Recent progress in cardiac catheterization and devices has allowed the development of new therapies for severe cardiac diseases like arrhythmias and heart failure. The skills required for such interventions are very challenging to learn, and are typically acquired over several years. Virtual reality simulators may reduce this burden by allowing trainees to practice such procedures without risk to patients. In this paper, we propose the first training system dedicated to cardiac electrophysiology, including pacing and ablation procedures. Our framework involves the simulation of a catheter navigation that reproduces issues intrinsic to intra-cardiac catheterization, and a graphics processing unit (GPU)-based electrophysiological model. A multithreading approach is proposed to compute both physical simulations (navigation and electrophysiology) asynchronously. With this method, we reach computational performances that account for user interactions in real-time. Based on a scenario of cardiac arrhythmia, we demonstrate the ability of the user-guided simulator to navigate inside vessels and cardiac cavities with a catheter and to reproduce an ablation procedure involving: extra-cellular potential measurements, endocardial surface reconstruction, electrophysiology mapping, radio-frequency (RF) ablation, as well as electrical stimulation. A clinical evaluation assessing the different aspects of the simulation is presented. This works is a step towards computerized medical learning curriculum.
Abstract. Recent progress in cardiac catheterization and devices allowed to develop new therapies for severe cardiac diseases like arrhythmias and heart failure. The skills required for such interventions are still very challenging to learn, and typically acquired over several years. Virtual reality simulators can reduce this burden by allowing to practice such procedures without consequences on patients. In this paper, we propose the first training system dedicated to cardiac electrophysiology, including pacing and ablation procedures. Our framework involves an efficient GPU-based electrophysiological model. Thanks to an innovative multithreading approach, we reach high computational performances that allow to account for user interactions in real-time. Based on a scenario of cardiac arrhythmia, we demonstrate the ability of the user-guided simulator to navigate inside vessels and cardiac cavities with a catheter and to reproduce an ablation procedure involving: extra-cellular potential measurements, endocardial surface reconstruction, electrophysiology mapping, radio-frequency (RF) ablation, as well as electrical stimulation. This works is a step towards computerized medical learning curriculum.
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