X-Ray Angiography Images and SYNTAX-Score Dataset

Coronary Heart Disease (CHD) is becoming a leading cause of death worldwide. To assess coronary artery narrowing or stenosis, doctors use coronary angiography, which is considered the gold-standard method. Interventional cardiologists rely on angiography to decide on the best course of treatment for CHD, such as revascularisation with bypass surgery, coronary stents, or medication. However, angiography has some issues, including operator bias, inter-observer variability, and poor reproducibility. Automated interpretation of coronary angiography has not yet been developed, and only highly specialized physicians can perform these tasks. Developing automated angiogram interpretation and coronary artery stenosis estimation using Artificial Intelligence (AI) approaches requires a large dataset of X-ray angiography images that include clinical information. We have collected 232 X-ray images of heart vessels, along with the necessary angiographic variables, including the SYNTAX score, to help advance research on CAD-related machine learning and data mining algorithms. We hope that this dataset will ultimately advance clinical diagnosis in CHD.