Innovation and AI in Endourology: An Overview from EAU Endourology.

PURPOSE OF REVIEW: Advancements in technology have been at the heart of endourology for decades. With the introduction of new and novel technologies, endourology is rapidly changing. This review aims to address the recent innovations and technological advances in endourology by addressing four different areas where tangible outcome improvements are being seen: (1) diagnostic and detection methods; (2) intraoperative optimisation and procedural automation; (3) prediction of treatment outcomes; and (4) the use of generative Artificial Intelligence (AI) and Large Language Models (LLMs) for patients' education and monitoring. RECENT FINDINGS: AI applications in endourology consistently demonstrate high diagnostic accuracy, with stone detection rates exceeding 95% across imaging modalities. Emerging tools include non-invasive analysis of stone composition and real-time intraoperative segmentation. Intraoperative improvements involve augmented reality-guided renal access, which has reduced puncture times, fluoroscopy exposure, and complications. New instruments, such as flexible, navigable suction devices (FANS) and intrarenal pressure (IRP) and temperature (IRT) monitoring systems, bring the field closer to achieving the endourological quadrifecta. Machine learning models trained on multicentre data can predict perioperative risks and personalise treatment, demonstrating similar effectiveness in managing stone disease. Additionally, generative AI and large language models are increasingly used for clinical documentation, patient communication, and outpatient workflows. However, concerns about hallucination, data privacy, and the need for human oversight remain significant in this growing area. Innovation, technology, and AI in endourology are advancing rapidly, introducing new ideas that are integrated into surgical procedures. These innovations offer numerous benefits to patients at various stages of treatment, leading to improved surgical results. Although combining these technologies can potentially maximise patient benefits, a careful and selective approach should be adopted, accompanied by thorough assessments before implementing these new innovations.