Artificial intelligence in adrenal imaging: A critical review of current applications.

Journal: Diagnostic and interventional imaging
Published Date: Sep 24, 2022

Abstract

In the elective field of adrenal imaging, artificial intelligence (AI) can be used for adrenal lesion detection, characterization, hypersecreting syndrome management and patient follow-up. Although a perfect AI tool that includes all required steps from detection to analysis does not exist yet, multiple AI algorithms have been developed and tested with encouraging results. However, AI in this setting is still at an early stage. In this regard, most published studies about AI in adrenal gland imaging report preliminary results that do not have yet daily applications in clinical practice. In this review, recent developments and current results of AI in the field of adrenal imaging are presented. Limitations and future perspectives of AI are discussed.

Authors

  • 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.
  • Martin Gaillard
    Université Paris Cité, Faculté de Médecine, Paris 75006, France; Department of Digestive, Hepatobiliary and Pancreatic Surgery, Hôpital Cochin, AP-HP, Paris 75014, France.
  • Anne-Ségolène Cottereau
    Department of Nuclear Medicine, Cochin Hospital, AP-HP, Paris, France.
  • Elliot K Fishman
    The Russell H. Morgan Department of Radiology and Radiologic Science, Johns Hopkins School of Medicine, Baltimore, Maryland. Electronic address: efishman@jhmi.edu.
  • Guillaume Assié
    Université Paris Cité, Faculté de Médecine, Paris 75006, France; Department of Endocrinology, Center for Rare Adrenal Diseases, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris 75014, France.
  • Anne Jouinot
    Université Paris Cité, Faculté de Médecine, Paris 75006, France; Department of Endocrinology, Center for Rare Adrenal Diseases, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris 75014, France.
  • Christine Hoeffel
    Department of Radiology, Robert Debré Hospital, 51092, Reims, France.
  • Philippe Soyer
    Department of Radiology, Hôpital Cochin-APHP, 27 Rue du Faubourg Saint-Jacques, Paris 75014, France.
  • Anthony Dohan
    Department of Diagnostic Radiology, McGill University, Montreal, QC, Canada.

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