In silico Optimization of Left Atrial Appendage Occluder Implantation Using Interactive and Modeling Tools

Position Statement on Cardiac Computed Tomography Following Left Atrial Appendage Occlusion

Left atrial appendage occlusion (LAAO) is rapidly growing as valid stroke prevention therapy in atrial fibrillation. Cardiac imaging plays an instrumental role in preprocedural planning, procedural execution, and postprocedural follow-up. Recently, cardiac computed tomography (CCT) has made significant advancements, resulting in increasing use both preprocedurally and in outpatient follow-up. It provides a noninvasive, high-resolution alternative to the current standard, transesophageal echocardiography, and may display advantages in both the detection and characterization of device-specific complications, such as peridevice leak and device-related thrombosis. The implementation of CCT in the follow-up after LAAO has identified new findings such as hypoattenuated thickening on the atrial device surface and left atrial appendage contrast patency, which are not readily assessable on transesophageal echocardiography. Currently, there is a lack of standardization for acquisition and interpretation of images and consensus on definitions of essential findings on CCT in the postprocedural phase. This paper intends to provide a practical and standardized approach to both acquisition and interpretation of CCT after LAAO based on a comprehensive review of the literature and expert consensus among European and North American interventional and imaging specialists.

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.

Left atrial appendage occlusion: On the need of a numerical model to simulate the implant procedure

Left atrial appendage occlusion (LAAO) is a percutaneous procedure to prevent thromboembolism in patients affected by atrial fibrillation. Despite its demonstrated efficacy, the LAA morphological complexity hinders the procedure, resulting in postprocedural drawbacks (device-related thrombus and peri-device leakage). Local anatomical features may cause difficulties in the device's positioning and affect the effectiveness of the device's implant. The current work proposes a detailed FE model of the LAAO useful to investigate implant scenarios and derive clinical indications. A high-fidelity model of the Watchman FLX device and simplified parametric conduits mimicking the zone of the LAA where the device is deployed were developed. Device-conduit interactions were evaluated by looking at clinical indicators such as device-wall gap, possible cause of leakage, and device protrusion. As expected, the positioning of the crimped device before the deployment was found to significantly affect the implant outcomes: clinician's choices can be improved if FE models are used to optimize the pre-operative planning. Remarkably, also the wall mechanical stiffness plays an important role. However, this parameter value is unknown for a specific LAA, a crucial point that must be correctly defined for developing an accurate FE model. Finally, numerical simulations outlined how the device's configuration on which the clinician relies to assess the implant success (i.e., the deployed configuration with the device still attached to the catheter) may differ from the actual final device's configuration, relevant for achieving a safe intervention.

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 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 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 the CHA2DS2-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.

Research on the Internal Flow Field of Left Atrial Appendage and Stroke Risk Assessment with Different Blood Models

Extant clinical research has underscored that patients suffering from atrial fibrillation (AF) bear an elevated risk for stroke, predominantly driven by the formation of thrombus in the left atrial appendage (LAA). As such, accurately identifying those at an increased risk of thrombosis becomes paramount to facilitate timely and effective treatment. This study was designed to shed light on the mechanisms underlying thrombus formation in the LAA by employing three-dimensional (3D) left atrium (LA) models of AF patients, which were constructed based on Computed Tomography (CT) imaging. The distinct benefits of Computational Fluid Dynamics (CFD) were leveraged to simulate the blood flow field within the LA, using three distinct blood flow models, both under AF and sinus rhythm (SR) conditions. The potential risk of thrombus formation was evaluated by analyzing the Relative Residence Time (RRT) and Endothelial Cell Activation Potential (ECAP) values. The results gleaned from this study affirm that all three blood flow models align with extant clinical guidelines, thereby enabling an effective prediction of thrombosis risk. However, noteworthy differences emerged when comparing the intricacies of the flow field and thrombosis risk across the three models. The single-phase non-Newtonian blood flow model resulted in comparatively lower residence times for blood within the LA and lower values for the Oscillatory Shear Index (OSI), RRT, and ECAP within the LAA. These findings suggest a reduced thrombosis risk. Conversely, the two-phase non-Newtonian blood flow model exhibited a higher residence time for blood and elevated RRT value within the LAA, suggesting an increased risk for thrombosis.

Cardiac magnetic resonance imaging for preprocedural planning of percutaneous left atrial appendage closure

Introduction

Percutaneous closure of the left atrial appendage (LAA) facilitates stroke prevention in patients with atrial fibrillation. Optimal device selection and positioning are often challenging due to highly variable LAA shape and dimension and thus require accurate assessment of the respective anatomy. Transesophageal echocardiography (TEE) and x-ray fluoroscopy (XR) represent the gold standard imaging techniques. However, device underestimation has frequently been observed. Assessment based on 3-dimensional computer tomography (CTA) has been reported as more accurate but increases radiation and contrast agent burden. In this study, the use of non-contrast-enhanced cardiac magnetic resonance imaging (CMR) to support preprocedural planning for LAA closure (LAAc) was investigated.

Methods

CMR was performed in thirteen patients prior to LAAc. Based on the 3-dimensional CMR image data, the dimensions of the LAA were quantified and optimal C-arm angulations were determined and compared to periprocedural data. Quantitative figures used for evaluation of the technique comprised the maximum diameter, the diameter derived from perimeter and the area of the landing zone of the LAA.

Results

Perimeter- and area-based diameters derived from preprocedural CMR showed excellent congruency compared to those measured periprocedurally by XR, whereas the respective maximum diameter resulted in significant overestimation (p < 0.05). Compared to TEE assessment, CMR-derived diameters resulted in significantly larger dimensions (p < 0.05). The deviation of the maximum diameter to the diameters measured by XR and TEE correlated well with the ovality of the LAA. C-arm angulations used during the procedures were in agreement with those determined by CMR in case of circular LAA.

Discussion

This small pilot study demonstrates the potential of non-contrast-enhanced CMR to support preprocedural planning of LAAc. Diameter measurements based on LAA area and perimeter correlated well with the actual device selection parameters. CMR-derived determination of landing zones facilitated accurate C-arm angulation for optimal device positioning.

Impact of left atrial appendage occlusion device position on potential determinants of device-related thrombus: a patient-specific in silico study

BACKGROUND

Device-related thrombus (DRT) after left atrial appendage occlusion (LAAO) is potentially linked to adverse events. Although clinical reports suggest an effect of the device type and position on the DRT risk, in-depth studies of its mechanistic basis are needed. This in silico study aimed to assess the impact of the position of non-pacifier (Watchman) and pacifier (Amulet) LAAO devices on surrogate markers of DRT risk.

METHODS

The LAAO devices were modeled with precise geometry and virtually implanted in different positions into a patient-specific left atrium. Using computational fluid dynamics, the following values were quantified: residual blood, wall shear stress (WSS) and endothelial cell activation potential (ECAP).

RESULTS

In comparison to an ostium-fitted device position, deep implantation led to more residual blood, lower average WSS and higher ECAP surrounding the device, especially on the device's atrial surface and the surrounding tissue, suggesting increased risk for potential thrombus. For the non-pacifier device, an off-axis device orientation resulted in even more residual blood, higher ECAP and similar average WSS as compared to an ostium-fitted device position. Overall, the pacifier device showed less residual blood, higher average WSS and lower ECAP, compared to the non-pacifier device.

CONCLUSIONS

In this in silico study, both LAAO device type and implant position showed an impact on potential markers of DRT in terms of blood stasis, platelet adhesion and endothelial dysfunction. Our results present a mechanistic basis for clinically observed risk factors of DRT and the proposed in silico model may aid in the optimization of device development and procedural aspects.

Left Atrial Thrombus-Are All Atria and Appendages Equal?

Although the left atrial appendage (LAA) seems useless, it has several critical functions that are not fully known yet, such as the causes for being the main origin of cardioembolic stroke. Difficulties arise due to the extreme range of LAA morphologic variability, making the definition of normality challenging and hampering the stratification of thrombotic risk. Furthermore, obtaining quantitative metrics of its anatomy and function from patient data is not straightforward. A multimodality imaging approach, using advanced computational tools for their analysis, allows a complete characterization of the LAA to individualize medical decisions related to left atrial thrombosis patients.

Pre-cath Laboratory Planning for Left Atrial Appendage Occlusion - Optional or Essential?

In the wake of rapid advancement in cardiovascular procedural technologies, physician-led preprocedural planning utilizing multi-modality imaging training is increasingly recognized as invaluable for procedural accuracy. Left atrial appendage occlusion (LAAO) is one such procedure in which complications such as device leak, cardiac injury, and device embolization can be decreased substantially with incorporation of physician driven imaging and digital tools. We discuss the benefits of cardiac CT and 3D printing in preprocedural planning for the Heart Team, as well as novel applications by physicians of intraprocedural 3D angiography and dynamic fusion imaging. Furthermore, incorporation of computational modeling and artificial intelligence (AI) may yield promise. For optimal patient-centric procedural success, we advocate for standardized preprocedural imaging planning by physicians within the Heart Team as an essential part of LAAO.

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.

Finding low CHA2DS2-VASc scores unreliable? Why not give morphological and hemodynamic methods a try?

Patients with atrial fibrillation (AF) suffer from a high risk of thrombosis. Currently, the CHA2DS2-VASc score is the most widely used tool for risk stratification in patients with AF, but it has disappointing accuracy and limited predictive value, especially in those with low scores. Thrombi in patients with AF mostly grow in their left atrial appendages (LAA), which is directly related to the abnormal morphology of the LAA or the left atrium and the unusual hemodynamic state around LAA, which may sensitively evaluate the risk of thrombosis complications in patients with AF and bring bases to clinical plans of medication and operation. Therefore, we investigated the research progress of hemodynamic and morphological studies about the predictive value of thrombosis risk in patients with AF, intending to discuss the prediction potential of morphological and hemodynamic indexes when compared with the presently used CHA2DS2-VASc system and how to build a more precise thromboembolic event prediction model for patients with AF.

Preliminary findings on left atrial appendage occlusion simulations applying different endocardial devices

Atrial fibrillation (AF) is one of the most investigated arrhythmias since it is associated with a five-fold increase in the risk of strokes. Left atrium dilation and unbalanced and irregular contraction caused by AF favour blood stasis and, consequently, stroke risk. The left atrial appendage (LAA) is the site of the highest clots formation, increasing the incidence of stroke in AF population. For many years oral anticoagulation therapy has been the most used AF treatment option available to decrease stroke risk. Unfortunately, several contraindications including bleeding risk increase, interference with other drugs and with multiorgan functioning, might outweigh its remarkable benefits on thromboembolic events. For these reasons, in recent years, other approaches have been designed, including LAA percutaneous closure. Unfortunately, nowadays, LAA occlusion (LAAO) is restricted to small subgroups of patients and require a certain level of expertise and training to successfully complete the procedure without complications. The most critical clinical problems associated with LAAO are represented by peri-device leaks and device related thrombus (DRT). The anatomical variability of the LAA plays a key role in the choice of the correct LAA occlusion device and in its correct positioning with respect to the LAA ostium during the implant. In this scenario, computational fluid dynamics (CFD) simulations could have a crucial role in improving LAAO intervention. The aim of this study was to simulate the fluid dynamics effects of LAAO in AF patients to predict hemodynamic changes due to the occlusion. LAAO was simulated by applying two different types of closure devices based on the plug and the pacifier principles on 3D LA anatomical models derived from real clinical data in five AF patients. CFD simulations were performed on the left atrium model before and after the LAAO intervention with each device. Blood velocity, particle washout and endothelial damage were computed to quantify flow pattern changes after the occlusion in relation to the thrombogenic risk. Our preliminary results confirmed an improved blood washout after the simulated implants and the capability of foreseeing thrombogenic risk based on endothelial damage and maximum blood velocities in different scenarios. This tool may help to identify effective device configurations in limiting stroke risk for patient-specific LA morphologies.

Left Atrial Appendage Occlusion: Current Advances and Remaining Challenges

The field of left atrial appendage occlusion is rapidly evolving. However, several issues remain including the limited randomized efficacy data, peri-device leak, device-related thrombus, and the ongoing refinement of procedural techniques. In this article, we provide a contemporary overview of left atrial appendage occlusion focusing on 4 key remaining challenges: efficacy data, peri-device leak, device-related thrombus, and procedural optimization.

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.

Domain expert evaluation of advanced visual computing solutions and 3D printing for the planning of the left atrial appendage occluder interventions

Advanced visual computing solutions and three-dimensional (3D) printing are moving from engineering to clinical pipelines for training, planning, and guidance of complex interventions. 3D imaging and rendering, virtual reality (VR), and in-silico simulations, as well as 3D printing technologies provide complementary information to better understand the structure and function of the organs, thereby improving and personalizing clinical decisions. In this study, we evaluated several advanced visual computing solutions, such as web-based 3D imaging visualization, VR, and computational fluid simulations, together with 3D printing, for the planning of the left atrial appendage occluder (LAAO) device implantations. Six cardiologists tested different technologies in pre-operative data of five patients to identify the usability, limitations, and requirements for the clinical translation of each technology through a qualitative questionnaire. The obtained results demonstrate the potential impact of advanced visual computing solutions and 3D printing to improve the planning of LAAO interventions as well as the need for their integration into a single workflow to be used in a clinical environment.

Computed tomography angiography/magnetic resonance imaging-based preprocedural planning and guidance in the interventional treatment of structural heart disease

Preprocedural planning and periprocedural guidance based on image fusion are widely established techniques supporting the interventional treatment of structural heart disease. However, these two techniques are typically used independently. Previous works have already demonstrated the benefits of integrating planning details into image fusion but are limited to a few applications and the availability of the proprietary tools used. We propose a vendor-independent approach to integrate planning details into periprocedural image fusion facilitating guidance during interventional treatment. In this work, we demonstrate the feasibility of integrating planning details derived from computer tomography and magnetic resonance imaging into periprocedural image fusion with open-source and commercially established tools. The integration of preprocedural planning details into periprocedural image fusion has the potential to support safe and efficient interventional treatment of structural heart disease.

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.

Evaluation of Stroke Risk in Patients With Atrial Fibrillation Using Morphological and Hemodynamic Characteristics

Background

It is well known that the thrombus triggering stroke in patients with atrial fibrillation (AF) mainly comes from the left atrial appendage (LAA). This study aims to characterize the morphological and hemodynamic parameters and evaluate their differences between AF patients with and without a stroke history.

Methods

Cardiac CT images were obtained from AF patients with (n = 10) and without a history of stroke (n = 10). 3D models of the left atrium (LA) were reconstructed by processing the CT image, and the LA/LAA morphological parameters were measured. Computational fluid dynamics (CFD) simulations were performed to calculate the hemodynamic parameters in LA. The species-transport model and discrete phase model (DPM) were applied to analyze blood residual ratio and particle residual ratio, two qualitative parameters for thrombus formation and flow-out potential, respectively.

Results

There were significant differences in LAA actual depth (p = 0.002), and direct length (p = 0.049) between the non-stroke and stroke groups. Significant differences were also found in certain hemodynamic parameters. The blood residual ratio in LAA was significantly smaller in the stroke group than in the non-stroke group (p < 0.05). Moreover, the particle residual ratio within LAA was significantly smaller in the stroke groups than in the non-stroke group (p < 0.05).

Conclusion

There are significant differences in both morphological and hemodynamic parameters between AF patients with and without a stroke history. A high blood residual ratio in LAA confirms that thrombus is more likely to form in AF patients. A significantly smaller particle residual ratio in the stroke group may suggest the thrombus formed with LAA is more likely to flow out of LAA, leading to a higher risk of stroke. The proposed morphological and hemodynamic parameters may be additional risk factors that can be used to better risk stratify AF patients.

Automated MSCT Analysis for Planning Left Atrial Appendage Occlusion Using Artificial Intelligence

Background

The number of multislice computed tomography (MSCT) analyses performed for planning structural heart interventions is rapidly increasing. Further automation is required to save time, increase standardization, and reduce the learning curve.

Objective

The purpose of this study was to investigate the feasibility of a fully automated artificial intelligence (AI)-based MSCT analysis for planning structural heart interventions, focusing on left atrial appendage occlusion (LAAO) as the selected use case.

Methods

Different deep learning models were trained, validated, and tested using a cohort of 583 patients for which manually annotated data were available. These models were used independently or in combination to detect the anatomical ostium, the landing zone, the mitral valve annulus, and the fossa ovalis and to segment the left atrium (LA) and left atrial appendage (LAA). The accuracy of the models was evaluated through comparison with the manually annotated data.

Results

The automated analysis was performed on 25 randomly selected patients of the test cohort. The results were compared to the manually identified landmarks. The predicted segmentation of the LA(A) was similar to the manual segmentation (dice score of 0.94 ± 0.02). The difference between the automatically predicted and manually measured perimeter-based diameter was −0.8 ± 1.3 mm (anatomical ostium), −1.0 ± 1.5 mm (Amulet landing zone), and −0.1 ± 1.3 mm (Watchman FLX landing zone), which is similar to the operator variability on these measurements. Finally, the detected mitral valve annulus and fossa ovalis were close to the manual detection of these landmarks, as shown by the Hausdorff distance (3.9 ± 1.2 mm and 4.8 ± 1.8 mm, respectively). The average runtime of the complete workflow, including data pre- and postprocessing, was 57.5 ± 34.5 seconds.

Conclusions

A fast and accurate AI-based workflow is proposed to automatically analyze MSCT images for planning LAAO. The approach, which can be easily extended toward other structural heart interventions, may help to handle the rapidly increasing volumes of patients.

Left Atrial Thrombus-Are All Atria and Appendages Equal?

Although the left atrial appendage (LAA) seems useless, it has several critical functions that are not fully known yet, such as the causes for being the main origin of cardioembolic stroke. Difficulties arise due to the extreme range of LAA morphologic variability, making the definition of normality challenging and hampering the stratification of thrombotic risk. Furthermore, obtaining quantitative metrics of its anatomy and function from patient data is not straightforward. A multimodality imaging approach, using advanced computational tools for their analysis, allows a complete characterization of the LAA to individualize medical decisions related to left atrial thrombosis patients.

Pre-cath Laboratory Planning for Left Atrial Appendage Occlusion - Optional or Essential?

In the wake of rapid advancement in cardiovascular procedural technologies, physician-led preprocedural planning utilizing multi-modality imaging training is increasingly recognized as invaluable for procedural accuracy. Left atrial appendage occlusion (LAAO) is one such procedure in which complications such as device leak, cardiac injury, and device embolization can be decreased substantially with incorporation of physician driven imaging and digital tools. We discuss the benefits of cardiac CT and 3D printing in preprocedural planning for the Heart Team, as well as novel applications by physicians of intraprocedural 3D angiography and dynamic fusion imaging. Furthermore, incorporation of computational modeling and artificial intelligence (AI) may yield promise. For optimal patient-centric procedural success, we advocate for standardized preprocedural imaging planning by physicians within the Heart Team as an essential part of LAAO.

Joint Analysis of Morphological Parameters and In Silico Haemodynamics of the Left Atrial Appendage for Thrombogenic Risk Assessment

Background. Atrial fibrillation (AF) is considered the most common human arrhythmia. In nonvalvular AF, around 99% of thrombi are formed in the left atrial appendage (LAA). Nevertheless, there is not a consensus in the community about the relevant factors to stratify the AF population according to thrombogenic risk. Objective. To demonstrate the need for combining left atrial morphological and haemodynamics indices to improve the thrombogenic risk assessment in nonvalvular AF patients. Methods. A cohort of 71 nonvalvular AF patients was analysed. Statistical analysis, regression models, and random forests were used to analyse the differences between morphological and haemodynamics parameters, extracted from computational simulations built on 3D rotational angiography images, between patients with and without transient ischemic attack (TIA) or cerebrovascular accident (CVA). Results. The analysis showed that models composed of both morphological and haemodynamic factors were better predictors of TIA/CVA compared with models based on either morphological or haemodynamic factors separately. Maximum ostium diameter, length of the centreline, blood flow velocity within the LAA, oscillatory shear index, and time average wall shear stress parameters were found to be key risk factors for TIA/CVA prediction. In addition, TIA/CVA patients presented more flow stagnation within the LAA. Conclusion. Thrombus formation in the LAA is the result of multiple factors. Analyses based only on morphological or haemodynamic parameters are not precise enough to predict such a phenomenon, as demonstrated in our results; a better patient stratification can be obtained by jointly analysing morphological and haemodynamic features.

Sensitivity Analysis of In Silico Fluid Simulations to Predict Thrombus Formation after Left Atrial Appendage Occlusion

Atrial fibrillation (AF) is nowadays the most common human arrhythmia and it is considered a marker of an increased risk of embolic stroke. It is known that 99% of AF-related thrombi are generated in the left atrial appendage (LAA), an anatomical structure located within the left atrium (LA). Left atrial appendage occlusion (LAAO) has become a good alternative for nonvalvular AF patients with contraindications to anticoagulants. However, there is a non-negligible number of device-related thrombus (DRT) events, created next to the device surface. In silico fluid simulations can be a powerful tool to better understand the relation between LA anatomy, haemodynamics, and the process of thrombus formation. Despite the increasing literature in LA fluid modelling, a consensus has not been reached yet in the community on the optimal modelling choices and boundary conditions for generating realistic simulations. In this line, we have performed a sensitivity analysis of several boundary conditions scenarios, varying inlet/outlet and LA wall movement configurations, using patient-specific imaging data of six LAAO patients (three of them with DRT at follow-up). Mesh and cardiac cycle convergence were also analysed. The boundary conditions scenario that better predicted DRT cases had echocardiography-based velocities at the mitral valve outlet, a generic pressure wave from an AF patient at the pulmonary vein inlets, and a dynamic mesh approach for LA wall deformation, emphasizing the need for patient-specific data for realistic simulations. The obtained promising results need to be further validated with larger cohorts, ideally with ground truth data, but they already offer unique insights on thrombogenic risk in the left atria.

A bi-atrial statistical shape model for large-scale in silico studies of human atria: Model development and application to ECG simulations

Large-scale electrophysiological simulations to obtain electrocardiograms (ECG) carry the potential to produce extensive datasets for training of machine learning classifiers to, e.g., discriminate between different cardiac pathologies. The adoption of simulations for these purposes is limited due to a lack of ready-to-use models covering atrial anatomical variability. We built a bi-atrial statistical shape model (SSM) of the endocardial wall based on 47 segmented human CT and MRI datasets using Gaussian process morphable models. Generalization, specificity, and compactness metrics were evaluated. The SSM was applied to simulate atrial ECGs in 100 random volumetric instances. The first eigenmode of our SSM reflects a change of the total volume of both atria, the second the asymmetry between left vs. right atrial volume, the third a change in the prominence of the atrial appendages. The SSM is capable of generalizing well to unseen geometries and 95% of the total shape variance is covered by its first 24 eigenvectors. The P waves in the 12-lead ECG of 100 random instances showed a duration of 109.7±12.2 ms in accordance with large cohort studies. The novel bi-atrial SSM itself as well as 100 exemplary instances with rule-based augmentation of atrial wall thickness, fiber orientation, inter-atrial bridges and tags for anatomical structures have been made publicly available. This novel, openly available bi-atrial SSM can in future be employed to generate large sets of realistic atrial geometries as a basis for in silico big data approaches.

Deep Learning Framework for Real-Time Estimation of in-silico Thrombotic Risk Indices in the Left Atrial Appendage

Patient-specific computational fluid dynamics (CFD) simulations can provide invaluable insight into the interaction of left atrial appendage (LAA) morphology, hemodynamics, and the formation of thrombi in atrial fibrillation (AF) patients. Nonetheless, CFD solvers are notoriously time-consuming and computationally demanding, which has sparked an ever-growing body of literature aiming to develop surrogate models of fluid simulations based on neural networks. The present study aims at developing a deep learning (DL) framework capable of predicting the endothelial cell activation potential (ECAP), an in-silico index linked to the risk of thrombosis, typically derived from CFD simulations, solely from the patient-specific LAA morphology. To this end, a set of popular DL approaches were evaluated, including fully connected networks (FCN), convolutional neural networks (CNN), and geometric deep learning. While the latter directly operated over non-Euclidean domains, the FCN and CNN approaches required previous registration or 2D mapping of the input LAA mesh. First, the superior performance of the graph-based DL model was demonstrated in a dataset consisting of 256 synthetic and real LAA, where CFD simulations with simplified boundary conditions were run. Subsequently, the adaptability of the geometric DL model was further proven in a more realistic dataset of 114 cases, which included the complete patient-specific LA and CFD simulations with more complex boundary conditions. The resulting DL framework successfully predicted the overall distribution of the ECAP in both datasets, based solely on anatomical features, while reducing computational times by orders of magnitude compared to conventional CFD solvers.

Subject-Specific Calculation of Left Atrial Appendage Blood-Borne Particle Residence Time Distribution in Atrial Fibrillation

Atrial fibrillation (AF) is the most common arrhythmia that leads to thrombus formation, mostly in the left atrial appendage (LAA). The current standard of stratifying stroke risk, based on the CHA2DS2-VASc score, does not consider LAA morphology, and the clinically accepted LAA morphology-based classification is highly subjective. The aim of this study was to determine whether LAA blood-borne particle residence time distribution and the proposed quantitative index of LAA 3D geometry can add independent information to the CHA2DS2-VASc score. Data were collected from 16 AF subjects. Subject-specific measurements included left atrial (LA) and LAA 3D geometry obtained by cardiac computed tomography, cardiac output, and heart rate. We quantified 3D LAA appearance in terms of a novel LAA appearance complexity index (LAA-ACI). We employed computational fluid dynamics analysis and a systems-based approach to quantify residence time distribution and associated calculated variable (LAA mean residence time, t m) in each subject. The LAA-ACI captured the subject-specific LAA 3D geometry in terms of a single number. LAA t m varied significantly within a given LAA morphology as defined by the current subjective method and it was not simply a reflection of LAA geometry/appearance. In addition, LAA-ACI and LAA t m varied significantly for a given CHA2DS2-VASc score, indicating that these two indices of stasis are not simply a reflection of the subjects' clinical status. We conclude that LAA-ACI and LAA t m add independent information to the CHA2DS2-VASc score about stasis risk and thereby can potentially enhance its ability to stratify stroke risk in AF patients.

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

BACKGROUND

Recently, advances in medical imaging, segmentation techniques, and high-performance computing have supported the use of patient-specific computational fluid dynamics (CFD) simulations. At present, CFD-compatible atrium geometries can be easily reconstructed from atrium images, providing important insight into the atrial fibrillation (AF) phenomenon, and assistance during therapy selection and surgical procedures. However, the hypothesis assumed for such CFD models should be adequately validated.

AIM

This work aims to perform an extensive study of the different hypotheses that are commonly assumed when performing atrial simulations for AF patients, as well as to evaluate and compare the range of indices that are usually applied to assess thrombus formation within the left atrium appendage (LAA).

METHODS

The atrial geometries of two AF patients have been segmented. The resulting geometries have been registered and interpolated to construct a dynamic mesh, which has been employed to compare the rigid and flexible models. Two families of hemodynamic indices have been calculated and compared: wall shear-based and blood age distribution-based.

RESULTS

The findings of this study illustrate the importance of validating the rigid atrium hypothesis when utilizing an AF CFD model. In particular, the absence of the A-wave contraction does not avoid a certain degree of passive atrial contraction, making the rigid model a poor approximation in some cases. Moreover, a new thrombosis predicting index has been proposed, i.e., M4, which has been shown to predict stasis more effectively than other indicators.

Linking statistical shape models and simulated function in the healthy adult human heart

Cardiac anatomy plays a crucial role in determining cardiac function. However, there is a poor understanding of how specific and localised anatomical changes affect different cardiac functional outputs. In this work, we test the hypothesis that in a statistical shape model (SSM), the modes that are most relevant for describing anatomy are also most important for determining the output of cardiac electromechanics simulations. We made patient-specific four-chamber heart meshes (n = 20) from cardiac CT images in asymptomatic subjects and created a SSM from 19 cases. Nine modes captured 90% of the anatomical variation in the SSM. Functional simulation outputs correlated best with modes 2, 3 and 9 on average (R = 0.49 ± 0.17, 0.37 ± 0.23 and 0.34 ± 0.17 respectively). We performed a global sensitivity analysis to identify the different modes responsible for different simulated electrical and mechanical measures of cardiac function. Modes 2 and 9 were the most important for determining simulated left ventricular mechanics and pressure-derived phenotypes. Mode 2 explained 28.56 ± 16.48% and 25.5 ± 20.85, and mode 9 explained 12.1 ± 8.74% and 13.54 ± 16.91% of the variances of mechanics and pressure-derived phenotypes, respectively. Electrophysiological biomarkers were explained by the interaction of 3 ± 1 modes. In the healthy adult human heart, shape modes that explain large portions of anatomical variance do not explain equivalent levels of electromechanical functional variation. As a result, in cardiac models, representing patient anatomy using a limited number of modes of anatomical variation can cause a loss in accuracy of simulated electromechanical function.

Pulmonary ridge coverage and device-related thrombosis after left atrial appendage occlusion

AIMS

The aim of this study was to evaluate the impact of pulmonary ridge (PR) coverage on both clinical and imaging follow-up outcomes in patients undergoing left atrial appendage occlusion (LAAO).

METHODS AND RESULTS

The study included consecutive patients with non-valvular atrial fibrillation who underwent LAAO with disc and lobe devices. Patients were classified into two groups according to the PR coverage. A total of 147 patients were included. Among these, the PR was covered in 109 (74%) and uncovered in 38 (26%). Successful implantation was achieved in 98.6%. No differences in procedural outcomes were observed between the groups. The rate of procedural major adverse events was 3% (only major bleedings and/or vascular access complications). No device embolisation, cardiac tamponade or in-hospital mortality was observed. After a mean follow-up of 1.77±2.2 years, the annualised ischaemic stroke and major bleeding rate was 1.3%/year and 6.5%/year, respectively, without differences between groups. At follow-up, patients with a covered PR presented a lower incidence of device-related thrombosis (DRT) (1%) than those with an uncovered PR (27%); p<0.001. In multivariable analysis, the presence of PR coverage emerged as an independent predictor of DRT.

CONCLUSIONS

Pulmonary ridge coverage was associated with a lower incidence of DRT after LAAO. Procedural and follow-up clinical outcomes did not differ between covered PR and uncovered PR patients.

Boundary-Condition Analysis of an Idealized Left Atrium Model

The most common type of cardiac arrhythmia is atrial fibrillation (AF), which is characterised by irregular and ineffective atrial contraction. This behaviour results into the formation of thrombi, mainly in the left atrial appendage (LAA), responsible for thromboembolic events. Very different approaches are considered as therapy for AF patients. Therefore, it is necessary to yield insight into the flow physics of thrombi formation to determine which is the most appropriate strategy in each case. Computational Fluid Dynamics (CFD) has proven successful in getting a better understanding of the thrombosis phenomenon, but it still requires validation by means of accurate flow field in vivo atrial measurements. As an alternative, in this paper it is proposed an in vitro flow validation, consisting in an idealised model that captures the main flow features observed in the human LA which, once combined with Particle Image Velocimetry (PIV) measurements, provides readily accessible, easy to emulate, detailed velocity fields. These results have been used to validate our laminar and Large Eddy Simulation (LES) simulations. Besides, we have run a parametric study of different boundary conditions sets previously employed in the literature. These data can be used as a benchmark for further development of LA CFD models.

Fibrosis, atrial fibrillation and stroke: clinical updates and emerging mechanistic models

The current paradigm of stroke risk assessment and mitigation in patients with atrial fibrillation (AF) is centred around clinical risk factors which, in the presence of AF, lead to thrombus formation. The mechanisms by which these clinical risk factors lead to thromboembolism, including any role played by atrial fibrosis, are not understood. In patients who had embolic stroke of undetermined source (ESUS), the problem is compounded by the absence of AF in a majority of patients despite long-term monitoring. Atrial fibrosis has emerged as a unifying mechanism that independently provides a substrate for arrhythmia and thrombus formation. Fibrosis-based computational models of AF initiation and maintenance promise to identify therapeutic targets in catheter ablation. In ESUS, fibrosis is also increasingly recognised as a major risk factor, but the underlying mechanism of this correlation is unclear. Simulations have uncovered potential vulnerability to arrhythmia induction in patients who had ESUS. Likewise, computational models of fluid dynamics representing blood flow in the left atrium and left atrium appendage have improved our understanding of thrombus formation, in particular left atrium appendage shapes and blood flow changes influenced by atrial remodelling. Multiscale modelling of blood flow dynamics based on structural fibrotic and morphological changes with associated cellular and tissue electrical remodelling leading to electromechanical abnormalities holds tremendous promise in providing a mechanistic understanding of the clinical problem of thromboembolisation. We present a review of clinical knowledge alongside computational modelling frameworks and conclude with a vision of a future paradigm integrating simulations in formulating personalised treatment plans for each patient.

Cardiac computational modelling

Cardiovascular diseases currently have a major social and economic impact, constituting one of the leading causes of mortality and morbidity. Personalized computational models of the heart are demonstrating their usefulness both to help understand the mechanisms underlying cardiac disease, and to optimize their treatment and predict the patient's response. Within this framework, the Spanish Research Network for Cardiac Computational Modelling (VHeart-SN) has been launched. The general objective of the VHeart-SN network is the development of an integrated, modular and multiscale multiphysical computational model of the heart. This general objective is addressed through the following specific objectives: a) to integrate the different numerical methods and models taking into account the specificity of patients; b) to assist in advancing knowledge of the mechanisms associated with cardiac and vascular diseases; and c) to support the application of different personalized therapies. This article presents the current state of cardiac computational modelling and different scientific works conducted by the members of the network to gain greater understanding of the characteristics and usefulness of these models.