Deep Learning Algorithm for Detecting Obstructive Coronary Artery Disease Using Fundus Photographs

Launched by YONG ZENG · Oct 22, 2023

Keywords

ClinConnect Summary

This clinical trial is exploring how artificial intelligence (AI) can help detect heart disease by analyzing photographs of the back of the eye, known as fundus photographs. The researchers believe that by using deep learning—a type of AI that learns from data—they can identify signs of coronary artery disease (CAD) more quickly and accurately. This is important because currently, there are not many effective tools for early screening of heart disease, especially in places like China.

To participate in the trial, individuals need to be at least 18 years old, suspected of having coronary artery disease, and scheduled to undergo a specific heart test called coronary angiography. However, those who have already had certain heart procedures or other specific heart conditions may not be eligible. Participants will have their eye photographs taken, which will be used to help develop a model that could make diagnosing heart disease easier in the future. Before joining the study, everyone will be fully informed and must agree to participate.

Gender

ALL

Eligibility criteria

• 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.