Performance Evaluation of Mixed Reality Display for Guidance During Transcatheter Cardiac Mapping and Ablation
PubDate: July 2020
Teams: SentiAR;Washington University in St. Louis
Writers: Michael K. Southworth; Jennifer N. Avari Silva; Walter M. Blume; George F. Van Hare; Aarti S. Dalal; Jonathan R. Silva
Abstract
Cardiac electrophysiology procedures present the physician with a wealth of 3D information, typically presented on fixed 2D monitors. New developments in wearable mixed reality displays offer the potential to simplify and enhance 3D visualization while providing hands-free, dynamic control of devices within the procedure room. Objective: This work aims to evaluate the performance and quality of a mixed reality system designed for intraprocedural use in cardiac electrophysiology. Method: The Enhanced Electrophysiology Visualization and Interaction System (E̅LVIS) mixed reality system performance criteria, including image quality, hardware performance, and usability were evaluated using existing display validation procedures adapted to the electrophysiology specific use case. Additional performance and user validation were performed through a 10 patient, in-human observational study, the Engineering E̅LVIS(E2) Study. Results: The E̅LVIS system achieved acceptable frame rate, latency, and battery runtime with acceptable dynamic range and depth distortion as well as minimal geometric distortion. Bench testing results corresponded with physician feedback in the observational study, and potential improvements in geometric understanding were noted. Conclusion: The E̅lvis system, based on current commercially available mixed reality hardware, is capable of meeting the hardware performance, image quality, and usability requirements of the electroanatomic mapping display for intraprocedural, real-time use in electrophysiology procedures. Verifying off the shelf mixed reality hardware for specific clinical use can accelerate the adoption of this transformative technology and provide novel visualization, understanding, and control of clinically relevant data in real-time.
