Exploration of fractional flow reservation score based on artificial intelligence post-processing for coronary artery lesions in patients with diabetes and coronary heart disease.

In order to evaluate the relationship between coronary heart disease (CHD) and fractional flow reservation (FFR) in patients with different levels of CHD and diabetes, this paper used AI (artificial intelligence) post-processing technology to detect CHD and FFR. In this paper, 94 patients suspected of CHD who underwent coronary arteriography (CAG) in a hospital between December 2022 and February 2023 were examined by coronary computed tomography angiography (CCTA) and FFR. Based on CCTA, AI software is used to process CCTA images, diagnose coronary plaques, coronary stenosis, corresponding stenosis of different types of plaques, and FFR values. The diagnostic performance of AI was evaluated using expert diagnosis, CAG diagnosis, and FFR examination results as the "gold standard". According to the diagnosis results, the relationship between FFR and CHD patients with diabetes at different levels was studied. The research results showed that AI image diagnosis has high sensitivity, specificity, and accuracy, and has good diagnostic effects on coronary plaques, coronary stenosis, stenosis corresponding to different types of plaques, and FFR values. The fasting blood glucose levels and FFR values of three groups of CHD patients were statistically significant, and correlation analysis revealed a negative correlation between the two. Using AI for CCTA diagnosis can efficiently, conveniently, and accurately obtain the required data, improving clinical diagnostic efficiency and accuracy. The analysis of AI recognition results found that in patients with CHD, the FFR value of patients with diabetes decreased, and the FFR value was negatively correlated with the fasting blood glucose concentration, indicating that CHD patients may lead to myocardial ischemia in the blood supply area due to the decline of their coronary blood flow reserve.