Enhanced Valves Interventions and Safe AI Generated End Results

Part of paid clinical trials in New York, New York.

Sponsor
Montreal Heart Institute
Study ID
NCT07213531
Status
Recruiting
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Conditions

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

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Medical imaging analysis via artificial intelligence algorithms — DIAGNOSTIC_TEST
    Development of AI algorithms based on pre-procedural imaging annotations and clinical informations to predict the transcatheter procedural outcomes

Study Details

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.

Key Dates

Start date
May 1, 2024
Status verified
Oct 2025
Primary completion
May 31, 2028
Completion
May 31, 2029

Study Design

Enrollment
21,000 participants (estimated)

Arms

  • Arm: 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.
  • Arm: 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.
  • Arm: 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.
  • Arm: 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.
  • Arm: 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.

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

Locations (1)

FacilityCityStateZIPSite coordinators
Montefiore Medical Center New YorkNew YorkNew York10467
Andrea Scotti, MD, PhD
[email protected]
+1 718-920-4321

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By research site
Montefiore Medical Center New York· New York, NY

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