Study on AI Recognition System Of Heart Sound In Congenital Heart Disease Screening

Recruiting

• Conditions: Congenital Heart Disease in Children

• Registration Number: NCT04307030
• Lead Sponsor: Xinhua Hospital, Shanghai Jiao Tong University School of Medicine

Brief Summary

The objective of this study is to establish AI algorithm based on the deep learning to strengthen the ability to classify the heart murmurs of healthy people and different major or other subdivided congenital heart diseases(CHDs) and to evaluate the effectiveness of artificial intelligence technology-assisted heart sound recognition system (referred to as: Heart sound AI recognition system) for multi-center CHD screening.

Detailed Description

This is a multi-center cluster cross-sectional study in CHINA. Heart sounds will be collected by auscultation using an electronic stethoscope in children (0 \~ 18 years old) confirmed with or without CHDs by echocardiography during outpatient or hospitalization in 10 pediatric medical centers. Heart sounds will be visualized as phonocardiogram, and feature extraction will be done after classification of normal and abnormal heart sounds and labeling the characteristics of heart murmurs by pediatric cardiovascular specialists. Artificial intelligence algorithm (machine learning, deep learning, etc.) will be trained to build a heart sounds recognition system with the data mentioned above.We will use the receiver operating characteristic (ROC) curve to compare the ability of recognition and classification of abnormal heart sounds between different artificial intelligence algorithm. Taken the results of echocardiography as the gold standard, we will use the evaluation indexes,such as sensitivity, specificity, accuracy, positive predictive value, negative predictive value, etc, to compare the diagnostic capacity of CHD screening between the AI recognition system and human cardiovascular pediatricians. Our target is to use artificial intelligence technology to assist heart auscultation for CHD screening.

Study Timeline

• Study First Submitted: 2020-03-11
• Study First Submitted QC: 2020-03-11
• Study First Posted: 2020-03-13
• Study Start: 2020-07-01
• Primary Completion: 2021-12-31
• Status Verified: 2023-04
• Last Update Submitted: 2023-04-19
• Last Update Posted: 2023-04-21
• Study Completion: 2023-06-30

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 5000

Inclusion Criteria

1. 0 ~ 18 years of age, regardless of gender ；
2. Children with or without congenital heart disease confirmed by echocardiography；
3. On the basis of informed consent，willing to cooperate with our group.

Exclusion Criteria

1. ≥ 18 years of age;
2. Children who can not undergo echocardiography or other related tests;
3. Subjects who refuse to join in, or who are unwilling to cooperate with the provision of diagnostic and therapeutic data for further analysis and research.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Receiver operating characteristic (ROC) of sensitivity	July 2020 to December 2021	ROC of sensitivity in CHD screening by different artificial intelligence algorithm and auscultation

Trial Locations

Locations (16)

Beijing Anzhen Hospital; 🇨🇳 Beijing, China

Children's Hospital Affiliated to Chongqing Medical University; 🇨🇳 Chongqing, China

The First Affiliated Hospital of Guangxi Medical University; 🇨🇳 Guangxi, China

Guangzhou Women and Children's Medical Center; 🇨🇳 Guangzhou, China

Children's Hospital Affiliated to Zhejiang Medical University; 🇨🇳 Hangzhou, China

Hunan Children's Hospital; 🇨🇳 Hunan, China

Shandong Provincial Hospital; 🇨🇳 Jinan, China

Kunming Children's Hospital; 🇨🇳 Kunming, China

Lanzhou University Second Hospital; 🇨🇳 Lanzhou, China

Linyi Hospital for Women and Children; 🇨🇳 Linyi, China

Scroll for more (6 remaining)