Safety and Efficacy Study of AI LVEF

Heart Failure, Systolic Clinical Trial

— EchoNet-RCT  

Official title:

Blinded Randomized Controlled Trial of Artificial Intelligence Guided Assessment of Cardiac Function

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05140642
• Other study ID #: STUDY00001707
• Status: Completed
• Phase: N/A
• Start date: April 1, 2022
• Est. completion date: June 29, 2022

Study information

• Verified date: June 2022
• Source: Cedars-Sinai Medical Center
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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 left ventricular ejection fraction compared to sonographer measurements in preliminary readings of echocardiograms.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 3495
• Est. completion date: June 29, 2022
• Est. primary completion date: June 29, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 110 Years

Eligibility

Inclusion Criteria:

• The study imaging studies will include patients who underwent imaging (limited or comprehensive transthoracic echocardiogram studies) and a LVEF was adjudicated in the echocardiography/non-invasive cardiac imaging laboratory.
• The study participants are cardiologists reading in the echocardiography/non-invasive cardiac imaging laboratory.

Exclusion Criteria:

• The study imaging studies will exclude transesophageal echocardiogram imaging.
• The study will exclude cardiologists who decline to participate

Related Conditions & MeSH terms

• Heart Failure
• Heart Failure, Diastolic
• Heart Failure, Systolic

Intervention

Other:
• Automated annotation of the left ventricle through deep learning
A semantic segmentation deep learning model will identify the left ventricle and label the left ventricle. The AI model will produce an assessment of LVEF using video based features.
• Sonographer Measurement of LVEF
Standard practice sonographer measurement of left ventricle and assessment of LVEF

Locations

Country	Name	City	State
United States	Cedars-Sinai Medical Center	Los Angeles	California

Sponsors (1)

Lead Sponsor	Collaborator
Cedars-Sinai Medical Center

Country where clinical trial is conducted

United States, 

References & Publications (1)

Ouyang D, He B, Ghorbani A, Yuan N, Ebinger J, Langlotz CP, Heidenreich PA, Harrington RA, Liang DH, Ashley EA, Zou JY. Video-based AI for beat-to-beat assessment of cardiac function. Nature. 2020 Apr;580(7802):252-256. doi: 10.1038/s41586-020-2145-8. Epu — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Frequency of >5% change in LVEF between preliminary and final report	Proportion of studies the LVEF is changed more than 5% in final report	10 Minutes
Primary	Average change in LVEF between preliminary and final report	Mean change in LVEF between preliminary and final report	10 Minutes
Secondary	Frequency cardiologist adjusts preliminary annotation	Proportion of studies the annotation is changed	10 Minutes
Secondary	Average change in LVEF between prior clinical report and final report	Mean change in LVEF between prior clinical report and final report	10 Minutes