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CIRSE Position Paper on Artificial Intelligence in Interventional Radiology

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Abstract

Artificial intelligence (AI) has made tremendous advances in recent years and will presumably have a major impact in health care. These advancements are expected to affect different aspects of clinical medicine and lead to improvement of delivered care but also optimization of available resources. As a modern specialty that extensively relies on imaging, interventional radiology (IR) is primed to be on the forefront of this development. This is especially relevant since IR is a highly advanced specialty that heavily relies on technology and thus is naturally susceptible to disruption by new technological developments. Disruption always means opportunity and interventionalists must therefore understand AI and be a central part of decision-making when such systems are developed, trained, and implemented. Furthermore, interventional radiologist must not only embrace but lead the change that AI technology will allow. The CIRSE position paper discusses the status quo as well as current developments and challenges.

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Funding

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Authors and Affiliations

  1. Department of Radiology and Nuclear Medicine, Institut für Radiologie und Nuklearmedizin, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland

    Arash Najafi

  2. Department of Interventional Radiology, University Hospital of Strasbourg, Strasbourg, France

    Roberto Luigi Cazzato

  3. Department of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany

    Bernhard C. Meyer

  4. Center of Radiology, Minimally Invasive Therapies and Nuclear Medicine, SLK-Kliniken GmbH, Academic Hospital of Ruprecht-Karls-University, Heidelberg, Germany

    Philippe L. Pereira

  5. APL Prof. Faculty of Eberhards-Karls-University, Tübingen, Germany

    Philippe L. Pereira

  6. Faculty of Danube Private University, Krems, Austria

    Philippe L. Pereira

  7. Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain

    Angel Alberich

  8. Medical Informatics and Radiology Department, Hospital Clinic de Barcelona, Barcelona, Spain

    Antonio López

  9. Université Paris Cité, CRI, Paris, France

    Maxime Ronot

  10. Service de Radiologie, Hôpital Beaujon APHP Nord, Clichy, France

    Maxime Ronot

  11. Department of Radiology, NYU Grossman School of Medicine, New York, USA

    Jan Fritz

  12. Antoni van Leeuwenhoek-Netherlands Cancer Institute, Amsterdam, The Netherlands

    Monique Maas, Sean Benson & Fernando Gomez Munoz

  13. Zentrum für Radiologie, HELIOS Universitätsklinikum Wuppertal, Wuppertal, Germany

    Patrick Haage

  14. Hospital Universitari i Politecnic La Fe, Valencia, Spain

    Fernando Gomez Munoz

Authors
  1. Arash Najafi
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  2. Roberto Luigi Cazzato
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  3. Bernhard C. Meyer
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  4. Philippe L. Pereira
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  5. Angel Alberich
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  6. Antonio López
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  7. Maxime Ronot
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  8. Jan Fritz
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  9. Monique Maas
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  10. Sean Benson
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  11. Patrick Haage
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  12. Fernando Gomez Munoz
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Corresponding author

Correspondence to Arash Najafi.

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Najafi, A., Cazzato, R.L., Meyer, B.C. et al. CIRSE Position Paper on Artificial Intelligence in Interventional Radiology. Cardiovasc Intervent Radiol 46, 1303–1307 (2023). https://doi.org/10.1007/s00270-023-03521-y

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  • DOI: https://doi.org/10.1007/s00270-023-03521-y

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