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Updated: Jun 14, 2025

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
Published on: October 6, 2023
Artificial intelligence for response prediction and personalisation in radiation oncology
Alex Zwanenburg1,2,3, Gareth Price4,5, Steffen Löck6,7
1OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Helmholtz-Zentrum Dresden-Rossendorf, Fetscherstr. 74, PF 41, 01307, Dresden, Germany. alexander.zwanenburg@nct-dresden.de.
None:
Artificial intelligence (AI) systems may personalise radiotherapy by assessing complex and multifaceted patient data and predicting tumour and normal tissue responses to radiotherapy. Here we describe three distinct generations of AI systems, namely personalised radiotherapy based on pretreatment data, response-driven radiotherapy and dynamically optimised radiotherapy. Finally, we discuss the main challenges in clinical translation of AI systems for radiotherapy personalisation.
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