ENVISAGE

Conditions studied

Heart Valve Disease, M-TEER, Mitraclip, T-TEER, TAVI, TMVI, TTVI, TriClip

What is being tested

• DIAGNOSTIC_TEST: Medical imaging analysis via artificial intelligence algorithms

What it measures

• Accuracy of transcatheter AI predictions, Validation of artificial intelligence algorithms for automatic segmentation of anatomic structures and imaging measurements, and prediction of the success of transcatheter interventions. Output of AI algorithm: * Sizes, types, and number of devices to be implanted * Device success * Percentage risk of permanent pacemaker implantation (for TAVI and TTVI) * Percentage risk of 30-day (para)valvular regurgitation for TAVI, and residual regurgitation for M-TEER and T-TEER * Single leaflet detachment for M-TEER and T-TEER * Left ventricular outflow tract obstruction for TMVI. Key success indicators: * First, independent retrospective validation dataset AI algorithms predict procedural outcome with \>90% accuracy and low inter-reader observer variability when compared to measured procedural outcome. * Second independent retrospective dataset, perform a study to validate AI algorithms with \>90% accuracy and low inter-reader observer variability when compared to measured procedural outcome., Preoperative phase: automated segmentation and measurements compared with manual assessments; Postoperative phase at day 30: comparison of predicted results with actual clinical patient outcomes.

Working with

Centre Cardiologique du Nord, Centre Hospitalier Universitaire de Bordeaux, FRANCE, Clinique Pasteur Toulouse, Hospitaux Universitaires Paris Sud, Istituto clinico Città di Brescia, Materialise, Montefiore Medical Center, Pie Medical Imaging, Rennes University Hospital, San Raffaele University Hospital, Italy, Unity Health Toronto, University Hospital, Lille, University Hospital, Marseille, University Medical Center Mainz, Universitätsklinikum Hamburg-Eppendorf, Vancouver Hospital