Congenital Heart Disease (CHD), Structural Heart Disease
Conditions
Keywords
artificial intelligence；congenital heart diseases；Chest X-ray；diagnosis
Brief summary
This study aims to investigate whether an AI-assisted decision support can improve the diagnosis of congenital heart diseases on Chest X-ray.
Detailed description
Congenital heart disease (CHD) is a structural abnormality of the heart and/or great vessels and the frequency of CHD is nearly 1% in general population. In clinical practice, Chest X-ray is an important routine method for detection of CHD. However, its learning curve is high. Based on Chest X-ray, Artificial intelligence (AI) has the potential to improve the efficiency and accuracy of CHD. This study aims to investigate whether an AI-assisted decision support can improve the diagnosis of congenital heart diseases on Chest X-ray. This study will enroll subjects with CHD, and the enrollment will be divided into two phases. Phase 1: Previous data of chest X-ray in patients with CHD. A minimum of 5000 patients is reached. Phase 2: Prospective inclusion of general patients with chest X-ray. A minimum of 50000 patients is reached.
Interventions
DIAGNOSTIC_TESTsurgical or interventional validation
surgical or interventional validation
Sponsors
Beijing Anzhen Hospital
Nanjing Medical University
Shanghai Jiao Tong University School of Medicine
Capital Medical University
Sichuan University
Kunming Medical University
Anhui Medical University
Shandong University
Zhejiang University
Peking Union Medical College
Harbin Medical University
Xi'an Jiaotong University
Huazhong University of Science and Technology
Guangdong Provincial People's Hospital
Wuhan University
Central South University
University of Chinese Academy of Sciences
The First Hospital of Hebei Medical University
Handan First Hospital
Second Affiliated Hospital of Wenzhou Medical University
Anyang Maternal and Child Health Care Center
Wenzhou Medical University
Guangxi Medical University
Xinjiang Medical University
Chongqing General Hospital
Tibet Autonomous Region People's Hospital
The Affiliated Hospital of Zunyi Medical College
Second Affiliated Hospital of Nanchang University
Second Xiangya Hospital of Central South University
Second Hospital of Shanxi Medical University
Handan Central Hospital
Affiliated First Hospital of Ningxia Medical University
Chinese Academy of Medical Sciences, Fuwai Hospital
Xijing Hospital
Inner Mongolia People's Hospital
Qinghai province cardiovascular and cerebrovascular disease specialist hospital
Second Affiliated Hospital, School of Medicine, Zhejiang University
China Medical University, China
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Qilu Hospital of Shandong University
Tianjin Medical University General Hospital
Hainan General Hospital
Fujian Medical University
Lanzhou University Second Hospital
Second Hospital of Jilin University
Zunyi Medical College
Ningxia Medical University
LanZhou University
Jilin University
West China Hospital
Peking University
Fudan University
Ruijin Hospital
Zhengzhou University
China National Center for Cardiovascular Diseases
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Healthy volunteers
Yes
Inclusion criteria
1. Chest X-ray of patients with ASD; 2. Chest X-ray of patients with VSD; 3. Chest X-ray of patients with PDA; 4. Chest X-ray of patients with PFO; 5. Chest X-ray of patients with PS; 6. Chest X-ray of patients with TOF/PAA; 7. Chest X-ray of patients with MS; 8. Chest X-ray of patients with other heart diseases;
Exclusion criteria
1. CHD Patients without surgical, interventional validation; 2. Serious Scoliosis; 3. Pulmonary inflammation or consolidation
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| accuracy with AI-assisted diagnosis | 12 months | Number of subjects with accuracy of CHD ; based on surgical validation or interventional validation. |
Countries
China
Outcome results
None listed