Digital Transformation and Artificial Intelligence in Radiology: Challenges and Opportunities for Clinical Practice, Research, and the Next Generation Digitale Transformation und künstliche Intelligenz in der Radiologie: Herausforderungen und Chancen für Klinik, Forschung und Nachwuchs

Hoffmann E, Bannas P, Bayerl N, Cyran CC, Dietzel M, Eisenblätter M, Hilger I, Jung C, Kiessling F, Mathy C, Müller L, Schick F, Wegner F, Bäuerle T, Adams L (2026)

Publication Type: Journal article, Review article

Publication year: 2026

Journal

Röfo: Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren Georg Thieme Verlag

Book Volume: 198

Pages Range: 852-860

Journal Issue: 7

DOI: 10.1055/a-2741-9717

Abstract

Background Radiology is at the center of the digital transformation of the healthcare system. As a highly digital field, radiology is well-suited for the early implementation and critical evaluation of innovative technologies, such as artificial intelligence (AI). This review aims to comprehensively and distinctly present the opportunities and challenges of digital transformation in radiology, focusing on clinical applications, research, and promoting young talents. Materials and Methods This narrative review is based on selective evaluation of relevant scientific literature and publications from the last 10 years. Relevant German- and Englishlanguage articles on the digital transformation of radiology were considered, particularly those addressing digital infrastructure, artificial intelligence, ethical and regulatory frameworks, and education and training. Results and Conclusion Digitalization offers significant opportunities for radiology. In addition to advancing imaging procedures and automating image analysis with AI, digitalization optimizes workflows, enables personalized diagnostics, and fosters new care models, such as teleradiology. However, there are also key challenges: Data protection issues, a lack of standardization, insufficient validation, and regulatory hurdles are hindering its widespread implementation in hospitals. To future-proof radiology, it is essential to promote young talent and incorporate digital skills in the curriculum.

Authors with CRIS profile

Nadine Bayerl Institute of Radiology Matthias Dietzel Institute of Radiology Claudius Mathy Institute of Radiology

Involved external institutions

Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen DE Germany (DE) Universitätsmedizin der Johannes Gutenberg-Universität Mainz DE Germany (DE) Eberhard Karls Universität Tübingen DE Germany (DE) Technische Universität München (TUM) DE Germany (DE) Universität Münster (ehem. Westfälische Wilhelms-Universität (WWU)) DE Germany (DE) Universität Bielefeld DE Germany (DE) Universitätsklinikum Schleswig-Holstein (UKSH) DE Germany (DE) Universitätsklinikum Hamburg-Eppendorf (UKE) DE Germany (DE) Klinikum der Universität München (LMU Klinikum) DE Germany (DE) Universitätsklinikum Jena DE Germany (DE) Klinikum Nordfriesland DE Germany (DE)

How to cite

APA:

Hoffmann, E., Bannas, P., Bayerl, N., Cyran, C.C., Dietzel, M., Eisenblätter, M.,... Adams, L. (2026). Digital Transformation and Artificial Intelligence in Radiology: Challenges and Opportunities for Clinical Practice, Research, and the Next Generation Digitale Transformation und künstliche Intelligenz in der Radiologie: Herausforderungen und Chancen für Klinik, Forschung und Nachwuchs. Röfo: Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, 198(7), 852-860. https://doi.org/10.1055/a-2741-9717

MLA:

Hoffmann, Emily, et al. "Digital Transformation and Artificial Intelligence in Radiology: Challenges and Opportunities for Clinical Practice, Research, and the Next Generation Digitale Transformation und künstliche Intelligenz in der Radiologie: Herausforderungen und Chancen für Klinik, Forschung und Nachwuchs." Röfo: Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren 198.7 (2026): 852-860.

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