Artificial intelligence based fusion imaging streamlining mitral transcatheter edge-to-edge repair

Abstract Aims Precise imaging is critical for procedural success in mitral transcatheter edge-to-edge repair (M-TEER), yet conventional fluoroscopy and echocardiography may lead to miscommunication and suboptimal device placement. The aim was to test the clinical utility of DeviceGuide EchoNavigator SmartVue (Philips Healthcare), a novel artificial intelligence-based fusion imaging software that automatically tracks the PASCAL Ace device and aligns live 3D transoesophageal echocardiography with fluoroscopy. Methods In this prospective multicentre study, DeviceGuide was evaluated in four structural heart centres in the United States, the Netherlands, and Switzerland in consecutive patients undergoing M-TEER with the PASCAL Ace device. Dedicated imaging modes support the procedure: Target Mode with trajectory overlays for real-time navigation, and a Device Mode that delivers continuous, auto-centred and auto-aligned device visualization throughout leaflet capture and closure. Interventional teams completed a structured qualitative questionnaire focusing on workflow, team discussions on optimal trajectory, perceived image quality and stability, and overall usefulness of the software during key procedural stages. Results Among 51 DeviceGuide-assisted M-TEER procedures, clinical teams rated the software as helpful or very helpful in guiding the intervention in most cases and reported improved discussion of optimal strategy. Main perceived advantages over conventional imaging were enhanced awareness and real-time feedback on trajectory and automated 3D TEE views with continuous, auto-aligned device imaging during implantation. Conclusion This AI-based fusion imaging approach demonstrated high perceived utility during M-TEER with PASCAL Ace and appeared to streamline workflow and team communication, supporting further studies to determine its impact on clinical outcomes.