Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA

Author:

Brady Adrian P.1ORCID,Allen Bibb23,Chong Jaron4,Kotter Elmar5,Kottler Nina67,Mongan John8,Oakden-Rayner Lauren9,dos Santos Daniel Pinto1011ORCID,Tang An12,Wald Christoph131415,Slavotinek John1617

Affiliation:

1. University College Cork, Cork, Ireland

2. Department of Radiology, Grandview Medical Center, Birmingham, AL, USA

3. Data Science Institute, American College of Radiology, Reston, VA, USA

4. Department of Medical Imaging, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada

5. Department of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany

6. Radiology Partners, El Segundo, CA, USA

7. Stanford Center for Artificial Intelligence in Medicine & Imaging, Palo Alto, CA, USA

8. Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA

9. Australian Institute for Machine Learning, University of Adelaide, Adelaide, SA, Australia

10. Department of Radiology, University Hospital of Cologne, Cologne, Germany

11. Department of Radiology, University Hospital of Frankfurt, Frankfurt, Germany

12. Department of Radiology, Radiation Oncology, and Nuclear Medicine, Université de Montréal, Montréal, QC, Canada

13. Department of Radiology, Lahey Hospital & Medical Center, Burlington, MA, USA

14. Tufts University Medical School, Boston, MA, USA

15. American College of Radiology, Reston, VA, USA

16. South Australia Medical Imaging, Flinders Medical Centre Adelaide, SA, Australia

17. College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia

Abstract

Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever‑growing availability of AI tools in radiology highlights an increasing need to critically evaluate claims for its utility and to differentiate safe product offerings from potentially harmful, or fundamentally unhelpful ones. This multi‑society paper, presenting the views of Radiology Societies in the USA, Canada, Europe, Australia, and New Zealand, defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiological practice. In addition to delineating the main points of concern that developers, regulators, and purchasers of AI tools should consider prior to their introduction into clinical practice, this statement also suggests methods to monitor their stability and safety in clinical use, and their suitability for possible autonomous function. This statement is intended to serve as a useful summary of the practical issues which should be considered by all parties involved in the development of radiology AI resources, and their implementation as clinical tools.

Publisher

SAGE Publications

Reference89 articles.

1. Creative Destruction Lab. Geoff Hinton: On Radiology. 2016. Accessed August 18, 2023. https://www.youtube.com/watch?v=2HMPRXstSvQ.

2. BBC News. AI’godfather’ quits Google over dangers of Artificial Intelligence. 2023. Accessed August 18, 2023. https://www.youtube.com/watch?v=DsBGaHywRhs.

3. Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study

4. GPT-4 for Automated Determination of Radiologic Study and Protocol Based on Radiology Request Forms: A Feasibility Study

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