Feinstein, Jeffrey A.

doi:10.1002/ccd.22878

Cited by 48 publications

(38 citation statements)

References 77 publications

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“…Coogan et al 3 examined the effects of stent-induced aortic stiffness on cardiac workload and blood pressure in post-intervention coarctation patients. A heart model was used as inlet boundary condition in order to enable the simulation of conditions beyond those when the patient is imaged (e.g.…”

Section: Resultsmentioning

confidence: 99%

“…The proximal vessels are modeled as axi-symmetric 1D vessel segments, where the flow satisfies the following properties: conservation of mass, conservation of momentum, and a state equation for wall deformation (1) - (3). The vessel wall is modeled as a purely elastic material.…”

Section: Reduced-order Model For Blood Flow Computationmentioning

confidence: 99%

“…Depending on the availability of in-vivo measurements and the underlying assumptions of the model, researches typically use one of the following inlet boundary condition: (i) time-varying velocity (or flow rate) profile 11,14 , or (ii) a lumped model of the heart coupled at the inlet 4,3 . The former can be easily determined in a clinical setting, and is often part of the diagnostic workflow (2D/3D Phasecontrast MRI, Doppler ultrasound).…”

Section: Parameter Estimation For Model Personalizationmentioning

confidence: 99%

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Non-Invasive Hemodynamic Assessment of Aortic Coarctation: Validation with In Vivo Measurements

et al. 2012

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We propose a CFD-based approach for the non-invasive hemodynamic assessment of pre-and post-operative coarctation of aorta (CoA) patients. Under our approach, the pressure gradient across the coarctation is determined from computational modeling based on physiological principles, medical imaging data, and routine non-invasive clinical measurements. The main constituents of our approach are a reduced-order model for computing blood flow in patientspecific aortic geometries, a parameter estimation procedure for determining patient-specific boundary conditions and vessel wall parameters from non-invasive measurements, and a comprehensive pressure-drop formulation coupled with the overall reduced-order model. The

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Section: Resultsmentioning

confidence: 99%

Section: Reduced-order Model For Blood Flow Computationmentioning

confidence: 99%

Section: Parameter Estimation For Model Personalizationmentioning

confidence: 99%

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Non-Invasive Hemodynamic Assessment of Aortic Coarctation: Validation with In Vivo Measurements

et al. 2012

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“…The clinical gold-standard is obtained by invasive cardiac catheterization to measure ( P ) across the coarctation site. Recently, Doppler and phase contrast (PC) MRI based methods have been proposed for a non-invasive estimation of P [2] by using simplified relationships (e.g. modified Bernoulli equation) between flow and pressure.…”

Section: Introductionmentioning

confidence: 99%

Hemodynamic Assessment of Pre- and Post-operative Aortic Coarctation from MRI

Ralovich

Itu

Mihalef

et al. 2012

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012

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Abstract. Coarctation of the aorta (CoA), is a congenital defect characterized by a severe narrowing of the aorta, usually distal to the aortic arch. The treatment options include surgical repair, stent implantation, and balloon angioplasty. In order to evaluate the physiological significance of the pre-operative coarctation and to assess the post-operative results, the hemodynamic analysis is usually performed by measuring the pressure gradient ( P ) across the coarctation site via invasive cardiac catheterization. The measure of success is reduction of the ( P > 20mmHg) systolic blood pressure gradient. In this paper, we propose a non-invasive method based on Computational Fluid Dynamics and MR imaging to estimate the pre-and post-operative hemodynamics for both native and recurrent coarctation patients. High correlation of our results and catheter measurements is shown on corresponding preand post-operative examination of 5 CoA patients.

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“…However, in spite of satisfactory repairs, recovering the pressure gradient to an acceptable limit, late complications are not uncommon. To address these problematic events, research have turned to computational fluid dynamics (CFD) to simulate the outcome of different CoA interventions, [10][11][12][29][30][31]38 where pressure drop and wall shear stress (WSS) are some of the evaluated parameters. However, a downside with most of these flow descriptors is that they can only be acquired with reasonable accuracy by invasive methods or via CFD.…”

Section: Introductionmentioning

confidence: 99%

Erratum to: Quantitative Assessment of Turbulence and Flow Eccentricity in an Aortic Coarctation: Impact of Virtual Interventions

Andersson

Lantz

Ebbers

et al. 2015

Cardiovasc Eng Tech

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Abstract-Turbulence and flow eccentricity can be measured by magnetic resonance imaging (MRI) and may play an important role in the pathogenesis of numerous cardiovascular diseases. In the present study, we propose quantitative techniques to assess turbulent kinetic energy (TKE) and flow eccentricity that could assist in the evaluation and treatment of stenotic severities. These hemodynamic parameters were studied in a pre-treated aortic coarctation (CoA) and after several virtual interventions using computational fluid dynamics (CFD), to demonstrate the effect of different dilatation options on the flow field. Patient-specific geometry and flow conditions were derived from MRI data. The unsteady pulsatile flow was resolved by large eddy simulation (LES) including non-Newtonian blood rheology. Results showed an inverse asymptotic relationship between the total amount of TKE and degree of dilatation of the stenosis, where the pre-stenotic hypoplastic segment may limit the possible improvement by treating the CoA alone. Spatiotemporal maps of TKE and flow eccentricity could be linked to the characteristics of the post-stenotic jet, showing a versatile response between the CoA dilatations. By including these flow markers into a combined MRI-CFD intervention framework, CoA therapy has not only the possibility to produce predictions via simulation, but can also be validated pre-and immediate post treatment, as well as during followup studies.Keywords-Computational fluid dynamics, Large eddy simulation, Turbulent kinetic energy, Flow displacement, NonNewtonian, Carreau, Virtual treatment, Magnetic resonance imaging.ERRATUM TO: CARDIOVASCULAR ENGINEERINGAND TECHNOLOGY (2015) 6(3):281-293 DOI 10.1007/S13239-015-0218-X This erratum originates from a fault in the boundary conditions of the computational models, resulting in elevated flow conditions through the descending aorta with respect to the measured patient-specific data. This was not in line with the numerical setup addressed in the paper. Hence, this matter was adjusted to the appropriate physiological state and each case re-simulated accordingly. In spite of this revision all conclusions of the paper are unaltered.

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Computational fluid dynamic simulations of aortic coarctation comparing the effects of surgical‐ and stent‐based treatments on aortic compliance and ventricular workload

Abstract: This pilot study suggests CoA stenting may not affect cardiac work to any significant degree as is commonly believed in the clinical community.

Cited by 48 publications

References 77 publications

Non-Invasive Hemodynamic Assessment of Aortic Coarctation: Validation with In Vivo Measurements

Non-Invasive Hemodynamic Assessment of Aortic Coarctation: Validation with In Vivo Measurements

Hemodynamic Assessment of Pre- and Post-operative Aortic Coarctation from MRI

Erratum to: Quantitative Assessment of Turbulence and Flow Eccentricity in an Aortic Coarctation: Impact of Virtual Interventions

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