AUTHOR=Hecko Jan , Precek Daniel , Januska Jaroslav , Hudec Miroslav , Barnova Katerina , Palickova-Mikolasova Martina , Pekar Matej , Chovancik Jan , Sknouril Libor , Jiravsky Otakar 

TITLE=Design and validation of a mixed reality workflow for structural cardiac procedures in interventional cardiology

JOURNAL=Frontiers in Virtual Reality

VOLUME=Volume 6 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/virtual-reality/articles/10.3389/frvir.2025.1690439

DOI=10.3389/frvir.2025.1690439

ISSN=2673-4192

ABSTRACT=BackgroundMixed reality (MR) technologies, such as those integrating Unity and Microsoft HoloLens 2, hold promises for enhancing non-coronary interventions in interventional cardiology by providing real-time 3D visualizations, multi-user collaboration, and gesture-based interactions. However, barriers to clinical adoption include insufficient validation of performance, usability, and workflow integration, aligning with the Research Topic on transforming medicine through extended reality (XR) via robust technologies, education, and ethical considerations. This study addresses these gaps by developing and rigorously evaluating an MR system for procedures like transcatheter valve replacements and atrial septal defect repairs.MethodsThe system was built using Unity with modifications to the UnityVolumeRendering plugin for Digital Imaging and Communications in Medicine (DICOM) data processing and volume rendering, Mixed Reality Toolkit (MRTK) for user interactions, and Photon Unity Networking (PUN2) for multi-user synchronization. Validation involved technical performance metrics (e.g., frame rate, latency), measured via Unity Profiler and Wireshark during stress tests. Usability was assessed using the System Usability Scale (SUS) and NASA Task Load Index (NASA-TLX), as well as through task-based trials. Workflow integration was evaluated in a simulated cath-lab setting with six cardiologists, focusing on calibration times and responses to a custom questionnaire. Statistical analysis included means ± standard deviation (SD) and 95% confidence intervals.ResultsTechnical benchmarks showed frame rates of 59.6 ± 0.7 fps for medium datasets, local latency of 14.3 ± 0.5 ms (95% CI: 14.1–14.5 ms), and multi-user latency of 26.9 ± 12.3 ms (95% CI: 23.3–30.5 ms), with 91% gesture recognition accuracy. Usability yielded a SUS score of 77.5 ± 3.8 and NASA-TLX of 37 ± 7, with task completion times under 60 s. Workflow metrics indicated 38 s calibration and high communication benefits (4.5 ± 0.2 on a 1–5 scale).ConclusionThis validated MR solution demonstrates feasibility for precise, collaborative cardiac interventions, paving the way for broader XR adoption in medicine while addressing educational and ethical integration challenges.