AI reads heart ultrasound videos to pick best candidates for valve repair

NCT ID NCT07247890

Not yet recruiting Knowledge-focused Sponsor: Beijing Hospital Source: ClinicalTrials.gov ↗

First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study aims to create an artificial intelligence (AI) model that analyzes ultrasound videos of the heart to help doctors decide if a patient with a leaky mitral valve (mitral regurgitation) is a good candidate for a minimally invasive repair procedure called TEER. The researchers will use data from 800 patients across multiple centers to build and test the AI. The goal is to make the preoperative assessment faster, more objective, and easier to use, especially in primary care settings.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance: AI model (Vision Mamba) for preoperative assessment
What this could lead to: If successful, this could provide a faster, more objective way to identify which patients with mitral regurgitation are good candidates for a minimally invasive heart valve repair, potentially improving surgical outcomes and healthcare efficiency.
What could go wrong: This is an early-stage model development study, not a treatment trial. The AI may not perform as well in real-world settings or across different patient groups, and it will need further validation before it can be used in clinical practice.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

mitral valve insufficiency

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

MITRAL REGURGITATION (MR)

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Other studies related to the condition(s) this trial covers.