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. 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). 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. 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.

A data-driven reduced order model (ROM) based on a proper orthogonal decomposition-radial basis function (POD-RBF) approach is adopted in this paper for the analysis of blood flow dynamics in a patient-specific case of atrial fibrillation (AF). The full order model (FOM) is represented by incompressible Navier–Stokes equations, discretized with a finite volume (FV) approach. Both the Newtonian and the Casson’s constitutive laws are employed. The aim is to build a computational tool able to efficiently and accurately reconstruct the patterns of relevant hemodynamics indices related to the stasis of the blood in a physical parametrization framework including the cardiac output in the Newtonian case and also the plasma viscosity and the hematocrit in the non-Newtonian one. Many FOM-ROM comparisons are shown to analyze the performance of our approach as regards errors and computational speed-up.

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). 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. 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). 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.