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Safety and Efficacy Study of AI LVEF (EchoNet-RCT)

Primary Purpose

Heart Failure, Systolic, Heart Failure, Diastolic

Status

Completed

Phase

Not Applicable

Locations

United States

Study Type

Interventional

Intervention

Automated annotation of the left ventricle through deep learning

Sonographer Measurement of LVEF

About this trial

This is an interventional diagnostic trial for Heart Failure, Systolic focused on measuring Echocardiogram, Artificial Intelligence

Eligibility Criteria

18 Years - 110 Years (Adult, Older Adult)All SexesDoes not accept 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

Sites / Locations

Cedars-Sinai Medical Center

Arms of the Study

Arm 1

Arm 2

Arm Type

Active Comparator

Experimental

Arm Label

Sonographer Annotation

Artificial Intelligence Annotation

Arm Description

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.

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.

Outcomes

Primary Outcome Measures

Frequency of >5% change in LVEF between preliminary and final report

Proportion of studies the LVEF is changed more than 5% in final report

Average change in LVEF between preliminary and final report

Mean change in LVEF between preliminary and final report

Secondary Outcome Measures

Frequency cardiologist adjusts preliminary annotation

Proportion of studies the annotation is changed

Average change in LVEF between prior clinical report and final report

Mean change in LVEF between prior clinical report and final report

Full Information

NCT ID

NCT05140642

First Posted

November 17, 2021

Last Updated

June 30, 2022

Sponsor

Cedars-Sinai Medical Center

1. Study Identification

Unique Protocol Identification Number

NCT05140642

Brief Title

Safety and Efficacy Study of AI LVEF

Acronym

EchoNet-RCT

Official Title

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

Study Type

Interventional

2. Study Status

Record Verification Date

June 2022

Overall Recruitment Status

Completed

Study Start Date

April 1, 2022 (Actual)

Primary Completion Date

June 29, 2022 (Actual)

Study Completion Date

June 29, 2022 (Actual)

3. Sponsor/Collaborators

Responsible Party, by Official Title

Principal Investigator

Name of the Sponsor

Cedars-Sinai Medical Center

4. Oversight

Studies a U.S. FDA-regulated Drug Product

Studies a U.S. FDA-regulated Device Product

Data Monitoring Committee

5. 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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study

Heart Failure, Systolic, Heart Failure, Diastolic

Keywords

Echocardiogram, Artificial Intelligence

7. Study Design

Primary Purpose

Diagnostic

Study Phase

Not Applicable

Interventional Study Model

Single Group Assignment

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.

Masking

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.

Allocation

Randomized

Enrollment

3495 (Actual)

8. Arms, Groups, and Interventions

Arm Title

Sonographer Annotation

Arm Type

Active Comparator

Arm Description

Arm Title

Artificial Intelligence Annotation

Arm Type

Experimental

Arm Description

Intervention Type

Other

Intervention Name(s)

Automated annotation of the left ventricle through deep learning

Intervention Description

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.

Intervention Type

Other

Intervention Name(s)

Sonographer Measurement of LVEF

Intervention Description

Standard practice sonographer measurement of left ventricle and assessment of LVEF

Primary Outcome Measure Information:

Title

Frequency of >5% change in LVEF between preliminary and final report

Description

Proportion of studies the LVEF is changed more than 5% in final report

Time Frame

10 Minutes

Title

Average change in LVEF between preliminary and final report

Description

Mean change in LVEF between preliminary and final report

Time Frame

10 Minutes

Secondary Outcome Measure Information:

Title

Frequency cardiologist adjusts preliminary annotation

Description

Proportion of studies the annotation is changed

Time Frame

10 Minutes

Title

Average change in LVEF between prior clinical report and final report

Description

Mean change in LVEF between prior clinical report and final report

Time Frame

10 Minutes

10. Eligibility

Sex

All

Minimum Age & Unit of Time

18 Years

Maximum Age & Unit of Time

110 Years

Accepts Healthy Volunteers

Eligibility Criteria

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

Facility Information:

Facility Name

Cedars-Sinai Medical Center

City

Los Angeles

State/Province

California

ZIP/Postal Code

90048

Country

United States

12. IPD Sharing Statement

Plan to Share IPD

Citations:

PubMed Identifier

32269341

Citation

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. Epub 2020 Mar 25.

Results Reference

result

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Safety and Efficacy Study of AI LVEF

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