Chapter 2 - Technology boosted diagnosis and advanced procedural planning in endovascular surgery - Robot-mediated vascular ultrasound imaging: a promising technology for vascular diagnosis and screening programs

This volume highlights SICVE’s strong interest in the most recent technological innovations that may enable major advances in vascular surgery and medical science. Across history, human progress has been driven by our unique capacity to invent tools and techniques that improve survival and reshape both society and the environment. Scientific development often proceeds through stable phases and sudden paradigm shifts, as described by Thomas Kuhn, and we are currently living through one of these transitions. Since the early 2000s, the Digital Revolution has rapidly expanded, evolving into what many call the Fourth Industrial Revolution, characterized by the convergence of physical, digital, and biological domains. Advances in artificial intelligence, robotics, IoT, 3D printing, genomics, nanotechnology, and quantum computing are transforming medicine and redefining the relationship between humans and intelligent machines. In this new scenario, healthcare is becoming increasingly dependent on digital data (electronic records, imaging, bioinformatics, apps, telemedicine, and wearable sensors) generating massive databases at an unprecedented scale. Modern medicine, including vascular surgery, is entering an era in which the physician is increasingly supported by a “Universal Intelligent Machine” capable of rapidly processing enormous amounts of global clinical knowledge, enhancing perception beyond human sensory limits, and supporting complex planning through tools such as machine learning, cognitive computing, and immersive technologies (virtual/augmented reality). While evidence-based medicine remains foundational, algorithmic systems are expanding their role in interpreting big and long data, potentially influencing or replacing certain medical decisions. However, significant caution is required. Current AI systems still suffer from limitations and biases, often due to inadequate training data and methodological weaknesses. Experts emphasize the need for robust prospective studies comparing clinical outcomes with and without algorithm-based support, rather than simplistic doctor-versus-AI comparisons. Since medical decisions affect human lives, adoption of AI must be supported by clear evidence and should avoid “pro-innovation bias,” which can lead to uncritical enthusiasm. A central principle remains that humans must retain final responsibility: ethical, legal, social, psychological, and holistic judgement cannot be delegated to machines. At the same time, medicine is evolving toward precision and personalized approaches, alongside participatory, predictive, preventive, and initiative healthcare—Hood’s “4P medicine.” Research is also shifting from isolated laboratory settings toward real-world, large-scale, network-driven processes enabled by computational systems. Looking further ahead, thinkers such as Ray Kurzweil and Roberto Marchesini suggest that accelerating progress in AI, nanotechnology, and genetic engineering may lead to transformative “post-human” scenarios, including hybrid intelligence and new forms of collective cognition. Ultimately, the new medical paradigm should not erase previous models but integrate and expand them, just as scientific revolutions have historically encompassed earlier theories. Both patients and physicians are already contributing, often unknowingly, to the emergence of a New Medicine shaped by technological innovation and a growing collective health consciousness.