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

Congenital Heart Disease in Children Clinical Trial

Official title:

Multi-center Study on Exploration and Application of Artificial Intelligence Technology-Assisted Heart Sound Recognition System in Children's Congenital Heart Disease Screening

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04307030
• Other study ID #: XH-20-003
• Status: Recruiting
• Start date: July 1, 2020
• Est. completion date: June 30, 2023

Study information

• Verified date: April 2023
• Source: Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
• Contact: KUN SUN, MD
• Phone: 8621-25076045
• Email: drsunkun[@]xinhuamed.com.cn
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 5000
• Est. completion date: June 30, 2023
• Est. primary completion date: December 31, 2021
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: N/A to 18 Years

Eligibility

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.

Related Conditions & MeSH terms

• Congenital Heart Disease in Children
• Heart Defects, Congenital
• Heart Diseases

Intervention

Diagnostic Test:
• Heart Auscultation and Echocardiography
Heart auscultation will be done by cardiovascular pediatrician and echocardiography by echocardiologist

Locations

Country	Name	City	State
China	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	Children's Hospital of Shanghai	Shanghai
China	Shanghai Children's Medical Center	Shanghai
China	Shiyan Taihe Hospital	Shiyan
China	Children's Hospital of Soochow University	Suzhou
China	The Second Hospital Affiliated to Wenzhou Medical University	Wenzhou
China	Wuhan Children's Hospital	Wuhan

Sponsors (1)

Lead Sponsor	Collaborator
Xinhua Hospital, Shanghai Jiao Tong University School of Medicine

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Receiver operating characteristic (ROC) of sensitivity	ROC of sensitivity in CHD screening by different artificial intelligence algorithm and auscultation	July 2020 to December 2021