Artificial intelligence (AI) is profoundly changing the future of radiology, particularly due to the high diagnostic performance of current models. Since the 1950s, computer scientists have worked on enhancing human-like cognitive capabilities of algorithms, with impressive results in combined vision and language models that are slowly gaining acceptance into interventional radiology (IR).1

Despite these advances, the potential of AI for enhancing physical capabilities through robotics and image interpretation is less widely understood by interventional radiologists. Our community built a multimodal approach to treating patients with real-time imaging and device manipulation. While the rapid adoption of computer vision in both diagnostic and interventional radiology is indicative of the wide acceptance of its utility in solving many imaging-related challenges, most IRs struggle to find AI applications to their procedural practice.

As interventional radiologists, we believe that our manual skills, such as using specialized devices and guiding them inside the patient, are the most important part of our work. However, this focus on manual capabilities may change with the revolution in robotics and AI—the so-called robolution. As technology advances, AI and robotics will assist in or even take over certain physical tasks that humans currently perform. Robots, guided by AI, could potentially improve precision, reduce fatigue, and allow for more complex procedures, thus changing how IRs approach their work. The rise of robotics in IR could shift the balance from manual skills to more technologically driven practices, where AI and robotics play a bigger role alongside human expertise.

The history of robotics in medicine dates to the 1980s, with the development of the first surgical robots. However, it wasn't until the late 1990s and early 2000s that robotic systems began to gain significant acceptance into clinical practice.2 While this technology has led to advances in other fields, its penetration in everyday clinical IR is still limited. Systems like the Da Vinci surgical robot have gained acceptance by the surgical community, and in many procedures, operators utilizing them can augment their agility and improve patient outcomes.3, 4, 5, 6

The early stages of robotics in IR focused on percutaneous procedures, with systems primarily assisting in biopsies and tumor ablations.7 These robots, often guided by CT or fluoroscopy, offered improved accuracy and precision compared to manual techniques. One of the earliest systems was the CT-integrated robot developed by Yanof et al., which demonstrated the feasibility of robotic assistance in percutaneous interventions.8 The mid-2000s marked a turning point with the introduction of FDA-approved endovascular robotic systems. The Sensei X system (Hansen Medical) emerged as a pioneer in endovascular procedures by enabling remote catheter manipulation.9 However, these first-generation systems faced limitations in terms of flexibility and range of motion, particularly when navigating small or tortuous vessels.10

In this article, we will review the current state of robotics in the field of IR. We will also cover how AI imaging techniques have been increasing the rate of progress in this field.