Radiology Societies Issue Joint Statement on AI Tools in Radiology: Revolutionizing Healthcare Practices and Ensuring Safety
The Radiological Society of North America (RSNA), along with the American College of Radiology (ACR) and three other prominent radiology societies, have come together to issue a joint statement on the development and use of artificial intelligence (AI) tools in radiology. The statement, published in RSNA’s journal, Radiology: Artificial Intelligence, highlights the immense potential of AI in revolutionizing healthcare practices while emphasizing the importance of ensuring safety.
According to RSNA President Curtis P. Langlotz, M.D., Ph.D., AI tools are an essential part of radiology’s future, as they enhance medical imaging through improved diagnosis, quantification, and management of various medical conditions. RSNA is committed to supporting the responsible use of AI in medical imaging, encompassing the pillars of education, research, and technological innovation.
The joint statement, titled Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RA, NZCR and RSNA, was drafted by representatives from RSNA, ACR, the Canadian Association of Radiologists, the European Society of Radiology, and the Royal Australian and New Zealand College of Radiologists.
Charles E. Kahn Jr., M.D., M.S., the editor of Radiology: Artificial Intelligence, emphasized the significance of this statement, stating that it provides vital guidance for the radiology profession. The document addresses key concerns related to the development, implementation, and monitoring of AI systems in clinical practice. It also emphasizes the need to differentiate safe and effective AI offerings from potentially harmful ones.
The multi-society paper identifies various practical problems and ethical issues surrounding the integration of AI into radiology practice. In addition to highlighting main areas of concern for developers, regulators, and purchasers of AI tools, the statement proposes methods for monitoring the stability and safety of these tools in clinical use and assessing their suitability for potential autonomous function.
John Mongan, M.D., Ph.D., a radiologist, 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, expressed the statement’s importance. Mongan stated, This statement will serve as both a guide for practicing radiologists on how to safely and effectively implement and use available AI today, and a roadmap for developers and regulators on how to approach delivering improved AI for tomorrow.
The authors of the statement address key issues regarding the integration of AI into medical imaging workflows. They stress the need for increased monitoring of AI’s utility and safety when incorporated into clinical practice. Additionally, they emphasize the importance of collaboration between developers, clinicians, and regulators to address ethical concerns and monitor AI performance effectively.
To ensure AI fulfills its promise in advancing patient well-being, rigorous evaluation and clear understanding of all stages from development to long-term integration in healthcare are crucial. The multi-society statement provides comprehensive guidance for developers, purchasers, and users of AI in radiology, prioritizing patient and societal safety and well-being.
This joint statement from leading radiology societies sets the stage for responsible AI implementation in radiology, paving the way for the future of healthcare. Through education, research, and innovation, AI tools hold the potential to transform medical imaging, supporting radiologists in providing accurate diagnoses and improving patient outcomes. The collaboration between these societies demonstrates a commitment to harnessing the power of AI while ensuring the highest standards of safety and efficacy in its application.
References:
– Radiology: Artificial Intelligence, journal.rsna.org
– Radiological Society of North America (RSNA), www.rsna.org
