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RSNA publishes joint statement on use of AI tools in radiology

The multi‑society paper defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiology practice

RSNA and four other radiology societies from around the world have issued a joint statement on the development and use of artificial intelligence (AI) tools in radiology. The statement was published in RSNA’s journal, Radiology: Artificial Intelligence.

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“AI tools are an essential part of radiology’s future,” said RSNA President Curtis P Langlotz. “RSNA is committed to supporting the responsible use of AI in medical imaging through all three pillars of its mission: education, research, and technological innovation.” 

“Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA” was drafted by representatives of RSNA, the American College of Radiology, the Canadian Association of Radiologists, the European Society of Radiology and the Royal Australian and New Zealand College of Radiologists. 

“This statement from RSNA and other leading radiology societies provides important guidance for our profession,” said Charles E Kahn Editor, Radiology: Artificial Intelligence. “It identifies key concerns that must be addressed to develop, implement, and monitor AI systems for clinical practice.” 

The multi‑society paper defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiology practice. In addition to delineating the main points of concern that developers, regulators, and purchasers of AI tools should consider before their introduction into clinical practice, the statement also suggests methods to monitor the tools for stability and safety in clinical use, and to assess their suitability for possible autonomous function. 

“This statement will serve as both a guide for practising radiologists on how to safely and effectively implement and use the AI that’s available today, and a roadmap for developers and regulators on how to approach delivering improved AI for tomorrow,” said statement co-author John Mongan, Radiologist and Vice Chair of Informatics in the Department of Radiology and Biomedical Imaging at the University of California, San Francisco, and chair of the RSNA Artificial Intelligence Committee. 

The authors address several key issues surrounding the integration of AI into medical imaging workflow. They note that AI incorporation into clinical practice demands increased monitoring of its utility and safety. They also stress that cooperation between developers, clinicians and regulators is critical, to allow all involved to address ethical issues and monitor AI performance. 

 

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