AI for Heart Valve Interventions (ENVISAGE Study)

This study, called ENVISAGE, is looking at how artificial intelligence (AI) can help doctors better predict the results of heart valve procedures. These procedures include TAVI (Transcatheter Aortic Valve Implantation), M-TEER (Mitral Transcatheter Edge-to-Edge Repair), TTVI (Transcatheter Tricuspid Valve Implantation), and TMVI (Transcatheter Mitral Valve Implantation). Researchers will use AI to analyze medical images and patient information to see if it can accurately predict how well these procedures will work. The goal is to improve patient selection and planning for these important heart valve treatments. This study is for adults aged 18 and older who have had a TAVI procedure and have specific CT scans available. Success will be measured by how accurate the AI predictions are compared to actual patient outcomes 30 days after the procedure. The study status is unclear.

Study design
This is an observational study, meaning researchers will analyze existing data rather than giving new treatments. It aims to include 21,000 participants.
What's involved
Not specified in the trial record.
Compensation
Not stated in the trial record.
Follow-up
The study will compare predicted results with actual patient outcomes 30 days after the procedure.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT07213531

Enhanced Valves Interventions and Safe AI Generated End Results

Recruiting
Not specifiedAges 18+Observational
Montreal Heart Institute
~21,000 participants
Updated 2025-10-09 on ClinicalTrials.gov
What's tested:Medical imaging analysis via artificial intelligence algorithms

At a glance

Recruiting sites
15 of 15 listed sites are recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Accuracy of transcatheter AI predictions
Measured over Preoperative phase: automated segmentation and measurements compared with manual assessments; Postoperative phase at day 30: comparison of predicted results with actual clinical patient outcomes.
Heart Valve Disease
TAVI
M-TEER
TTVI
TMVI
T-TEER
Mitraclip
TriClip
15 sites across 6 states
France7
Canada2
Germany2
Italy2
New York1
Quebec1
  • Thomas Modine, MD, PhD · PRINCIPAL_INVESTIGATOR · University Hospital Bordeaux, France
  • Walid Ben Ali, MD, PhD · PRINCIPAL_INVESTIGATOR · Montreal Heart Institute

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Eligibility criteria

Inclusion

For TAVI group: All patients who have had TAVI with a third generation transcatheter heart valve (THV), with an available pre-procedural optimal quality CT scan as defined by an ECG- gating CT with:
For TMVI group: Patients who have had a TMVI with a dedicated device and screen failures, with an available optimal quality CT scan.
For TTVI group: Patients who have had a TTVI with a dedicated device and screen failures, with an available optimal quality CT scan.
For M-TEER: All patient who have had a M-TEER with 1) G4 or newer iteration of MitraClip or 2) G2 or newer iteration of Pascal, with available pre-procedural TEE videos images from one of two vendors: Phillips or GE, with clear identifiable views of the Mitral valve, frame per second equal or higher than 40 frames per second, acceptable 3D reconstructions.
For T-TEER: All patient who have had a T-TEER with G4 or newer iteration of TriClip or 2) G2 or newer iteration of Pascal, with available pre-procedural TEE videos images from one of two vendors: Phillips or GE, with clear identifiable views of the Tricuspid valve, frame per second equal or higher than 40 frames per second, acceptable transgastric image with acceptable 3D reconstructions.

Exclusion

For TAVI group: Valve-in-valve procedures
For TMVI group: Valve-in-valve and valve-in-ring procedures
For TTVI: Valve-in-valve and valve-in-ring procedures
For M-TEER: G3 or older MitraClip, G1 Pascal
For T-TEER: G3 Triclip, G1 Pascal
  • Accuracy of transcatheter AI predictionsPreoperative phase: automated segmentation and measurements compared with manual assessments; Postoperative phase at day 30: comparison of predicted results with actual clinical patient outcomes.

    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.