Impact of atrial fibrillation on left atrium haemodynamics: A computational fluid dynamics study

Corti, Mattia; Zingaro, Alberto; Dedè, Luca; Quarteroni, Alfio

doi:10.1016/j.compbiomed.2022.106143

Cited by 29 publications

(35 citation statements)

References 60 publications

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“…In these studies, surrogates of blood flow fields have been studied to associate the dynamics of the blood flow inside the LA and LAA to risk of clot formation. There are several examples of these surrogates, including but not limited to: shear strain rate, wall shear stress ( 13 , 14 ), oscillatory shear index, time-averaged wall shear stress ( 15 , 16 ), time-averaged velocity ( 13 , 17 – 21 ), particle resident time ( 22 , 23 ), local relative residence time ( 16 , 24 – 26 ), residual virtual contrast agent ( 13 , 18 , 19 , 27 ), vortex structure ( 14 , 17 – 20 , 25 ), flow kinetic energy ( 25 ), age stasis ( 28 ), and endothelial cell activation potential (ECAP) ( 16 , 29 – 31 ). The most accurate approach to simulate clot formation is to include the mechanics of the blood cell (i.e., red blood cells, platelets, etc.)…”

Section: Introductionmentioning

confidence: 99%

Subject-specific factors affecting particle residence time distribution of left atrial appendage in atrial fibrillation: A computational model-based study

Sanatkhani

Nedios²,

Menon³

et al. 2023

Front. Cardiovasc. Med.

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BackgroundAtrial fibrillation (AF) is a prevalent arrhythmia, that causes thrombus formation, ordinarily in the left atrial appendage (LAA). The conventional metric of stroke risk stratification, CHA2DS2-VASc score, does not account for LAA morphology or hemodynamics. We showed in our previous study that residence time distribution (RTD) of blood-borne particles in the LAA and its associated calculated variables (i.e., mean residence time, tm, and asymptotic concentration, C∞) have the potential to improve CHA2DS2-VASc score. The purpose of this research was to investigate the effects of the following potential confounding factors on LAA tm and C∞: (1) pulmonary vein flow waveform pulsatility, (2) non-Newtonian blood rheology and hematocrit level, and (3) length of the simulation.MethodsSubject-Specific data including left atrial (LA) and LAA cardiac computed tomography, cardiac output (CO), heart rate, and hematocrit level were gathered from 25 AF subjects. We calculated LAA tm and C∞ based on series of computational fluid dynamics (CFD) analyses.ResultsBoth LAA tm and C∞ are significantly affected by the CO, but not by temporal pattern of the inlet flow. Both LAA tm and C∞ increase with increasing hematocrit level and both calculated indices are higher for non-Newtonian blood rheology for a given hematocrit level. Further, at least 20,000 s of CFD simulation is needed to calculate LAA tm and C∞ values reliably.ConclusionsSubject-specific LA and LAA geometries, CO, and hematocrit level are essential to quantify the subject-specific proclivity of blood cell tarrying inside LAA in terms of the RTD function.

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Section: Introductionmentioning

confidence: 99%

Subject-specific factors affecting particle residence time distribution of left atrial appendage in atrial fibrillation: A computational model-based study

Sanatkhani

Nedios²,

Menon³

et al. 2023

Front. Cardiovasc. Med.

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“…In parallel, echocardiographic LV stasis mapping has proven predictive value for LV thrombosis and brain embolism in pre-clinical and clinical pilot studies [54][55][56]. However, blood flow in the LA is highly three-dimensional and unsteady, and CFD-simulated LA hemodynamics can exhibit significant intra-patient variability depending on modeling parameters [17,21,36,53]. A better understanding of this variability is required to develop reliable CFD-derived biomarkers of atriogenic stroke risk.…”

Section: Discussionmentioning

confidence: 99%

“…These single-chamber simulations have focused mostly on LV hemodynamics [11][12][13][14][15][16], although there is a growing body of literature exploring different aspects of LA hemodynamics. One of the most studied aspects is the effect of LA wall motion on the flow and LAA stasis [17][18][19][20][21], motivated by the fact that AF causes weak irregular LA wall motion and LAA stasis is associated with increased thrombosis risk [1,[22][23][24][25]. Motivated by the clinical association between LAA morphology and stroke risk in AF patients [26][27][28], several groups have used CFD to investigate how LAA shape influences surrogate hemodynamic metrics of thrombosis risk [29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Pulmonary vein flow split effects in patient-specific simulations of left atrial flow

Durán

García-Villalba

Martínez‐Legazpi

et al. 2023

Preprint

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Disruptions to left atrial (LA) blood flow, such as those caused by atrial fibrillation (AF), can lead to thrombosis in the left atrial appendage (LAA) and an increased risk of systemic embolism. LA hemodynamics are influenced by various factors, including LA anatomy and function, and pulmonary vein (PV) inflow conditions. In particular, the PV flow split can vary significantly among and within patients depending on multiple factors. In this study, we investigated how changes in PV flow split affect LA flow transport, focusing on blood stasis in the LAA, using a high-fidelity patient-specific computational fluid dynamics (CFD) model. We analyzed LA anatomies from eight patients with varying atrial function, including three with AF and either a LAA thrombus or a history of TIAs. Using four different flow splits (60/40\% and 55/45\% through right and left PVs, even flow rate, and same velocity through each PV), we found that flow patterns are sensitive to PV flow split variations, particularly in planes parallel to the mitral valve. Changes in PV flow split also had a significant impact on blood stasis and could contribute to increased risk for thrombosis inside the LAA, particularly in patients with AF and previous LAA thrombus or a history of TIAs. Our study highlights the importance of considering patient-specific PV flow split variations when assessing LA hemodynamics and identifying patients at increased risk for thrombosis and stroke.

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“…ℛ u ð Þ is a resistive term that accounts for the presence of valves in a penalty-based approach (see below). 43,[107][108][109][110][111] In analogy with the solid mechanics problem (Section 2.1.4), no boundary conditions are prescribed on Σ since, on that portion of ∂Ω f , the interface conditions for the fluid-solid coupling are imposed (see Section 2.1.7). The functions p in t ð Þ and p out t ð Þ are pressures provided by the circulation model (see Section 2.1.8) for the pulmonary venous and systemic arterial circulation compartments, respectively.…”

Section: Fluid Dynamicsmentioning

confidence: 99%

A mathematical model that integrates cardiac electrophysiology, mechanics, and fluid dynamics: Application to the human left heart

Bucelli

Zingaro

Africa

et al. 2023

Numer Methods Biomed Eng

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We propose a mathematical and numerical model for the simulation of the heart function that couples cardiac electrophysiology, active and passive mechanics and hemodynamics, and includes reduced models for cardiac valves and the circulatory system. Our model accounts for the major feedback effects among the different processes that characterize the heart function, including electro‐mechanical and mechano‐electrical feedback as well as force‐strain and force‐velocity relationships. Moreover, it provides a three‐dimensional representation of both the cardiac muscle and the hemodynamics, coupled in a fluid–structure interaction (FSI) model. By leveraging the multiphysics nature of the problem, we discretize it in time with a segregated electrophysiology‐force generation‐FSI approach, allowing for efficiency and flexibility in the numerical solution. We employ a monolithic approach for the numerical discretization of the FSI problem. We use finite elements for the spatial discretization of partial differential equations. We carry out a numerical simulation on a realistic human left heart model, obtaining results that are qualitatively and quantitatively in agreement with physiological ranges and medical images.

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Impact of atrial fibrillation on left atrium haemodynamics: A computational fluid dynamics study

Cited by 29 publications

References 60 publications

Subject-specific factors affecting particle residence time distribution of left atrial appendage in atrial fibrillation: A computational model-based study

Subject-specific factors affecting particle residence time distribution of left atrial appendage in atrial fibrillation: A computational model-based study

Pulmonary vein flow split effects in patient-specific simulations of left atrial flow

A mathematical model that integrates cardiac electrophysiology, mechanics, and fluid dynamics: Application to the human left heart

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