Clinical trial NCT06783933: Artificial Intelligence-assisted Diagnosis
Official title: Artificial Intelligence-assisted Diagnosis of Congenital Heart Diseases on Chest X-ray
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Congenital Heart Disease (CHD)
Structural Heart Disease
Keywords: artificial intelligence；congenital heart diseases；Chest X-ray；diagnosis
Lead sponsor: China National Center for Cardiovascular Diseases
Sponsor class: OTHER_GOV
Collaborators: name: Beijing Anzhen Hospital
name: Nanjing Medical University
name: Shanghai Jiao Tong University School of Medicine
name: Capital Medical University
name: Sichuan University
name: Kunming Medical University
name: Anhui Medical University
name: Shandong University
name: Zhejiang University
name: Peking University
name: Peking Union Medical College
name: Harbin Medical University
name: Xi'an Jiaotong University
name: Huazhong University of Science and Technology
name: Guangdong Provincial People's Hospital
name: Wuhan University
name: Central South University
name: University of Chinese Academy of Sciences
First posted: 2025-01-20
Enrollment: 8000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: This study will enroll subjects with CHD and structural heart diseases.

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 3000 patients is reached.

Phase 2: Prospective inclusion of general patients with chest X-ray. A minimum of 5000 patients is reached.

Eligibility criteria: 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

Primary outcomes:
measure: accuracy with AI-assisted diagnosis
timeFrame: 12 months
Secondary outcomes:
Other outcomes:
Locations:
city: Beijing
country: China
facility: Fuwai hospital
state: Beijing
Study officials:
affiliation: Fuwai Hospital, Beijing, China
name: Shihua Zhao, MD and PhD
role: STUDY_CHAIR
References: