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

Maxime Barat; Martin Gaillard; Anne-Ségolène Cottereau; Elliot K Fishman; Guillaume Assié; Anne Jouinot; Christine Hoeffel; Philippe Soyer; Anthony Dohan

doi:10.1016/j.diii.2022.09.003

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

Diagn Interv Imaging. 2023 Jan;104(1):37-42. doi: 10.1016/j.diii.2022.09.003. Epub 2022 Sep 24.

Authors

Maxime Barat¹, Martin Gaillard², Anne-Ségolène Cottereau³, Elliot K Fishman⁴, Guillaume Assié⁵, Anne Jouinot⁵, Christine Hoeffel⁶, Philippe Soyer⁷, Anthony Dohan⁷

Affiliations

¹ Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris 75014, France; Université Paris Cité, Faculté de Médecine, Paris 75006, France. Electronic address: maxime.barat@aphp.fr.
² Université Paris Cité, Faculté de Médecine, Paris 75006, France; Department of Digestive, Hepatobiliary and Pancreatic Surgery, Hôpital Cochin, AP-HP, Paris 75014, France.
³ Université Paris Cité, Faculté de Médecine, Paris 75006, France; Department of Nuclear Medicine, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris 75014, France.
⁴ The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
⁵ 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.
⁶ Department of Radiology, Robert Debré Hospital, Reims 51092, France.
⁷ Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris 75014, France; Université Paris Cité, Faculté de Médecine, Paris 75006, France.

PMID: 36163169
DOI: 10.1016/j.diii.2022.09.003

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.

Keywords: Adrenal glands; Artificial intelligence; Deep learning; Machine learning.

Publication types

Review

MeSH terms

Algorithms
Artificial Intelligence*
Deep Learning*
Diagnostic Imaging
Humans
Machine Learning