Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation

Dimitris Visvikis; Philippe Lambin; Kim Beuschau Mauridsen; Roland Hustinx; Michael Lassmann; Christoph Rischpler; Kuangyu Shi; Jan Pruim

doi:10.1007/s00259-022-05891-w

Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation

Eur J Nucl Med Mol Imaging. 2022 Nov;49(13):4452-4463. doi: 10.1007/s00259-022-05891-w. Epub 2022 Jul 9.

Authors

Dimitris Visvikis¹, Philippe Lambin^{2

3}, Kim Beuschau Mauridsen^{4

5}, Roland Hustinx⁶, Michael Lassmann⁷, Christoph Rischpler⁸, Kuangyu Shi^{5

9}, Jan Pruim¹⁰

Affiliations

¹ LaTIM, INSERM, UMR 1101, University of Brest, Brest, France.
² The D-Lab, Department of Precision Medicine, GROW - School for Oncology, Maastricht University Medical Center (MUMC +), Maastricht, The Netherlands.
³ Department of Radiology and Nuclear Medicine, GROW - School for Oncology, Maastricht University Medical Center (MUMC +), Maastricht, The Netherlands.
⁴ Center of Functionally Integrative Neuroscience and MindLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
⁵ Department of Nuclear Medicine, University of Bern, Bern, Switzerland.
⁶ GIGA-CRC in Vivo Imaging, University of Liège, GIGA, Avenue de l'Hôpital 11, 4000, Liege, Belgium.
⁷ Klinik Und Poliklinik Für Nuklearmedizin, Universitätsklinikum Würzburg, Würzburg, Germany.
⁸ Department of Nuclear Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
⁹ Department of Informatics, Technical University of Munich, Munich, Germany.
¹⁰ Medical Imaging Center, Dept. of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. j.pruim@umcg.nl.

Abstract

Artificial intelligence (AI) will change the face of nuclear medicine and molecular imaging as it will in everyday life. In this review, we focus on the potential applications of AI in the field, both from a physical (radiomics, underlying statistics, image reconstruction and data analysis) and a clinical (neurology, cardiology, oncology) perspective. Challenges for transferability from research to clinical practice are being discussed as is the concept of explainable AI. Finally, we focus on the fields where challenges should be set out to introduce AI in the field of nuclear medicine and molecular imaging in a reliable manner.

Keywords: Artificial intelligence; Molecular imaging; Nuclear medicine.

Publication types

Review

MeSH terms

Artificial Intelligence*
Humans
Image Processing, Computer-Assisted / methods
Molecular Imaging
Nuclear Medicine*
Radionuclide Imaging