EchoNet-RCT: Safety and Efficacy Study of AI LVEF

Sponsor

Cedars-Sinai Medical Center (Other)

Overall Status

Completed

CT.gov ID

NCT05140642

Collaborator

(none)

3,495

Enrollment

Location

Arms

2.9

Actual Duration (Months)

1195.3

Patients Per Site Per Month

Study Details

Study Description

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.

Condition or Disease	Intervention/Treatment	Phase
Heart Failure, Systolic Heart Failure, Diastolic	Other: Automated annotation of the left ventricle through deep learning Other: Sonographer Measurement of LVEF	N/A

Study Design

Study Type:

Interventional

Actual Enrollment :

3495 participants

Allocation:

Randomized

Intervention Model:

Single Group Assignment

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.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.

Masking:

Single (Participant)

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.

Primary Purpose:

Diagnostic

Official Title:

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

Actual Study Start Date :

Apr 1, 2022

Actual Primary Completion Date :

Jun 29, 2022

Actual Study Completion Date :

Jun 29, 2022

Arms and Interventions

Arm	Intervention/Treatment
Active Comparator: Sonographer Annotation Currently, sonographer technicians provide preliminary interpretations prior to validation and overreading by cardiologists. This staggered, stepwise evaluation allows for the introduction of AI decision support with minimal impact on patient care. Physicians are already used to adjusting the preliminary report given the variable training of sonographers and on the lookout for changes, variation, or adjustments that need to be made.	Other: Sonographer Measurement of LVEF Standard practice sonographer measurement of left ventricle and assessment of LVEF
Experimental: Artificial Intelligence Annotation In preliminary work, a novel AI algorithm developed to assess LVEF was shown to be more precise than human interpretation in 10,030 echocardiograms done at Stanford University (Ouyang et al. Nature, 2020). With randomization, a proportion of the preliminary interpretations will be done by AI technology and the study team will assess how different this preliminary interpretation is from the final interpretation.	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.

Arm

Intervention/Treatment

Active Comparator: Sonographer Annotation

Currently, sonographer technicians provide preliminary interpretations prior to validation and overreading by cardiologists. This staggered, stepwise evaluation allows for the introduction of AI decision support with minimal impact on patient care. Physicians are already used to adjusting the preliminary report given the variable training of sonographers and on the lookout for changes, variation, or adjustments that need to be made.

Other: Sonographer Measurement of LVEF

Standard practice sonographer measurement of left ventricle and assessment of LVEF

Experimental: Artificial Intelligence Annotation

In preliminary work, a novel AI algorithm developed to assess LVEF was shown to be more precise than human interpretation in 10,030 echocardiograms done at Stanford University (Ouyang et al. Nature, 2020). With randomization, a proportion of the preliminary interpretations will be done by AI technology and the study team will assess how different this preliminary interpretation is from the final interpretation.

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.

Outcome Measures

Primary Outcome Measures

Frequency of >5% change in LVEF between preliminary and final report [10 Minutes]
Proportion of studies the LVEF is changed more than 5% in final report
Average change in LVEF between preliminary and final report [10 Minutes]
Mean change in LVEF between preliminary and final report

Secondary Outcome Measures

Frequency cardiologist adjusts preliminary annotation [10 Minutes]
Proportion of studies the annotation is changed
Average change in LVEF between prior clinical report and final report [10 Minutes]
Mean change in LVEF between prior clinical report and final report

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years to 110 Years

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

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

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Cedars-Sinai Medical Center	Los Angeles	California	United States	90048

Sponsors and Collaborators

Cedars-Sinai Medical Center

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

David Ouyang, Staff Physician, Cedars-Sinai Medical Center

ClinicalTrials.gov Identifier:

NCT05140642

Other Study ID Numbers:

STUDY00001707

First Posted:

Dec 1, 2021

Last Update Posted:

Jul 5, 2022

Last Verified:

Jun 1, 2022

Individual Participant Data (IPD) Sharing Statement:

Plan to Share IPD:

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Keywords provided by David Ouyang, Staff Physician, Cedars-Sinai Medical Center

Echocardiogram

Artificial Intelligence

Additional relevant MeSH terms:

Heart Failure

Heart Failure, Systolic

Heart Failure, Diastolic

Study Results

No Results Posted as of Jul 5, 2022