Enhanced Valves Interventions and Safe AI Generated End Results

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
• T-TEER
• Mitraclip
• TriClip

Interventions

DIAGNOSTIC_TEST

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

Sponsors & Collaborators

• Centre Hospitalier Universitaire de Bordeaux, FRANCE

  collaborator UNKNOWN

• Materialise

  collaborator INDUSTRY

• Pie Medical Imaging

  collaborator UNKNOWN

• Clinique Pasteur Toulouse

  collaborator OTHER

• Centre Cardiologique du Nord

  collaborator OTHER

• CHU Rennes,France

  collaborator UNKNOWN

• San Raffaele University Hospital, Italy

  collaborator OTHER

• Istituto clinico Città di Brescia

  collaborator UNKNOWN

• Unity Health Toronto

  collaborator OTHER

• University Hospital, Marseille

  collaborator OTHER

• Lille University Hospital

  collaborator UNKNOWN

• Hospitaux Universitaires Paris Sud

  collaborator UNKNOWN

• Montefiore Medical Center

  collaborator OTHER

• University Medical Center Mainz

  collaborator OTHER

• Universitätsklinikum Hamburg-Eppendorf

  collaborator OTHER

• Vancouver Hospital

  collaborator UNKNOWN

• Montreal Heart Institute

  lead OTHER

Principal Investigators

• Thomas Modine, MD, PhD · University Hospital Bordeaux, France

• Walid Ben Ali, MD, PhD · Montreal Heart Institute

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2024-05-01

Primary Completion

2028-05-31

Completion

2029-05-31

Countries

• United States
• Canada
• France
• Germany
• Italy

Study Locations