Efficacy of AI EF Screening by Using Smartphone Application Recorded PLAX View Cardiac Ultrasound Video Clips

March 18, 2024 updated by: Sittiluck Wongwantanee, Rayong Hospital

Assessing the Efficacy of Artificial Intelligence in Left Ventricular Function Screening Using Parasternal Long Axis View Cardiac Ultrasound Video Clips

Assessing the Efficacy of Artificial Intelligence in Left Ventricular Function Screening Using Parasternal Long Axis View Cardiac Ultrasound Video Clips

ABSTRACT BACKGROUND: Echocardiography serves as a fundamental diagnostic procedure for managing heart failure patients. Data from Thailand's Ministry of Public Health reveals that there is a substantial patient population, with over 100,000 admissions annually due to this condition. Nevertheless, the widespread implementation of echocardiography in this patient group remains challenging, primarily due to limitations in specialist resources, particularly in rural community hospitals. Although modern community hospitals are equipped with ultrasound machines capable of basic cardiac assessment (e.g., parasternal long axis view), the demand for expert cardiologists remains a formidable obstacle to achieving comprehensive diagnostic capabilities. Leveraging the capabilities of Artificial Intelligence (AI) technology, proficient in the accurate prediction and processing of diverse healthcare data types, offers a promising for addressing this prevailing issue. This study is designed to assess the effectiveness of AI in evaluating cardiac performance from parasternal long axis view ultrasound video clips obtained via the smartphone application.

OBJECTIVES: To evaluate the effectiveness of artificial intelligence in screening cardiac function from parasternal long axis view cardiac ultrasound video clips obtained through the smartphone application.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

METHODS: The investigators built the smartphone application to collect parasternal long axis view video clips and used artificial intelligence "Easy EF" to evaluate cardiac function. All samples that were evaluated for LVEF by certified cardiologists, 70% of all clips were used to train AI, while the remaining 30% of clips were used to test if AI could process the results correctly. Artificial intelligence aims to classify cardiac function into three groups: Reduced EF, Mildly Reduced EF, and Preserved LV.

Study Type

Interventional

Enrollment (Actual)

923

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Thailand
      • Rayong, Thailand, 066
        • Rayong Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Shot 5 second VDO clip of Parasternal long axis heart ultrasound recorded by smartphone Application "Easy EF" without patient identification with result of Ejection fraction that performed by certify cardiologist approved result

Exclusion Criteria:

  • Incomplete VDO clip (too much shaking, too shot recording)
  • Lighting was inappropriate
  • Inappropriate ultrasound framing
  • arrhythmia (atrial fibrillation)

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Non-Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Active Comparator: LV function from cardiologist
Certified Cardiologist will access and interpreted LV function by used traditional Echocardiography then separate result into three group Preserved LV ejection fraction(EF>50%), mildly reduce ejection fraction(EF40-49%), reduced LV ejection fraction(EF<40%)
Other: Easy EF
AI was integrated into the application smartphone and used smartphone camera to recorded shot VDO clip of heart ultrasound in parasternal long axis view and returned cardiac function result to user.
Other Names:
  • artificial intelligence
  • mobile smart phone application
Experimental: LV function By artificial intelligence
AI will access VDO clips in only parasternal long axis view and separate into three group Preserved LV ejection fraction(EF>50%), mildly reduce ejection fraction(EF40-49%), reduced LV ejection fraction(EF<40%)
Other: Easy EF
AI was integrated into the application smartphone and used smartphone camera to recorded shot VDO clip of heart ultrasound in parasternal long axis view and returned cardiac function result to user.
Other Names:
  • artificial intelligence
  • mobile smart phone application

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
efficiency of AI in screening left ventricular cardiac function by use smartphone application
Time Frame: 3 month
percentage of correct LV function clip that interpreted by AI in each LV function group(Preserved LV, Mildly reduced LV, Reduced LV function) and overall compare with result from certified cardiologist
3 month

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Rayong Hospital

Collaborators

Chulalongkorn University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 1, 2023

Primary Completion (Actual)

July 31, 2023

Study Completion (Actual)

July 31, 2023

Study Registration Dates

First Submitted

March 5, 2024

First Submitted That Met QC Criteria

March 18, 2024

First Posted (Actual)

March 26, 2024

Study Record Updates

Last Update Posted (Actual)

March 26, 2024

Last Update Submitted That Met QC Criteria

March 18, 2024

Last Verified

March 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • RayongH

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

result of AI screening

IPD Sharing Time Frame

3 month

IPD Sharing Access Criteria

contact rayong hospital

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Heart Failure

Clinical Trials on Easy EF

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in Mozambique

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

3
Subscribe