Modeling Left Atrial Flow, Energy, Blood Heating Distribution in Response to Catheter Ablation Therapy

Introduction: Atrial fibrillation (AF) is a widespread cardiac arrhythmia that commonly affects the left atrium (LA), causing it to quiver instead of contracting effectively. This behavior is triggered by abnormal electrical impulses at a specific site in the atrial wall. Catheter ablation (CA) treatment consists of isolating this driver site by burning the surrounding tissue to restore sinus rhythm (SR). However, evidence suggests that CA can concur to the formation of blood clots by promoting coagulation near the heat source and in regions with low flow velocity and blood stagnation.Methods: A patient-specific modeling workflow was created and applied to simulate thermal-fluid dynamics in two patients pre- and post-CA. Each model was personalized based on pre- and post-CA imaging datasets. The wall motion and anatomy were derived from SSFP Cine MRI data, while the trans-valvular flow was based on Doppler ultrasound data. The temperature distribution in the blood was modeled using a modified Pennes bioheat equation implemented in a finite-element based Navier-Stokes solver. Blood particles were also classified based on their residence time in the LA using a particle-tracking algorithm.Results: SR simulations showed multiple short-lived vortices with an average blood velocity of 0.2-0.22 m/s. In contrast, AF patients presented a slower vortex and stagnant flow in the LA appendage, with the average blood velocity reduced to 0.08–0.14 m/s. Restoration of SR also increased the blood kinetic energy and the viscous dissipation due to the presence of multiple vortices. Particle tracking showed a dramatic decrease in the percentage of blood remaining in the LA for longer than one cycle after CA (65.9 vs. 43.3% in patient A and 62.2 vs. 54.8% in patient B). Maximum temperatures of 76° and 58°C were observed when CA was performed near the appendage and in a pulmonary vein, respectively.Conclusion: This computational study presents novel models to elucidate relations between catheter temperature, patient-specific atrial anatomy and blood velocity, and predict how they change from SR to AF. The models can quantify blood flow in critical regions, including residence times and temperature distribution for different catheter positions, providing a basis for quantifying stroke risks

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

Wake dynamics of flow past a curved circular cross-section body under cross-flow vibration

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Ventricular Mechanics in Congenital Heart Disease

Looking at "Horse in Motion", the iconic photograph by E. Muybridge, it is almost possible to hear the horse galloping. The pounding sound of the hoofs hitting the ground -like a drum- can also echo the rythmic beating of the human heart. That sound, that visceral rhythm, reminds us of the link between motion and performance: the perfectly executed stride of the horse, the incredible coordination of multiscale phenomena behind a heart beat. Furthermore, the decomposed sequence in Muybridge's photograph has become a well-known example of breaking motion into its components over time, and as such is reminiscent of those images that are routinely acquired in clinical practice, where the heart appears dilating and shirnking in a sequence of snapshots. The investigation of this motion and its subtleties is essential for refining our understanding of cardiac function, and the appreciation of how and when this motion is no longer perfectly executed can lead us to understand functional impairments and provide insight into the unfolding of pathology. In the presence of congenital heart disease (CHD), cardiac mechanics are altered: from single ventricle physiology to conduction abnormalities to different cardiomyopathies, it is important to both capture and interpret biomechanical changes that occur in the presence of a congenital defect. This special issue in Frontiers in Pediatrics, now an e-book, focuses on 'Ventricular mechanics in congenital heart disease' and looks at current knowledge of phenomena such as systolic/diastolic dysfuction and current methods (chiefly in cardiovascular magnetic resonance imaging and echocardiography) to evaluate cardiac function in the presence of CHD, and then presents a series of original studies that employ both medical imaging and computational modelling techniques to study specific CHD scenarios

Numerical simulation of blood flow in 7 mitral valve replacement patients

Modelling datasets are based on CT and echo images of patients. Computer simulations are performed using an in-house finite-element software (CHeart) in different configurations for each patient to simulate the blood flow changes induced by implantation of an artificial mitral valve. More specifically, the aim of this study is to investigate the effects on ventricular hemodynamics that a partial occlusion of the left ventricular outflow tract can cause as a result of the implantation of a prosthetic valve. Related publication: de Vecchi et al. 2018. "Left ventricular outflow obstruction predicts increase in systolic pressure gradients and blood residence time after transcatheter mitral valve replacement" Nature Scientific Reports. Accepted

Anatomically accurate mesh: Using Gaussian process for velocity reconstruction after coronary stenosis applicable in positron emission particle tracking

<p>The FLUENT mesh files of the anatomically accurate geometry with and without stenosis at LCx. </p> <p>The stenosis has been created virtually. </p> <p> </p&gt