ESTRO 2025 - Abstract Book

S4346

RTT - Treatment planning, OAR and target definitions

ESTRO 2025

distribution).The greatest scoring discrepancy among radiation oncologists was seen for patient 2, where MDs 2 and 3 agreed on the hybrid as the best plan, while MD 1 preferred 3D-CRT due to favorable anatomical features.

Conclusion: IMRT and hybrid strategies were the primary selections by the MDs. Expanding the patient cohort is necessary to further elucidate correlations between anatomical parameters and treatment choice. Preliminary observations suggest consistent anatomical characteristics among cases where the hybrid strategy was preferred.

Keywords: planning, parameters, breast

References: 1_Bradley, Julie A. and Mendenhall, Nancy P. , Novel Radiotherapy Techniques for Breast Cancer, Annual Review of Medicine Vol. 69:277-288 2_START Trialists' Group, Bentzen SM et al.The UK Standardisation of Breast Radiotherapy (START) Trial B of radiotherapy hypofractionation for treatment of early breast cancer: a randomised trial. Lancet. 2008 Mar 29;371(9618):1098-107. 3_ Guan H et al. Morphological factors and cardiac doses in whole breast radiation for left-sided breast cancer. Asian Pac J Cancer Prev. 2015;16(7):2889-94. 4_ Fadavi P et al. The Relationship between Lung and Heart Two-Dimensional Parameters and Three-Dimensional Dose-Volume Data in Adjuvant Radiotherapy for Breast Cancer. Med J Islam Repub Iran. 2022 Mar 2;36:16.

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Digital Poster Internal validation of two AI-based autocontouring softwares

João Dias, Joep Stroom, Nuno Pimentel, Adriana Martins, Maria Cardoso, Ana Soares, Dalila Mateus, Beatriz Nunes, Vasco Louro, Ana Vasconcelos, Oriol Pares, Justyna Kociolek, Ana Duarte, Inês Antunes, Miguel Simas, Javier Hernandez, Carlo Greco Radiotherapy, Fundação Champalimaud, Lisboa, Portugal Purpose/Objective: The delimitation of organs at risk (OARs) is one of the most important stages in the radiotherapy treatment process and one of the most time-consuming. Artificial intelligence (AI) has played an important role in new software that automatically contours the OARs allowing to reduce the time spent by radiation oncologists (RO), maintain contour delineation quality, avoid errors, and minimize variability between them. Two AI-based software programs were