Advanced computational modelling in the design of new cardiac radiofrequency ablation strategies
Speaker: Prof Luca Gerardo-Giorda- Johannes Kepler University Linz, Austria
Abstract: Radiofrequency ablation (RFA) is a common procedure in cardiac catheterization for the treatment of arrhythmias. Although globally a pretty safe procedure, it may present some risk. Thrombus formation can occur during RFA at the electrode-tissue interface when the temperature exceeds 80°C. Steam pops are caused by tissue overheating at 100°C, and may trigger explosive ruptures of myocardium. If the steam pop occurs sufficiently deep in the tissue, or if the RFA procedure is performed on atria, whose walls are thinner than the ones of the ventricles, such explosive rupture may result in a perforation of the cardiac chamber wall, and in dramatic haemorrhagic events. We will discuss the role of advanced computational modelling in designing safer and more efficient ablation strategies to be applied in the clinical environment, and present the strategy we developed in collaboration with the hospital
Luca Gerardo-Giorda studied Mathematics at the University of Turin, and in 2002 received his Doctorate in Applied Mathematics from the University of Trento. He was awarded a Marie Curie Industry Fellowship at the Institut Francais du Petrole in 2003. After working on applied interdisciplinary research at institutions in Europe (University of Trento, Ecole Polytechnique Paris) and the USA (Emory), in 2011 he joined BCAM (the Basque Center for Applied Mathematics in Bilbao) as a senior researcher, Therein, in 2014 he set up the group on Mathematical Modelling in Biosciences, that he led until February 2020 when he joined Johannes Kepler University Linz. He is currently the head of the Institute for Mathematical Methods in Medicine and Data-Based Modelling at JKU, and group leader at the Johann Radon Institute for Computational and Applied Mathematics (RICAM) of the Austrian Academy of Sciences. An expert in biomedical modelling and simulation, he seeks quantitative answers to clinical problems, with the aim of providing medical doctors with innovative simulation tools to be efficiently used for in silico pathology assessment and in support of clinical decision making.
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