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

NCT06330103 | Completed

• 1 other identifier: RayongH
• Study Type: interventional
• Target: 923
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Heart Failure; Heart Failure With Reduced Ejection Fraction; Cardiac Failure; Echocardiography; Artificial Intelligence

Outcome Measures

Primary Outcomes (1)

• efficiency of AI in screening left ventricular cardiac function by use smartphone application

  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

Study Arms (2)

LV function from cardiologist

ACTIVE COMPARATOR

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

LV function By artificial intelligence

EXPERIMENTAL

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

Interventions

Easy EF OTHER

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.

Also known as: artificial intelligence, mobile smart phone application

LV function By artificial intelligence; LV function from cardiologist

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• 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

You may not qualify if:

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

Sponsors & Collaborators

• Rayong Hospital: lead
• Chulalongkorn University: collaborator

Study Sites (1)

Rayong Hospital

Rayong, 066, Thailand

Location

MeSH Terms

Conditions

Heart Failure

Interventions

Artificial Intelligence

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Intervention Hierarchy (Ancestors)

Algorithms; Mathematical Concepts

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Model Details: 923 samples that were evaluated for LVEF by certified cardiologists, 739 clips were used to train AI, while the remaining 184 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 Record Dates

• First Submitted: March 5, 2024
• First Posted: March 26, 2024
• Study Start: May 1, 2023
• Primary Completion: July 31, 2023
• Study Completion: July 31, 2023
• Last Updated: March 26, 2024

Record last verified: 2024-03

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP
• Time Frame: 3 month
• Access Criteria: contact rayong hospital

Locations

TH (1)