In JACC. Asia
Percutaneous coronary intervention has been a standard treatment strategy for patients with coronary artery disease with continuous ebullient progress in technology and techniques. The application of artificial intelligence and deep learning in particular is currently boosting the development of interventional solutions, improving the efficiency and objectivity of diagnosis and treatment. The ever-growing amount of data and computing power together with cutting-edge algorithms pave the way for the integration of deep learning into clinical practice, which has revolutionized the interventional workflow in imaging processing, interpretation, and navigation. This review discusses the development of deep learning algorithms and their corresponding evaluation metrics together with their clinical applications. Advanced deep learning algorithms create new opportunities for precise diagnosis and tailored treatment with a high degree of automation, reduced radiation, and enhanced risk stratification. Generalization, interpretability, and regulatory issues are remaining challenges that need to be addressed through joint efforts from multidisciplinary community.
Chu Miao, Wu Peng, Li Guanyu, Yang Wei, Gutiérrez-Chico Juan Luis, Tu Shengxian
2023-Feb
CAD, coronary artery disease, CCTA, coronary computed tomography angiography, CMRA, coronary magnetic resonance angiography, CNN, convolutional neural network, DL, deep learning, FFR, fractional flow reserve, IVUS, intravascular ultrasound, OCT, optical coherence tomography, PCI, percutaneous coronary intervention, artificial intelligence, coronary artery disease, coronary imaging, deep learning
