Application of Artificial Intelligence in Interventional Radiology

Interventional medicine (IM) is a specialized field within medicine that uses needles and catheters to treat diseases under the guidance of medical imaging. IM has irreplaceable advantages, such as accurate lesion localization, minimal trauma, fewer complications, rapid and outstanding response after intervention, and good repeatability. After more than 30 years of development, interventional therapy is considered one of the three pillar disciplines, together with traditional surgery and internal medicine. However, traditional interventional radiology has some significant drawbacks: (1) exposure to X-rays during the procedure poses long-term health risks for doctors; (2) existing surgical methods require advanced skills and involve high risks, leading to long training for doctors; and (3) factors such as complex operations, long procedure duration, doctor fatigue, and unstable manual operations directly affect surgical quality and subsequently impact patient outcomes. These clinical challenges impose a great burden on interventional radiology. With the rapid pace of technological innovation, artificial intelligence (AI) has been increasingly used in the medical field. Specifically, the value of AI in interventional radiology has been manifested in the following aspects: medical image processing, surgical navigation, reduced radiation exposure, target tracking technologies, and the development of interventional surgical robots by integrating the abovementioned technologies. In summary, the emergence of AI provides an innovative method for accurate, intelligent, safe, and efficient interventional radiology.