ESTRO 2025 - Abstract Book

S3470

Physics - Optimisation, algorithms and applications for ion beam treatment planning

ESTRO 2025

Conclusion: Improving our planning strategy in reOpt plans significantly reduces the dose in multiple OARs and increased ΔNTCP without violating the robustness clinical goal. This will be clinically implemented.

Keywords: Proton, Lung, IMPT

1806

Digital Poster Evaluating CNN-based linear energy transfer prediction uncertainty using latent space distance and ensemble models Aaron Kieslich 1,2 , Yerik Singh 1,3 , Martina Palkowitsch 1,2 , Sebastian Starke 1,4 , Fabian Hennings 1,2 , Esther G. Troost 1,2 , Mechthild Krause 1,2 , Jona Bensberg 5 , Armin Lühr 5 , Feline Heinzelmann 6,7 , Christian Bäumer 5,6 , Beate Timmermann 6,7 , Steffen Löck 1,8 1 OncoRay—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, Dresden, Germany. 2 Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology – OncoRay, Dresden, Germany. 3 Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilians-Universität München, München, Germany. 4 Helmholtz-Zentrum Dresden-Rossendorf, Department of Information Services and Computing, Dresden, Germany. 5 TU Dortmund University, Department of Physics, Dortmund, Germany. 6 West German Proton Therapy Center Essen (WPE), University Hospital Essen, Essen, Germany. 7 Clinic for Particle Therapy,