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Congress: ECR24
Poster Number: C-10913
Type: EPOS Radiologist (scientific)
Authorblock: J. H. R. Cairns, B. Riley, H. Ismail, B. Al-Qaisieh, M. Siddique, C. Herbert, B. Wheller, F. U-H. Chowdhury, A. Scarsbrook; Leeds/UK
Disclosures:
James Henry Robert Cairns: Nothing to disclose
Beverley Riley: Nothing to disclose
Hanif Ismail: Nothing to disclose
Bashar Al-Qaisieh: Nothing to disclose
Mohua Siddique: Nothing to disclose
Christopher Herbert: Nothing to disclose
Bob Wheller: Nothing to disclose
Fahmid Ul-Haque Chowdhury: Nothing to disclose
Andrew Scarsbrook: Nothing to disclose
Keywords: Artificial Intelligence, Computer applications, Management, CT, Nuclear medicine conventional, Plain radiographic studies, Cost-effectiveness, Health policy and practice, Technology assessment, Quality assurance
Purpose Radiology offers an attractive opportunity for deployment of artificial intelligence (AI) solutions because much of the workflow is already digitised, and AI could be part of a potential solution to the well-publicised workforce crisis affecting the National Health Service (NHS)1. AI has the potential to revolutionise clinical workflow, reduce risk, and improve diagnostic accuracy in radiology. However, incorporating AI into routine medical care requires significant organisational transformation, encompassing not only technology adoption but also effective navigation of ethical, legal, and...
Read more Methods and materials To successfully navigate the complexity associated with the incorporation of AI in clinical radiology while maintaining patient safety, LTHT has established a multidisciplinary clinical AI board. The primary function of this board is to coordinate, supervise, assess all practical implementations of AI solutions and technologies related to imaging and ensure a comprehensive strategy to integrating AI. The board consists of clinical radiologists, radiographers, AI experts from academic and medical image analysis fields, health economists, IT and information governance personnel, and...
Read more Results The AI board has successfully overseen the evaluation of all imaging related AI initiatives providing a unified and standardised approach to AI implementation. This is vital in overcoming commonly experienced barriers with the implementation of AI, such as streamlining complex, time consuming information governance approval, upgrading highly variable IT infrastructure, increasing awareness of the transformative potential of AI, and securing funding through industry collaboration10.  During the prioritisation workshop, the AI board identified several key domains for applying AI, such as...
Read more Conclusion AI is an area of intense imaging research activity and commercial development which is not yet in routine clinical use in most settings. Establishment of an institutional AI Board with a linked PPIE group and creation of an XNAT virtual PACS ‘sandbox’ environment has helped to guide safe and effective AI implementation in radiology at LTHT. These measures have laid the groundwork for ongoing innovation, industry partnerships, and continuous improvement in patient outcomes and service delivery. The AI board will...
Read more References 1) The Royal College of Radiologists. Clinical Radiology Census Report 2022. London: The Royal College of Radiologists, 2023. Available at: https://www.rcr.ac.uk/news-policy/policy-reports-initiatives/clinical-radiology-census-reports/ (Accessed 07/01/2024)2) Stogiannos N, Malik R, Kumar A, Barnes A, Pogose M, Harvey H, McEntee MF, Malamateniou C. Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK. Br J Radiol 2023 Dec; 96(1152):20221157. doi: 10.1259/bjr.202211573) Daye D, Wiggins WF, Lungren MP, Alkasab...
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