ESTRO 2025 - Abstract Book

S3103

Physics - Inter-fraction motion management and offline adaptive radiotherapy

ESTRO 2025

Conclusion: The deep-learning network effectively generated high-quality sCTs with CT numbers, proton range, and dose characteristics comparable to fan-beam CT. Its robustness against intra-patient variations makes it a feasible tool for adaptive proton therapy.

Keywords: Synthetic CT generation, Adaptive proton therapy

References: [1] Vestergaard CD, Elstrøm UV, Muren LP, Ren J, Nørrevang O, Jensen K, Taasti VT. Proton dose calculation on cone beam computed tomography using unsupervised 3D deep learning networks. Phys Imaging Radiat Oncol 2024;32:100658. https://doi.org/10.1016/j.phro.2024.100658.

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Digital Poster Reducing fractions for abdominal lymph node oligometastases: the need for online adaptive radiotherapy to provide personalized adaptive fractionation Erik van Lieshout, Lucy A. van Werkhoven, Mischa S. Hoogeman, Remi A. Nout, Maaike T. W. Milder, Joost J. M. E. Nuyttens Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, Netherlands