Integrating artificial intelligence into paediatric interventional radiology: a review of emerging applications and...

Artificial intelligence (AI) is heralded to revolutionise healthcare by improving efficiency, personalising care, and enhancing clinical outcomes. Although interventional radiology (IR) has been at the forefront of adopting AI technologies, their use within paediatric IR remains in early stages. Unlike adult practice, paediatric IR faces unique challenges, including scarcity of age- and pathology-specific datasets, wide anatomical and physiological variability across developmental stages, frequent need for sedation or anaesthesia, and heightened lifetime radiation risk. This review outlines the current and emerging applications of AI across the clinical paediatric IR pathway-such as pre-procedural planning, intra-procedural guidance, and post-procedural follow-up. We highlight areas where adult IR experience may inform paediatric adaption, while examining the technical, ethical, and regulatory considerations unique to children. By highlighting paediatric-specific needs and opportunities, we aim to delineate realistic pathways for safe, equitable, and clinically meaningful AI integration into paediatric IR.