Artificial Intelligence in Radiology: Unlocking New Dimensions of Value

Artificial intelligence (AI) is emerging as a transformative force in radiology, offering the potential to revolutionize the field by enabling sophisticated analysis of complex radiological data and uncovering previously unknown information in medical images.

About a decade after the introduction of clinically applicable AI tools, this article explores the current status, opportunities, and limitations of AI integration in radiological practice. We discuss the growing demand for imaging services, increasing complexity of imaging data, and anticipated workforce shortages. Moreover, the role of large language models, computer vision, and automation in improving diagnostic accuracy, workflow efficiency, and patient communication is highlighted. We also examine the evolving European regulatory framework, including the AI Act, MDR (Medical Device Regulation), and EHDS (European Health Data Space), and their implications for the safe and ethical deployment of AI in clinical settings.

Radiology, as a highly digitalized and data-rich specialty, is uniquely positioned to benefit from AI-driven innovations across the entire clinical workflow - from patient scheduling to diagnosis and report generation. Challenges, such as the increasing complexity of imaging data or workforce shortages, further underscore the need for selective, well-validated AI-supported solutions. Despite its promise, current limitations such as data quality, model interpretability, or integration barriers, as well as lack of reimbursement, remain critical challenges.

This review underscores the need for thoughtful implementation to fully realize AI's potential as an enabling infrastructure in radiology that makes imaging-based healthcare more efficient, accurate, and accessible.

· Artificial intelligence is emerging as a transformative force in diagnostic and interventional radiology.. · This article explores the status, opportunities, and limitations of clinically applicable AI tools.. · The article reviews the evolving European regulatory framework for AI deployment.. · The review highlights the need for interdisciplinary collaboration and well-planned AI implementation based on benefits and evidence..

· Bamberg F, Adam G, Antoch G et al. Artificial Intelligence in Radiology: Unlocking New Dimensions of Value. Rofo 2026; DOI 10.1055/a-2794-9496.