Interactive Training System for Interventional Electrocardiology Procedures

International audienceRecent progress in cardiac catheterization and devices al-lowed to develop new therapies for severe cardiac diseases like arrhyth-mias and heart failure. The skills required for such interventions are still very challenging to learn, and typically acquired over several years. Vir-tual 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, includ-ing pacing and ablation procedures. Our framework involves an efficient GPU-based electrophysiological model. Thanks to an innovative mul-tithreading 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 poten-tial 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

Interactive Training System for Interventional Electrocardiology Procedures

International audienceRecent 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 multi-threading 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, electrophysiol-ogy 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

Surgery Training, Planning and Guidance Using the SOFA Framework

International audienceIn recent years, an active development of novel technologies dealing with medical training, planning and guidance has become an increasingly important area of interest in both research and health-care manufacturing. A combination of advanced physical models, realistic human-computer interaction and growing computational power is bringing new solutions in order to help both medical students and experts to achieve a higher degree of accuracy and reliability in surgical interventions. In this paper, we present three different examples of medical physically-based simulations implemented in a common software platform called SOFA. Each example represents a different application: training for cardiac electrophysiology, pre-operative planning of cryosurgery and per-operative guidance for laparoscopy. The goal of this presentation is to evaluate the realism, accuracy and efficiency of the simulations, as well as to demonstrate the potential and flexibility of the SOFA platform

Use of extended realities in cardiology

Recent miniaturization of electronic components and advances in image processing software have facilitated the entry of extended reality technology into clinical practice. In the last several years, the number of applications in cardiology has multiplied, with many promising to become standard of care. We review many of these applications in the areas of patient and physician education, cardiac rehabilitation, pre-procedural planning and intraprocedural use. The rapid integration of these approaches into the many facets of cardiology suggests that they will one day become an every-day part of physician practice

Focal Spot, Winter 2005/2006

https://digitalcommons.wustl.edu/focal_spot_archives/1101/thumbnail.jp

Computer-Aided Clinical Decision Support Systems for Atrial Fibrillation

Clinical decision support systems (clinical DSSs) are widely used today for various clinical applications such as diagnosis, treatment, and recovery. Clinical DSS aims to enhance the end‐to‐end therapy management for the doctors, and also helps to provide improved experience for patients during each phase of the therapy. The goal of this chapter is to provide an insight into the clinical DSS associated with the highly prevalent heart rhythm disorder, atrial fibrillation (AF). The use of clinical DSS in AF management is ubiquitous, starting from detection of AF through sophisticated electrophysiology treatment procedures, all the way to monitoring the patient\u27s health during follow‐ups. Most of the software associated with AF DSS are developed based on signal processing, image processing, and artificial intelligence techniques. The chapter begins with a brief description of DSS in general and then introduces DSS that are used for various clinical applications. The chapter continues with a background on AF and some relevant mechanisms. Finally, a couple of clinical DSS used today in regard with AF are discussed, along with some proposed methods for potential implementation of clinical DSS for detection of AF, prediction of an AF treatment outcome, and localization of AF targets during a treatment procedure

Improving Nurses’ Corrected QT Interval Monitoring on a Telemetry Unit

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