Extended reality simulator for dynamic visualization and evaluation of stereotactic arrhythmia radioablation (STAR) treatment plans within RAVENTA trial

Stereotactic arrhythmia radioablation (STAR) represents an emerging non-invasive treatment for therapy-refractory ventricular tachycardia. Yet, planning remains challenged by multimodal cardiac imaging integration, electroanatomical mapping (EAM) transfer, and cardiorespiratory motion effects on dose delivery. Current radiotherapy (RT) planning systems offer mainly static visualization and limited access to intramural myocardial structures, hindering communication between cardiology and radiation oncology teams. We present a novel extended reality (XR) simulator designed to dynamically visualize STAR-relevant imaging and planning data. The system integrates diastolic cardiac CT, respiratory-binned 4DCT, anatomical segmentations, EAM data, and phase-recomputed RT dose distributions within an XR environment. Cardiac structures are propagated across respiratory phases using deformable registration, while dose distributions are recomputed on each respiratory-binned CT, enabling phase-specific inspection of dose conformality for both planning target volumes (PTVs) and cardiac target volumes (CardTVs). The resulting time-resolved volumetric dataset is rendered in XR, allowing clinicians to explore cardiac motion, visualize intramural dose deposition, and jointly assess target and organ-at-risk dynamics. This supports qualitative evaluation of dose-motion interplay and interdisciplinary interpretation of intramural targets. The system was tested on three STAR patients enrolled in the RAVENTA trial. Motion analysis revealed PTV centroid displacement amplitudes over the breathing cycle of up to 17.5, 10.2, and 8.9 mm for patients 1, 2, and 3, respectively, with conformity number variations of 0.38, 0.34, and 0.19. Expert evaluation showed positive perceived utility for target-anatomy-dose understanding, motion interpretation, and multidisciplinary communication. This proof-of-concept demonstrates the feasibility and potential clinical value of XR-based motion-aware dose visualization for STAR planning.