Artificial intelligence in diagnostic and interventional radiology: Where are we now?

Journal: Diagnostic and interventional imaging
Published Date: Dec 6, 2022

Abstract

The emergence of massively parallel yet affordable computing devices has been a game changer for research in the field of artificial intelligence (AI). In addition, dramatic investment from the web giants has fostered the development of a high-quality software stack. Going forward, the combination of faster computers with dedicated software libraries and the widespread availability of data has opened the door to more flexibility in the design of AI models. Radiomics is a process used to discover new imaging biomarkers that has multiple applications in radiology and can be used in conjunction with AI. AI can be used throughout the various processes of diagnostic imaging, including data acquisition, reconstruction, analysis and reporting. Today, the concept of "AI-augmented" radiologists is preferred to the theory of the replacement of radiologists by AI in many indications. Current evidence bolsters the assumption that AI-assisted radiologists work better and faster. Interventional radiology becomes a data-rich specialty where the entire procedure is fully recorded in a standardized DICOM format and accessible via standard picture archiving and communication systems. No other interventional specialty can bolster such readiness. In this setting, interventional radiology could lead the development of AI-powered applications in the broader interventional community. This article provides an update on the current status of radiomics and AI research, analyzes upcoming challenges and also discusses the main applications in AI in interventional radiology to help radiologists better understand and criticize articles reporting AI in medical imaging.

Authors

  • Tom Boeken
    Vascular and Oncological Interventional Radiology, University of Paris, Hopital Européen Georges Pompidou, Paris, France.
  • Jean Feydy
    Université Paris Cité, HeKA team, Inria Paris, Inserm, 75006, Paris, France.
  • Augustin Lecler
    Université Paris Cité, Faculté de Médecine, Paris 75006, France; Department of Radiology, Rothschild Foundation Hospital, Paris 75019, France.
  • Philippe Soyer
    Department of Radiology, Hôpital Cochin-APHP, 27 Rue du Faubourg Saint-Jacques, Paris 75014, France.
  • Antoine Feydy
    Department of Radiology B, Cochin Hospital, AP-HP, 75014 Paris, France; Université de Paris, 75006 Paris, France.
  • Maxime Barat
    Radiology Department, Hopital Cochin - AP-HP. Centre Université de Paris, 27 Rue du Faubourg Saint-Jacques, Paris 75014, France; Université de Paris, 85 boulevard Saint-Germain, Paris 75006, France.
  • Loïc Duron
    From the Department of Radiology, Hôpital Fondation A. de Rothschild, 25 rue Manin, 75019 Paris, France (L.D.); Faculty of Medicine, Université de Paris, Paris, France (L.D., A. Feydy); Gleamer, Paris, France (A.D., C.A., N.C., Z.Z., N.N., E.L., A.P., N.E.R.); Department of Biostatistics, CHU Rouen, Rouen, France (A.G.); Department of Radiology, Hôpital Hôtel-Dieu, Assistance Publique-Hôpitaux de Paris, Paris, France (J.L.); Department of Radiology, Hôpital Ambroise-Paré, Assistance Publique-Hôpitaux de Paris, Boulogne-Billancourt, France (A. Felter); Department of Radiology, Hôpital Raymond-Poincaré, Assistance Publique-Hôpitaux de Paris, Garches, France (A. Felter); and Department of Radiology B, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris, France (L.L., N.E.R., A. Feydy).

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