iHEART – MCF2020, Modelling the Cardiac Function – Milan, Italy
Coupled Multiphysics Models of Cardiac Hemodynamics: From Fundamental Insights to Clinical Translation
Abstract: The mammalian heart has been sculpted by millions of years of evolution into a flow pump par excellence. During the typical lifetime of a human, the heart will beat over three billion times and pump enough blood to fill over 60 Olympic-sized swimming pools. Each of these billions of cardiac cycles is itself a manifestation of a complex and elegant interplay between several distinct physical domains including electrophysiology and mechanics of the cardiac muscles, hemodynamics, and flow-induced movement of the cardiac valves. Another multiphysics interaction that is key to hemostasis involves hemodynamics and blood biochemistry. The clotting cascade, which is a natural response to injury, is initiated by a sequence of biochemical and biomolecular reactions that are strongly modulated by local flow conditions. In this regard, how the chambers and valves of a healthy heart manage to avoid thrombosis, remains an open question. The presence of heart conditions such as myocadial infarction (MI), cardiomyopathies, valve anomalies and atrial fibrillations, disturb the hemostatic balance and can lead to thrombosis with devastating sequalae such as stroke and MI. Computational models for thrombogenesis in the cardiac system have the potential to provide useful insights into this important phenomenon. In the current talk, I will describe high-fidelity chemo-fluidic modeling of thrombogenesis in the left heart and demonstrate how fundamental insights from these studies have been translated into clinically relevant metrics. Application of these models to thrombogenesis in transcatheter aortic valves will also be described.
Monte and Usha Ahuja Distinguished Seminar Series – Ohio State University
The (Un)known-(Un)knowns of COVID-19 – A Fluid Dynamicist’s Perspective
Abstract: COVID-19 spread across the world with a speed and intensity that laid bare the limits in our understanding of the transmission pathways of such respiratory diseases. There is, however, an emerging consensus that airborne transmission constitutes an important mode for the spread of COVID-19. Each stage in this transmission pathway is mediated by complex flow phenomena, ranging from air-mucous interaction inside the respiratory tract, turbulence in the exhaled jet/ambient flow, to inhalation and deposition of these aerosols in the lungs. Inspired by the Drake Equation that provides a framework to estimate the seemingly inestimable probability of advanced extraterrestrial life, I propose a phenomenological model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19. The model incorporates simple ideas from fluid dynamics with known factors involved in airborne transmission, and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia. Given the rapidly evolving nature of the pandemic and the resurgence of infections in many communities, the importance of communicating infection risk across scientific disciplines, as well as to policy/decision makers, is more important than ever.