A comprehensive comparison of various patient-specific CFD models of the left atrium for atrial fibrillation patients

Influence of the flow split ratio on the position of the main atrial vortex: Implications for stasis on the left atrial appendage

BACKGROUND

Despite the recent advances in computational fluid dynamics (CFD) techniques applied to blood flow within the left atrium (LA), the relationship between atrial geometry, flow patterns, and blood stasis within the left atrial appendage (LAA) remains unclear. A better understanding of this relationship would have important clinical implications, as thrombi originating in the LAA are a common cause of stroke in patients with atrial fibrillation (AF).

AIM

To identify the most representative atrial flow patterns on a patient-specific basis and study their influence on LAA blood stasis by varying the flow split ratio and some common atrial modeling assumptions.

METHODS

Three recent techniques were applied to nine patient-specific computational fluid dynamics (CFD) models of patients with AF: a kinematic atrial model to isolate the influence of wall motion because of AF, projection on a universal LAA coordinate system, and quantification of stagnant blood volume (SBV).

RESULTS

We identified three different atrial flow patterns based on the position of the center of the main circulatory flow. The results also illustrate how atrial flow patterns are highly affected by the flow split ratio, increasing the SBV within the LAA. As the flow split ratio is determined by the patient's lying position, the results suggest that the most frequent position adopted while sleeping may have implications for the medium- and long-term risks of stroke.

Computational fluid dynamics in cardiac surgery and perfusion: A review

Cardiovascular diseases persist as a leading cause of mortality and morbidity, despite significant advances in diagnostic and surgical approaches. Computational Fluid Dynamics (CFD) represents a branch of fluid mechanics widely used in industrial engineering but is increasingly applied to the cardiovascular system. This review delves into the transformative potential for simulating cardiac surgery procedures and perfusion systems, providing an in-depth examination of the state-of-the-art in cardiovascular CFD modeling. The study first describes the rationale for CFD modeling and later focuses on the latest advances in heart valve surgery, transcatheter heart valve replacement, aortic aneurysms, and extracorporeal membrane oxygenation. The review underscores the role of CFD in better understanding physiopathology and its clinical relevance, as well as the profound impact of hemodynamic stimuli on patient outcomes. By integrating computational methods with advanced imaging techniques, CFD establishes a quantitative framework for understanding the intricacies of the cardiac field, providing valuable insights into disease progression and treatment strategies. As technology advances, the evolving synergy between computational simulations and clinical interventions is poised to revolutionize cardiovascular care. This collaboration sets the stage for more personalized and effective therapeutic strategies. With its potential to enhance our understanding of cardiac pathologies, CFD stands as a promising tool for improving patient outcomes in the dynamic landscape of cardiovascular medicine.

Impact of left atrial wall motion assumptions in fluid simulations on proposed predictors of thrombus formation

Atrial fibrillation (AF) poses a significant risk of stroke due to thrombus formation, which primarily occurs in the left atrial appendage (LAA). Medical image-based computational fluid dynamics (CFD) simulations can provide valuable insight into patient-specific hemodynamics and could potentially enhance personalized assessment of thrombus risk. However, the importance of accurately representing the left atrial (LA) wall dynamics has not been fully resolved. In this study, we compared four modeling scenarios; rigid walls, a generic wall motion based on a reference motion, a semi-generic wall motion based on patient-specific motion, and patient-specific wall motion based on medical images. We considered a LA geometry acquired from 4D computed tomography during AF, systematically performed convergence tests to assess the numerical accuracy of our solution strategy, and quantified the differences between the four approaches. The results revealed that wall motion had no discernible impact on LA cavity hemodynamics, nor on the markers that indicate thrombus formation. However, the flow patterns within the LAA deviated significantly in the rigid model, indicating that the assumption of rigid walls may lead to errors in the estimated risk factors. In contrast, the generic, semi-generic, and patient-specific cases were qualitatively similar. The results highlight the crucial role of wall motion on hemodynamics and predictors of thrombus formation, and also demonstrate the potential of using a generic motion model as a surrogate for the more complex patient-specific motion. While the present study considered a single case, the employed CFD framework is entirely open-source and designed for adaptability, allowing for integration of additional models and generic motions.

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data

Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like theCHA 2 DS 2 -VASc score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations. Our cohort, evenly split between control and stroke groups, comprises eight patients. Utilizing CINE CMR, we compute kinematic features, revealing smaller left atrial volumes for stroke patients. The incorporation of patient-specific atrial displacement into our hemodynamic simulations unveils the influence of atrial compliance on the flow fields, emphasizing the importance of LA motion in CFD simulations and challenging the conventional rigid wall assumption in hemodynamics models. Standardizing hemodynamic features with functional metrics enhances the differentiation between stroke and control cases. While standalone assessments provide limited clarity, the synergistic fusion of CMR-derived functional data and patient-informed CFD simulations offers a personalized and mechanistic understanding, distinctly segregating stroke from control cases. Specifically, our investigation reveals a crucial clinical insight: normalizing hemodynamic features based on ejection fraction fails to differentiate between stroke and control patients. Differently, when normalized with stroke volume, a clear and clinically significant distinction emerges and this holds true for both the left atrium and its appendage, providing valuable implications for precise stroke risk assessment in clinical settings. This work introduces a novel framework for seamlessly integrating hemodynamic and functional metrics, laying the groundwork for improved predictive models, and highlighting the significance of motion-informed, personalized risk assessments.

On the importance of fundamental computational fluid dynamics toward a robust and reliable model of left atrial flows

Computational fluid dynamics (CFD) studies of left atrial flows have reached a sophisticated level, for example, revealing plausible relationships between hemodynamics and stresses with atrial fibrillation. However, little focus has been on fundamental fluid modeling of LA flows. The purpose of this study was to investigate the spatiotemporal convergence, along with the differences between high- (HR) versus normal-resolution/accuracy (NR) solution strategies, respectively. Rigid wall CFD simulations were conducted on 12 patient-specific left atrial geometries obtained from computed tomography scans, utilizing a second-order accurate and space/time-centered solver. The convergence studies showed an average variability of around 30% and 55% for time averaged wall shear stress (WSS), oscillatory shear index (OSI), relative residence time (RRT), and endothelial cell activation potential (ECAP), even between intermediate spatial and temporal resolutions, in the left atrium (LA) and left atrial appendage (LAA), respectively. The comparison between HR and NR simulations showed good correlation in the LA for WSS, RRT, and ECAP (R 2 > .9 ), but not for OSI (R 2 = .63 ). However, there were poor correlations in the LAA especially for OSI, RRT, and ECAP (R 2 = .55, .63, and .61, respectively), except for WSS (R 2 = .81 ). The errors are comparable to differences previously reported with disease correlations. To robustly predict atrial hemodynamics and stresses, numerical resolutions of 10 M elements (i.e., Δ x = ∼ .5 mm) and 10 k time-steps per cycle seem necessary (i.e., one order of magnitude higher than normally used in both space and time). In conclusion, attention to fundamental numerical aspects is essential toward establishing a plausible, robust, and reliable model of LA flows.

The impact of contrast retention on thrombus formation risks in patients with atrial fibrillation: A numerical study

Background

Contrast retention (CR) is an important predictor of left atrial appendage thrombus (LAAT) and stroke in patients with non-valvular atrial fibrillation (AF). We sought to explore the underlying mechanisms of CR using computational fluid dynamic (CFD) simulations.

Methods

A total of 12 patients with AF who underwent both cardiac computed tomography angiography (CTA) and transesophageal echocardiography (TEE) before left atrial appendage occlusion (LAAO) were included in the study. The patients were allocated into the CR group or non-CR group based on left atrial appendage (LAA) angiography. Patient-specific models were reconstructed to evaluate time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and endothelial cell activation potential (ECAP). Additionally, the incidence of thrombosis was predicted using residence time (RT) at different time-points.

Results

TAWSS was lower [median (Interquartile Range) 0.27 (0.19-0.47) vs 1.35 (0.92-1.79), p < 0.001] in LAA compared to left atrium. In contrast, RRT [1438 (409.70-13869) vs 2.23 (1.81-3.14), p < 0.001] and ECAP [122.70 (30.01-625.70) vs 0.19 (0.16-0.27), p < 0.001)] was higher in the LAA. The patients in the CR group had significantly higher RRT [(mean ± SD) 16274 ± 11797 vs 639.70 ± 595.20, p = 0.009] and ECAP [610.80 ± 365.30 vs 54.26 ± 54.38, p = 0.004] in the LAA compared to the non-CR group. Additionally, patients with CR had a wider range of thrombus-prone regions [0.44(0.27-0.66)% vs 0.05(0.03-0.27)%, p = 0.009] at the end of the 15th cardiac cycle.

Conclusions

These findings suggest that CR might be an indicator of high-risk thrombus formation in the LAA. And CT-based CFD simulation may be a feasible substitute for the evaluation of LAA thrombotic risk in patients with AF, especially in patients with CR.

The role of the pulmonary veins on left atrial flow patterns and thrombus formation

Atrial fibrillation (AF) is the most common human arrhythmia, forming thrombi mostly in the left atrial appendage (LAA). However, the relation between LAA morphology, blood patterns and clot formation is not yet fully understood. Furthermore, the impact of anatomical structures like the pulmonary veins (PVs) have not been thoroughly studied due to data acquisition difficulties. In-silico studies with flow simulations provide a detailed analysis of blood flow patterns under different boundary conditions, but a limited number of cases have been reported in the literature. To address these gaps, we investigated the influence of PVs on LA blood flow patterns and thrombus formation risk through computational fluid dynamics simulations conducted on a sizeable cohort of 130 patients, establishing the largest cohort of patient-specific LA fluid simulations reported to date. The investigation encompassed an in-depth analysis of several parameters, including pulmonary vein orientation (e.g., angles) and configuration (e.g., number), LAA and LA volumes as well as their ratio, flow, and mass-less particles. Our findings highlight the total number of particles within the LAA as a key parameter for distinguishing between the thrombus and non-thrombus groups. Moreover, the angles between the different PVs play an important role to determine the flow going inside the LAA and consequently the risk of thrombus formation. The alignment between the LAA and the main direction of the left superior pulmonary vein, or the position of the right pulmonary vein when it exhibits greater inclination, had an impact to distinguish the control group vs. the thrombus group. These insights shed light on the intricate relationship between PV configuration, LAA morphology, and thrombus formation, underscoring the importance of comprehensive blood flow pattern analyses.

A global solution to a hyperbolic problem for blood flow modelling

The paper aims to examine the hyperbolic system of equations governing one-dimensional haemodynamics and its relevance in analysing blood flow under mechanical influences, with particular emphasis on the impact of altering the angle of the leg axis. Methods and approaches for solving hyperbolic equations have been developed in light of their properties and characteristics. The primary objective of this study was to investigate the interplay between vein pressure, pulse wave velocity, and vascular distension. The study revealed an inverse relationship between vein pressure and pulse wave velocity. A decrease in pulse wave velocity occurs when vein pressure rises, and vice versa. Both real measurements and modelling results confirmed this dependence. The pressure in the veins is between 10.8 and 13.6 kPa, and the speed of the pulse wave is between 0.061 and 0.27 kPa. The agreement between real and model data was high. The modelled venous pressure and pulse wave velocity values are close to the actual values. However, it is essential to acknowledge the limitations of this paper. These limitations include the utilisation of one-dimensional haemodynamic models, which fail to consider the three-dimensional structure of the circulatory system. Additionally, the analysis is restricted to examining changes solely in the leg axis angle. The research helps to clarify the relationship between mechanical actions and haemodynamic parameters. The findings may help research and develop new methods for identifying and treating conditions associated with the cardiovascular system.

Computational study on hemodynamic effects of left superior pulmonary vein resection and associated physiological changes in the left atrium after left upper lobectomy

Left upper lobectomy (LUL) with left superior pulmonary vein (LSPV) resection alters the left atrium (LA) physiological states and LA hemodynamics associated with thrombosis, although this underlying mechanism is poorly understood. Therefore, we investigated the effects of LSPV resection and associated LA physiological changes on LA hemodynamics using four-dimensional computed tomography image-based computational simulations. Three cases were considered: the LA before and after LUL extracted from computed tomography images and artificial LSPV resection without physiological changes. Comparisons among the three cases demonstrated that physiological changes associated with LSPV resection are the possible factors that affect the LA hemodynamics after LUL.

Virtual surgery to predict optimized conduit size for adult Fontan patients with 16-mm conduits

OBJECTIVES

Recent evidence suggests that conduits implanted in Fontan patients at the age of 2-4 years become undersized for adulthood. The objective of this study is to use computational fluid dynamic models to evaluate the effect of virtual expansion of the Fontan conduit on haemodynamics and energetics of the total cavopulmonary connection (TCPC) under resting conditions and increased flow conditions.

METHODS

Patient-specific, magnetic resonance imaging-based simulation models of the TCPC were performed during resting and increased flow conditions. The original 16-mm conduits were virtually enlarged to 3 new sizes. The proposed conduit sizes were defined based on magnetic resonance imaging-derived conduit flow in each patient. Flow efficiency was evaluated based on power loss, pressure drop and resistance and thrombosis risk was based on flow stagnation volume and relative residence time (RRT).

RESULTS

Models of 5 adult patients with a 16-mm extracardiac Fontan connection were simulated and subsequently virtually expanded to 24-32 mm depending on patient-specific conduit flow. Virtual expansion led to a 40-65% decrease in pressure gradient across the TCPC depending on virtual conduit size. Despite improved energetics of the entire TCPC, the pulmonary arteries remained a significant contributor to energy loss (60-73% of total loss) even after virtual surgery. Flow stagnation volume inside the virtual conduit and surface area in case of elevated RRT (>20/Pa) increased after conduit enlargement but remained negligible (flow stagnation <2% of conduit volume in rest, <0.5% with exercise and elevated RRT <3% in rest, <1% with exercise).

CONCLUSIONS

Virtual expansion of 16-mm conduits to 24-32 mm, depending on patient-specific conduit flow, in Fontan patients significantly improves TCPC efficiency while thrombosis risk presumably remains low.

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

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 for the first time on blood stasis in the LAA, using a high-fidelity patient-specific computational fluid dynamics (CFD) model. We use an Immersed Boundary Method, simulating the flow in a fixed, uniform Cartesian mesh and imposing the movement of the LA walls with a moving Lagrangian mesh generated from 4D Computerized Tomography images. We analyzed LA anatomies from eight patients with varying atrial function, including three with AF and either a LAA thrombus or a history of Transient Ischemic Attacks (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. This knowledge is relevant to planning clinical procedures such as AF ablation or the implementation of LAA occluders.

Elevated atrial blood stasis in paroxysmal atrial fibrillation during sinus rhythm: a patient-specific computational fluid dynamics study

Introduction

Atrial fibrillation (AF) is associated with an increased risk of stroke, often caused by thrombi that form in the left atrium (LA), and especially in the left atrial appendage (LAA). The underlying mechanism is not fully understood but is thought to be related to stagnant blood flow, which might be present despite sinus rhythm. However, measuring blood flow and stasis in the LAA is challenging due to its small size and low velocities. We aimed to compare the blood flow and stasis in the left atrium of paroxysmal AF patients with controls using computational fluid dynamics (CFD) simulations.

Methods

The CFD simulations were based on time-resolved computed tomography including the patient-specific cardiac motion. The pipeline allowed for analysis of 21 patients with paroxysmal AF and 8 controls. Stasis was estimated by computing the blood residence time.

Results and Discussion

Residence time was elevated in the AF group (p < 0.001). Linear regression analysis revealed that stasis was strongest associated with LA ejection ratio (p < 0.001, R2 = 0.68) and the ratio of LA volume and left ventricular stroke volume (p < 0.001, R2 = 0.81). Stroke risk due to LA thrombi could already be elevated in AF patients during sinus rhythm. In the future, patient specific CFD simulations may add to the assessment of this risk and support diagnosis and treatment.

Computational modeling of hemodynamics and risk of thrombosis in the left atrial appendage using patient-specific blood viscosity and boundary conditions at the mitral valve

Hemodynamics play a vital role for the risk of thrombosis in the left atrial appendage (LAA) and left atrium (LA) for patients with atrial fibrillation. Accurate prediction of hemodynamics in the LA can provide important guidance for assessing the risk of thrombosis in the LAA. Patient specificity is a crucial factor in representing the true hemodynamic fields. In this study, we investigated the effects of blood rheology (as a function of hematocrit and shear rate), as well as patient-specific mitral valve (MV) boundary conditions (MV area and velocity profiles measured by ultrasound) on the hemodynamics and thrombosis potential of the LAA. Four scenarios were setup with different degrees of patient specificity. Though using a constant blood viscosity can classify the thrombus and non-thrombus patients for all the hemodynamic indicators, the risk of thrombosis was underestimated for all patients compared with patient-specific viscosities. The results with least patient specificities showed that patients prone to thrombosis predicted by three hemodynamic indicators were inconsistent with clinical observations. Moreover, though patients had the same MV inlet flow rate, different MV models lead to different trends in the risk of thrombosis in different patients. We also found that endothelial cell activation potential and relative residence time can effectively distinguish thrombus and non-thrombus patients for all the scenarios, relatively insensitive to patient specificities. Overall, the findings of this study provide useful insights on patients-specific hemodynamic simulations of the LA.

Personalized biomechanical insights in atrial fibrillation: opportunities & challenges

INTRODUCTION

Atrial fibrillation (AF) is an increasingly prevalent and significant worldwide health problem. Manifested as an irregular atrial electrophysiological activation, it is associated with many serious health complications. AF affects the biomechanical function of the heart as contraction follows the electrical activation, subsequently leading to reduced blood flow. The underlying mechanisms behind AF are not fully understood, but it is known that AF is highly correlated with the presence of atrial fibrosis, and with a manifold increase in risk of stroke.

AREAS COVERED

In this review, we focus on biomechanical aspects in atrial fibrillation, current and emerging use of clinical images, and personalized computational models. We also discuss how these can be used to provide patient-specific care.

EXPERT OPINION

Understanding the connection betweenatrial fibrillation and atrial remodeling might lead to valuable understanding of stroke and heart failure pathophysiology. Established and emerging imaging modalities can bring us closer to this understanding, especially with continued advancements in processing accuracy, reproducibility, and clinical relevance of the associated technologies. Computational models of cardiac electromechanics can be used to glean additional insights on the roles of AF and remodeling in heart function.

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

Background

Atrial 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.

Methods

Subject-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.

Results

Both 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.

Conclusions

Subject-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.

Recent developments in modeling, imaging, and monitoring of cardiovascular diseases using machine learning

Cardiovascular diseases are the leading cause of mortality, morbidity, and hospitalization around the world. Recent technological advances have facilitated analyzing, visualizing, and monitoring cardiovascular diseases using emerging computational fluid dynamics, blood flow imaging, and wearable sensing technologies. Yet, computational cost, limited spatiotemporal resolution, and obstacles for thorough data analysis have hindered the utility of such techniques to curb cardiovascular diseases. We herein discuss how leveraging machine learning techniques, and in particular deep learning methods, could overcome these limitations and offer promise for translation. We discuss the remarkable capacity of recently developed machine learning techniques to accelerate flow modeling, enhance the resolution while reduce the noise and scanning time of current blood flow imaging techniques, and accurate detection of cardiovascular diseases using a plethora of data collected by wearable sensors.

Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke

Atrial fibrillation (AF) underlies almost one third of all ischaemic strokes, with the left atrial appendage (LAA) identified as the primary thromboembolic source. Current stroke risk stratification approaches, such as the CHA₂DS₂-VASc score, rely mostly on clinical comorbidities, rather than thrombogenic mechanisms such as blood stasis, hypercoagulability and endothelial dysfunction-known as Virchow's triad. While detection of AF-related thrombi is possible using established cardiac imaging techniques, such as transoesophageal echocardiography, there is a growing need to reliably assess AF-patient thrombogenicity prior to thrombus formation. Over the past decade, cardiac imaging and image-based biophysical modelling have emerged as powerful tools for reproducing the mechanisms of thrombogenesis. Clinical imaging modalities such as cardiac computed tomography, magnetic resonance and echocardiographic techniques can measure blood flow velocities and identify LA fibrosis (an indicator of endothelial dysfunction), but imaging remains limited in its ability to assess blood coagulation dynamics. In-silico cardiac modelling tools-such as computational fluid dynamics for blood flow, reaction-diffusion-convection equations to mimic the coagulation cascade, and surrogate flow metrics associated with endothelial damage-have grown in prevalence and advanced mechanistic understanding of thrombogenesis. However, neither technique alone can fully elucidate thrombogenicity in AF. In future, combining cardiac imaging with in-silico modelling and integrating machine learning approaches for rapid results directly from imaging data will require development under a rigorous framework of verification and clinical validation, but may pave the way towards enhanced personalised stroke risk stratification in the growing population of AF patients. This Review will focus on the significant progress in these fields.

Numerical study of the risk of thrombosis in the left atrial appendage of chicken wing shape in atrial fibrillation

Atrial fibrillation (AF) is a common and life-threatening disease. For the patients with AF, more than 90% of the thrombi are formed in the left atrial appendage (LAA), thrombus dislodgement can cause vascular embolism, making them is becoming a high-risk group for stroke. Therefore, identifying the patients with high risk of thrombosis is crucial for advanced stroke warning. To better investigate the mechanism behind thrombus formation in the LAA, this study reconstructed the 3-D Left Atrium (LA) models of six AF volunteer patients by corresponding Computed Tomography (CT) images. Combine the advantages of Computational Fluid Dynamics (CFD), the blood flow field in LA both in AF and sinus heart rate states were studied. The risk of thrombus was evaluated based on the blood viscosity, shear rate thrombus prediction model and Time Average Wall Shear Stress (TAWSS), Oscillatory Shear Index (OSI), and Relative Residence Time (RRT) values. The results showed that the left atrium had lower blood flow velocity and TAWSS values at the LAA in both AF and sinus rhythm, thus the LAA is the most thrombogenic region in the LA. Besides, the RRT value of LAA was generally higher in AF than in sinus rhythm. Therefore, AF carries a higher risk of thrombosis.

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

We analyse the haemodynamics of the left atrium, highlighting differences between healthy individuals and patients affected by atrial fibrillation. The computational study is based on patient-specific geometries of the left atria to simulate blood flow dynamics. We design a novel procedure to compute the boundary data for the 3D haemodynamic simulations, which are particularly useful in absence of data from clinical measurements. With this aim, we introduce a parametric definition of atrial displacement, and we use a closed-loop lumped parameter model of the whole cardiovascular circulation conveniently tuned on the basis of the patient's characteristics. We evaluate several fluid dynamics indicators for atrial haemodynamics, validating our numerical results in terms of clinical measurements; we investigate the impact of geometric and clinical characteristics on the risk of thrombosis. To highlight the correlation of thrombus formation with atrial fibrillation, according to medical evidence, we propose a novel indicator: age stasis. It arises from the combination of Eulerian and Lagrangian quantities. This indicator identifies regions where slow flow cannot properly rinse the chamber, accumulating stale blood particles, and creating optimal conditions for clots formation.

Stroke risk evaluation for patients with atrial fibrillation: Insights from left atrial appendage

Left atrial appendage (LAA) is believed to be a common site of thrombus formation in patients with atrial fibrillation (AF). However, the commonly-applied stroke risk stratification model (such as. CHA2DS2-VASc score) does not include any structural or hemodynamic features of LAA. Recent studies have suggested that it is important to incorporate LAA geometrical and hemodynamic features to evaluate the risk of thrombus formation in LAA, which may better delineate the AF patients for anticoagulant administration and prevent strokes. This review focuses on the LAA-related factors that may be associated with thrombus formation and cardioembolic events.

Increased Blood Residence Time as Markers of High-Risk Patent Foramen Ovale

Previous investigations have suggested that patients with patent foramen ovale (PFO) often have an atrial dysfunction, like to that observed in patients with atrial fibrillation (AF) which may concur to an increased risk of cryptogenic stroke. The aim of the study is to compare the atrial resident time (Rt) of PFO patients to those with sinus rhythm (SR) and AF using patient-specific 3D computational fluid dynamics (CFD) analysis. Models of left atrium (LA) hemodynamics were obtained from time-resolved CT scans and transthoracic echocardiography (TTE). Enrolled patients were divided into three groups: 30 healthy subjects with SR, 30 with PFO, and 30 with AF without PFO. Blood stasis was evaluated by determining the blood residence time (Rt) distribution in the LA and left atrial appendage (LAA). Overall, 90 patients (mean age 47.4 ± 7.5 years, 51 males) were included into the analysis. PFO patients exhibit higher mean Rt values compared to healthy subjects (2.65 ± 0.2 vs 1.5 ± 0.2 s). Conversely, AF patients presented higher Rt when compared to PFO patients (2.9 ± 0.3 vs 2.3 ± 0.2 s). Moreover, PFO patients presenting cerebral lesions at magnetic resonance imaging have a higher Rt compared to those without (2.9 ± 0.3 vs 2.3 ± 0.2 s, respectively, p < 0.001). PFO patients have a higher degree of atrial Rt compared to healthy subjects similar to that observed in AF patients. The higher mean LA Rt values offer an insight into the pathophysiological mechanism linking PFO with cryptogenic stroke and might be a marker of high-risk PFOs.

On the Impact of Left Upper Lobectomy on the Left Atrial Hemodynamics

The left atrium (LA) functions to transport oxygenated blood from the pulmonary veins (PVs) to the left ventricle (LV). LA hemodynamics has received much attention because thrombosis in the LA in pathological states, such as atrial fibrillation, is a major factor leading to thromboembolic stroke. In the last 5 years, multiple cohort studies have revealed that left upper lobectomy (LUL) with PV resection risks thrombus formation in the PV stump even in the normal LA without a history of cardiac disease; the causal mechanism is, however, an open question. The present study investigated the potential effect of an LUL on LA hemodynamics associated with thrombus formation through computational simulation using four-dimensional computed tomography (4D-CT) images. Time series of patient-specific LA geometries before and after LUL were extracted from the 4D-CT images and these motions were estimated through non-rigid registration. Adopting the LA geometries and prescribed moving wall boundary conditions, the LA blood flow was determined using a Cartesian-grid computational fluid dynamics solver. The obtained results show that the LUL resulted in blood flow impingement from the left and right PV inflows into the LA upper region throughout most of the cardiac cycle. This characteristic alteration of the LA hemodynamics generated fine-scale vortices with viscous energy dissipations, enhancing the flow stasis associated with thrombus formation in the PV stump. These findings show that an LUL affects the hemodynamics not only in the PV stump but also throughout the LA region. They also highlight the importance of computational analysis of LA hemodynamics in understanding the underlying mechanism of LUL-induced thrombus formation.

Estimation of coronary artery movement using a non-rigid registration with global-local structure preservation

BACKGROUND

At present, coronary artery disease (CAD) is the leading cause of death worldwide. Many studies have shown that CAD is strongly associated with the motion characteristics of the coronary arteries. Although cardiovascular imaging technology has been widely used for the diagnosis of CAD, the motion parameters of the heart and coronary arteries cannot be directly calculated from the images. In this paper, we propose a point set registration method with global and local topology constraints to quantify coronary artery movement.

METHODS

The global constraint is the motion coherence of the point set which enforces the smoothness of the displacement field. The local linear embedding based topological structure and the local feature descriptor i.e., the 3D shape context, are designed to retain the local structure of the point set. We incorporate these constraints into a maximum likelihood framework and derive an expectation-maximization algorithm to obtain the transformation function between the two point sets. The proposed method was compared with four existing algorithms using simulated data and applied to the real data obtained from 4D CT angiograms.

RESULTS

For the simulation data, the proposed method achieves a lower registration error than the comparison algorithms. For the real data, the proposed method shows that, in most cases, the right coronary artery achieves a larger velocity than the left anterior descending and left circumflex branches, and there are three well-defined velocity peaks, during the cardiac cycle for these branches.

CONCLUSION

The proposed approach is feasible and effective in quantifying coronary artery movement and thus adds to the diagnostic power of coronary imaging.

Inherited and Acquired Rhythm Disturbances in Sick Sinus Syndrome, Brugada Syndrome, and Atrial Fibrillation: Lessons from Preclinical Modeling

Rhythm disturbances are life-threatening cardiovascular diseases, accounting for many deaths annually worldwide. Abnormal electrical activity might arise in a structurally normal heart in response to specific triggers or as a consequence of cardiac tissue alterations, in both cases with catastrophic consequences on heart global functioning. Preclinical modeling by recapitulating human pathophysiology of rhythm disturbances is fundamental to increase the comprehension of these diseases and propose effective strategies for their prevention, diagnosis, and clinical management. In silico, in vivo, and in vitro models found variable application to dissect many congenital and acquired rhythm disturbances. In the copious list of rhythm disturbances, diseases of the conduction system, as sick sinus syndrome, Brugada syndrome, and atrial fibrillation, have found extensive preclinical modeling. In addition, the electrical remodeling as a result of other cardiovascular diseases has also been investigated in models of hypertrophic cardiomyopathy, cardiac fibrosis, as well as arrhythmias induced by other non-cardiac pathologies, stress, and drug cardiotoxicity. This review aims to offer a critical overview on the effective ability of in silico bioinformatic tools, in vivo animal studies, in vitro models to provide insights on human heart rhythm pathophysiology in case of sick sinus syndrome, Brugada syndrome, and atrial fibrillation and advance their safe and successful translation into the cardiology arena.