S1973
Physics - Dose prediction/calculation, optimisation and applications for photon and electron planning
ESTRO 2026
efficiency. These findings demonstrate the feasibility and clinical potential of fully automated, artificial intelligence–driven H&N radiotherapy planning that combines high efficiency, dosimetric robustness, and generalizability.
References: [1] Momin S, Fu Y, Lei Y, et al. Knowledge-based radiation treatment planning: A data-driven method survey. J Appl Clin Med Phys. 2021;22(8):16-44.[2] Babier A, Mahmood R, Zhang B, et al. OpenKBP-Opt: international reproducible evaluation of 76 knowledge-based planning pipelines. Phys Med Biol. 2022;67(18):185012.[3] Prunaretty J, Ungun B, Vauclin R, et al. Fully automated planning for prostate and pelvic radiotherapy: quantitative evaluation. Cancers. 2024;16(2):3735.[4] Podell D, English Z, Lacey K, et al. SDXL: latent diffusion models for high-resolution image synthesis. In: Proc. ICLR 2024; 2024:1862-74. Keywords: Automated-planning, Artificial Intelligence, VMAT Digital Poster 4016 Assessment of Ethos-based Stereotactic Prostate Treatment Planning: Clinical Feasibility and Dosimetric Result András Herein 1 , Domonkos Szegedi 1,2 , Ádám Gáldi 1,3 , István Szabolcs Tódor 1 , Tamás Pócza 1 , Csilla
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