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Nuklearmedizin 2023; 62(06): 354-360
DOI: 10.1055/a-2191-3271
Review

Clinical Applications of Radiomics in Nuclear Medicine

Klinische Anwendungen von Radiomics in der Nuklearmedizin
Philipp Lohmann
1   Institute of Neuroscience and Medicine (INM-3/-4), Forschungszentrum Jülich GmbH, Jülich, Germany (Ringgold ID: RIN28334)
,
Ralph Alexander Bundschuh
2   Faculty of Medicine, Department of Nuclear Medicine, University of Augsburg, Augsburg, Germany (Ringgold ID: RIN26522)
,
Isabelle Miederer
3   Department of Nuclear Medicine, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany (Ringgold ID: RIN39068)
,
Felix M. Mottaghy
4   Department of Nuclear Medicine, University Hospital RWTH Aachen, Aachen, Germany
5   Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany
6   Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
,
Karl Josef Langen
1   Institute of Neuroscience and Medicine (INM-3/-4), Forschungszentrum Jülich GmbH, Jülich, Germany (Ringgold ID: RIN28334)
4   Department of Nuclear Medicine, University Hospital RWTH Aachen, Aachen, Germany
6   Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
,
Norbert Galldiks
7   Faculty of Medicine and University Hospital Cologne, Department of Neurology, University of Cologne, Cologne, Germany (Ringgold ID: RIN14309)
1   Institute of Neuroscience and Medicine (INM-3/-4), Forschungszentrum Jülich GmbH, Jülich, Germany (Ringgold ID: RIN28334)
6   Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
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Abstract

Radiomics is an emerging field of artificial intelligence that focuses on the extraction and analysis of quantitative features such as intensity, shape, texture and spatial relationships from medical images. These features, often imperceptible to the human eye, can reveal complex patterns and biological insights. They can also be combined with clinical data to create predictive models using machine learning to improve disease characterization in nuclear medicine. This review article examines the current state of radiomics in nuclear medicine and shows its potential to improve patient care. Selected clinical applications for diseases such as cancer, neurodegenerative diseases, cardiovascular problems and thyroid diseases are examined. The article concludes with a brief classification in terms of future perspectives and strategies for linking research findings to clinical practice.

Keywords

PET - SPECT - Artificial Intelligence (AI) - Machine Learning - Cancer - Neurodegenerative Disease - Cardiovascular Disease - Thyroid Diseases


Publication History

Received: 21 September 2023

Accepted: 12 October 2023

Article published online:
07 November 2023

© 2023. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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