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AI-CXR: Feasibility of AI-based Heart Function Prediction Model Using CXR

Sponsor
Yonsei University (Other)
Overall Status
Recruiting
CT.gov ID
NCT04996381
Collaborator
(none)
500
Enrollment
1
Location
10
Anticipated Duration (Months)
49.9
Patients Per Site Per Month

Study Details

Study Description

Brief Summary

The investigators will develop an artificial intelligence model to predict left ventricular ejection fraction using chest radiographic images and transthoracic echocardiography data.

Condition or Disease Intervention/Treatment Phase
  • Diagnostic Test: Scanning Chest X-rays and performing AI algorithms on images

Detailed Description

Echocardiography should be considered at an early stage in patients who have first developed heart failure or who do not have information about heart function, but the examination may be delayed due to lack of time and manpower in the actual medical field.

Primary Objective: Use chest radiographs to predict the left ventricular ejection fraction

Study Design

Study Type:
Observational
Anticipated Enrollment :
500 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Feasibility of Artificial Intelligence-based Heart Function Prediction Model Using Chest Radiography
Actual Study Start Date :
Mar 1, 2022
Actual Primary Completion Date :
Jun 30, 2022
Anticipated Study Completion Date :
Dec 31, 2022

Outcome Measures

Primary Outcome Measures

  1. Left Ventricular Ejection Fraction < 40% [Within two weeks of chest X-ray]

    Evaluate the performance of chest X-ray based artificial intelligence algorithms to identify individuals with reduced ejection fraction (<40%)

Eligibility Criteria

Criteria

Ages Eligible for Study:
20 Years to 90 Years
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
Inclusion Criteria:

  • Adults who are 20 years and older

  • Patient who visited the emergency room or outpatient clinic due to dyspnea and chest pain

Exclusion Criteria:

  • Patient refusal

  • Uncertain radiographs or transthoracic echocardiography

  • Uncertain tests results

Contacts and Locations

Locations

Site City State Country Postal Code
1 Yongin Severance Hospital Yongin Giheung-gu Korea, Republic of 16995

Sponsors and Collaborators

  • Yonsei University

Investigators

  • Study Chair: In Hyun Jung, MD, PhD, Yongin Severance Hospital, Yonsei University College of Medicine

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
SungA Bae, MD. PhD., Yonsei University
ClinicalTrials.gov Identifier:
NCT04996381
Other Study ID Numbers:
  • YonseiU
First Posted:
Aug 9, 2021
Last Update Posted:
Jul 1, 2022
Last Verified:
Jun 1, 2022
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No

Study Results

No Results Posted as of Jul 1, 2022