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NCT07632794

Artificial Intelligence Assisting Transcatheter Mitral Edge-to-Edge Repair

Sponsor: Mi Chen

View on ClinicalTrials.gov

Summary

This multicenter, retrospective study develops and validates artificial intelligence (AI)-based semantic segmentation algorithms for intraprocedural transesophageal echocardiography (TEE) during Transcatheter Mitral Edge-to-Edge Repair (TEER). Using pooled imaging data from multiple high-volume structural heart centers, the study aims to automate recognition of mitral leaflets and MitraClip components, measure leaflet insertion length in real time, and display clip position and orientation. Algorithm performance will be benchmarked against expert manual annotations.

Official title: Artificial Intelligence Semantic Segmentation Technology Assisting Transcatheter Mitral Edgeto-Edge Repair

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

1500

Start Date

2025-09-01

Completion Date

2030-08-31

Last Updated

2026-06-08

Healthy Volunteers

No

Locations (3)

Fuwai Hospital, Chinese Academy of Medical Sciences

Beijing, Beijing Municipality, China

IRCCS Policlinico San Donato

Milan, Italy

San Raffaele Hospital

Milan, Italy