Computational fluid dynamics modelling of left valvular heart diseases   during atrial fibrillation
  Although atrial fibrillation (AF), a common arrhythmia, frequently presents in patients with underlying valvular disease, its hemodynamic contributions are not fully understood. The present work aimed to computationally study how physical conditions imposed by pathologic valvular anatomy act on AF hemodynamics. We simulated AF with different severity grades of left-sided valvular diseases and compared the cardiovascular effects that they exert during AF, compared to lone AF. The fluid dynamics model used here has been recently validated for lone AF and relies on a lumped parameterization of the four heart chambers, together with the systemic and pulmonary circulation. Three different grades of severity (mild, moderate, severe) were analyzed for each of the four valvulopathies (aortic stenosis, mitral stenosis, aortic regurgitation, mitral regurgitation). Regurgitation was hemodynamically more relevant than stenosis, as the latter led to inefficient cardiac flow, while the former introduced more drastic fluid dynamics variation. Moreover, mitral valvulopathies were more significant than aortic ones. In case of aortic valve diseases, proper mitral functioning damps out changes at atrial and pulmonary levels. In the case of mitral valvulopathy, the mitral valve lost its regulating capability, thus hemodynamic variations almost equally affected regions upstream and downstream of the valve. The present study revealed that both mitral and aortic regurgitation strongly affect hemodynamics, followed by mitral stenosis, while aortic stenosis has the least impact among the analyzed valvular diseases. The proposed approach can provide new mechanistic insights as to which valvular pathologies merit more aggressive treatment of AF. Present findings, if clinically confirmed, hold the potential to impact AF management (e.g., adoption of a rhythm control strategy) in specific valvular diseases. 
Stefania Scarsoglio, Andrea Saglietto, Fiorenzo Gaita, Luca Ridolfi,   Matteo Anselmino
physics.flu-dyn physics.med-ph q-bio.TO