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.

Trial Health

On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment

21,000

participants targeted

Target at P75+ for all trials

Timeline

36mo left

Started May 2024

Longer than P75 for all trials

Geographic Reach

5 countries

15 active sites

Status

recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

5 years study duration

Study Progress40%

May 2024May 2029

Study Start

First participant enrolled

May 1, 2024

Completed

1.4 years until next milestone

First Submitted

Initial submission to the registry

September 24, 2025

Completed

15 days until next milestone

First Posted

Study publicly available on registry

October 9, 2025

Completed

2.6 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

May 1, 2028

Expected

1 year until next milestone

Study Completion

Last participant's last visit for all outcomes

May 1, 2029

Last Updated

October 9, 2025

Status Verified

October 1, 2025

Enrollment Period

4 years

First QC Date

September 24, 2025

Last Update Submit

October 1, 2025

Conditions

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

Keywords

Medical imagingCTArtificial intelligenceM-TEERT-TEERTAVITMVIvalvulopathypredictive algorithms

Outcome Measures

Primary Outcomes (1)

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.

Secondary Outcomes (1)

Performance of AI algorithms in CT and TEE image analysis
Through study completion, an average of 2 years (retrospective analysis and validation of algorithms).

Other Outcomes (1)

AI-based discovery of clinical knowledge for patient selection
Baseline (pre-procedural) and post-procedural (day 90) analysis

Study Arms (5)

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.