Recruiting

Observational StudyEnhanced Valves Interventions and Safe AI Generated End Results

Sponsor:

Montreal Heart Institute

Code:

NCT07213531

Conditions

Heart Valve Disease

TAVI

M-TEER

TTVI

TMVI

Eligibility Criteria

Sex: All

Age: 18+

Healthy Volunteers: Not accepted

Interventions

Medical imaging analysis via artificial intelligence algorithms

Study Details

Brief summary:

This non-interventional study aims to use artificial intelligence to improve the prediction of transcatheter heart valve interventions and optimize patient outcomes. It is based on the analysis of retrospective data from various specialized centers worldwide.

Conditions

Heart Valve Disease

TAVI

M-TEER

TTVI

TMVI

Study ID

NCT07213531

Start date

May 1, 2024

Status verified date

Oct, 2025

Completion date

May, 2029

Anticipated

Primary completion date

May, 2028

Anticipated

Eligibility Criteria

Sex: All

Age: 18+

Healthy Volunteers: Not accepted

Inclusion Criteria:

Patients who have reached the age of legal majority under local laws.

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:

1. five to ten image volumes at cardiac phases from 5% to 95% R-R
2. 0.625 mm slice thickness
3. 0.625 mm spacing between slices
4. 0.88 mm in-plane pixel spacing

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 Criteria:

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

Study Design

Enrollment

21000 participants

Anticipated

Interventions and Outcome Measures

Arms

TAVI

All patients who have had TAVI with a third generation transcatheter heart valve (THV). Medical imaging data (CT, TEE) and preoperative clinical data will be collected for analysis.

TMVI

Patients who have had a TMVI with a dedicated transeptal device and screen failures. Medical imaging data (CT, TEE) and preoperative clinical data will be collected for analysis.

TTVI

Patients who have had a TTVI with a dedicated device and screen failures. Medical imaging data (CT, TEE) and preoperative clinical data will be collected for analysis.

M-TEER

All patients who have had a M-TEER with 1) G4 or newer iteration of MitraClip or 2) G2 or newer iteration of Pascal. Medical imaging data (CT, TEE) and preoperative clinical data will be collected for analysis.

T-TEER

All patients who have had a T-TEER with G4 or newer iteration of TriClip or 2) G2 or newer iteration of Pascal. Medical imaging data (CT, TEE) and preoperative clinical data will be collected for analysis.

Interventions

Medical imaging analysis via artificial intelligence algorithms

Development of AI algorithms based on pre-procedural imaging annotations and clinical informations to predict the transcatheter procedural outcomes

Primary outcome measure

Accuracy of transcatheter AI predictions [ Time Frame: Preoperative phase: automated segmentation and measurements compared with manual assessments; Postoperative phase at day 30: comparison of predicted results with actual clinical patient outcomes. ]

Central Contacts and Locations

Central contacts

Thomas Modine, MD, PhD

+33(0)5 25 377541 thomasmodine@gmail.com

Walid Ben Ali, MD, PhD

+1 5145611037 dr.walidbenali@gmail.com

Locations

Montefiore Medical Center New York

Recruiting

New York, New York, United States, 10467

Contacts

Andrea Scotti, MD, PhD

+1 718-920-4321 a.scotti@hotmail.com

Montreal Heart Institute, 5000 Rue Bélanger, Montréal

Recruiting

Montreal, Quebec, Canada, H1T 1C8

Contacts

Walid Ben Ali, MD, PhD

+1 5145611037 dr.walidbenali@gmail.com

Principal Investigator:

Walid Ben Ali, MD, PhD

St Michael's Hospital Toronto

Recruiting

Toronto, Canada

Contacts

Neil Fam, MD

+1 416-864-5939 neil.fam@unityhealth.to

St Paul's Hospital Vancouver

Recruiting

Vancouver, Canada

Contacts

John Webb, MD

+1-604-806-8804 johngraydonwebb@gmail.com

More Information

Sponsor

Montreal Heart Institute

Last update posted

Oct 9, 2025

Last verified

Oct, 2025

Keywords

Medical imaging
CT
Artificial intelligence
M-TEER
T-TEER
TAVI
TMVI
valvulopathy
predictive algorithms

Trial information was received from ClinicalTrials.gov and was last updated on 2026-09-10. This information was provided to ClinicalTrials.gov by Montreal Heart Institute on 2025-10-09.