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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT06102226
Other study ID # 121100004006885458
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date July 1, 2021
Est. completion date December 30, 2024

Study information

Verified date October 2023
Source Beijing Anzhen Hospital
Contact yong zeng, Dr
Phone +8613501373114
Email yzeng_anzhen@163.com
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Artificial Intelligence, trained through model learning, can quickly perform medical image recognition and is widely used in early disease screening and assisted diagnosis. With the continuous optimization of deep learning, the application of AI has helped to discover some previously unknown associations with other systemic diseases. Artificial intelligence based on retinal fundus images can be used to detect anemia, hepatobiliary diseases, and chronic kidney disease, and to predict other systemic biomarkers. The above studies provide a theoretical basis for the application of artificial intelligence technology based on retinal fundus images to the diagnosis and prediction of cardiovascular diseases. At present, there is still a lack of accurate, rapid, and easy-to-use diagnostic and therapeutic tools for predictive modeling of coronary heart disease risk and early screening tools in China and the world. Fundus image is gradually used as a tool for extensive screening of diseases due to its special connection with blood vessels throughout the body, as well as easy access, cheap and efficient. It is of great scientific and social significance to develop and validate a model for identification and prediction of coronary heart disease and its risk factors based on fundus images using AI deep learning algorithms, and to explore the value of AI fundus images in assisting coronary heart disease diagnosis and screening for a wide range of applications.


Recruitment information / eligibility

Status Recruiting
Enrollment 7000
Est. completion date December 30, 2024
Est. primary completion date August 1, 2024
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years to 80 Years
Eligibility Inclusion Criteria: Eligible participants were = 18 years of age, with clinically suspected CAD, and were scheduled for coronary angiography. Exclusion Criteria: The exclusion criteria were as follows: (i) prior percutaneous coronary intervention (PCI); (ii) prior coronary artery bypass graft (CABG); (iii) other heart disease (e.g., congenital heart disease, valvular heart disease, or macrovascular disease); (iv) inability to have photographs taken; and (v) and a diagnosis of ST-segment elevation myocardial infarction (STEMI). Prior to the coronary angiography procedure, all eligible patients provided informed consent to participate in the study and to have their photographs used for research purposes.

Study Design


Intervention

Diagnostic Test:
coronary artery imaging (coronary CTA or coronary angiography)
In order to obtain the gold standard labeling for coronary heart disease, this topic will form a panel of experts on labeling, and the diagnosis will be based on coronary angiography, defined as a lesion with a stenosis of at least 50% in at least one coronary artery

Locations

Country Name City State
China Yong Zeng Beijing ??

Sponsors (1)

Lead Sponsor Collaborator
Yong Zeng

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary AUC To evaluate the algorithm performance area under the receiver operating characteristic curve (AUC) were calculated December 30, 2024
Secondary sensitivity To evaluate the algorithm performance, the sensitivity were calculated December 30, 2024
Secondary specificity To evaluate the algorithm performance, the specificity were calculated December 30, 2024
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