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Safety and Efficacy Study of AI LVEF

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

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT05140642
Acronym
EchoNet-RCT
Enrollment
3495
Registered
2021-12-01
Start date
2022-04-01
Completion date
2022-06-29
Last updated
2022-07-05

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Heart Failure, Diastolic, Heart Failure, Systolic

Keywords

Echocardiogram, Artificial Intelligence

Brief 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.

Interventions

OTHERAutomated 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.

OTHERSonographer Measurement of LVEF

Standard practice sonographer measurement of left ventricle and assessment of LVEF

Sponsors

Cedars-Sinai Medical Center
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Subject)

Masking description

Measurements shown in Picture Archiving and Communication System (PACS) without direct communication between sonographer and cardiologist. Annotations are shown without identifiers on how the annotations were done. Cardiologists are blinded to source of preliminary interpretation.

Intervention model description

Studies will be randomized 1:1 to either sonographer preliminary report finding or AI preliminary report finding with final adjudication by the cardiologist. With AI preliminary report, the preliminary interpretations will be generated by AI (artificial intelligence) technology \[a semantic segmentation model\] and the PACS system's native EF calculation workflow will be used to calculate LVEF. The study team will assess how much cardiologists edit and change this preliminary interpretation is from the final interpretation.

Eligibility

Sex/Gender
ALL
Age
18 Years to 110 Years
Healthy volunteers
No

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

Design outcomes

Primary

MeasureTime frameDescription
Frequency of >5% change in LVEF between preliminary and final report10 MinutesProportion of studies the LVEF is changed more than 5% in final report
Average change in LVEF between preliminary and final report10 MinutesMean change in LVEF between preliminary and final report

Secondary

MeasureTime frameDescription
Frequency cardiologist adjusts preliminary annotation10 MinutesProportion of studies the annotation is changed
Average change in LVEF between prior clinical report and final report10 MinutesMean change in LVEF between prior clinical report and final report

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 11, 2026