Safety and Efficacy Study of AI Wall Thickness Measurement (EchoNet-LVH-RCT)

Enrolling by invitation · Not applicable

Conditions studied: Heart Failure

In brief

To determine whether an integrated AI decision support can save time and improve accuracy of assessment of echocardiograms, the investigators are conducting a blinded, randomized controlled study of AI guided measurements of wall thickness in parasternal long axis view compared to sonographer measurements in preliminary readings of echocardiograms.

Key facts

Study ID

NCT05791227

Run by

Cedars-Sinai Medical Center

People needed

4000

Starts

2025-04-01

Expected to finish

2027-01-01

Last updated by the study team

2026-07-22

Who can join

Age: 18 and older, up to 100. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Sonographers and cardiologists at CSMC Echocardiography Lab
• All transthoracic echocardiogram studies performed in the CSMC echocardiogram lab

You may not qualify if…

• transthoracic echocardiogram studies not able to be measured by sonographers in run in period

Where it is running

• Cedars-Sinai Medical Center — Los Angeles, California, United States

Full record on ClinicalTrials.gov

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