ESTRO 2025 - Abstract Book

S2219

Interdisciplinary – Global health

ESTRO 2025

Conclusion: We report the patient and staff travel and its estimated CO 2 e emissions from 13 centres worldwide. No significant differences were found between centres located in cities with more or less than 1 million inhabitants. Patient travel was a greater contributor to greenhouse gas emissions than staff travel. Opportunities to reduce these emissions, such as increased hypofractionation, should be maximised.

Keywords: Patient travel, staff travel, carbon footprint

References: 1. Chuter, R. et al. Towards estimating the carbon footprint of external beam radiotherapy. Physica Medica 112 (2023). 2. Ali, D. & Piffoux, M. Methodological guide for assessing the carbon footprint of external beam radiotherapy: A single-center study with quantified mitigation strategies. Clin Transl Radiat Oncol 46 (2024). 3. Lichter, K. E. et al. Quantification of the environmental impact of radiotherapy and associated secondary human health effects: a multi-institutional retrospective analysis and simulation. Lancet Oncol 25 (2024). 4. Department for Energy Security and Net Zero. Greenhouse gas reporting: conversion factors 2024 - GOV.UK. https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2024 (2024)

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Digital Poster Assessing the Global Transferability of Knowledge-Based Planning Models for Breast Radiotherapy: A Case Study in Nepal Marco Esposito 1,2 , Rita Buono 3 , Surendra Bahadur Chand 4 , Shivaji Poudel 4 , Roberta Castriconi 3 , Alessia Tudda 3 , Lorenzo Placidi 5 , Elisabetta Cagni 6 , Valeria Landoni 7 , Aldo Mazzilli 8 , Eugenia Moretti 9 , Giulia Rambaldi Guidasci 10 , Claudio Fiorino 3 1 Medical Physics, Abdus Salam International Center for Theoretical Physics, Trieste, Italy. 2 Medical Physics, Azienda Sanitaria USL Toscana Centro, Firenze, Italy. 3 Medical Physics Dept, IRCCS San Raffaele Scientific Institute, Milano, Italy. 4 Radiation Oncology Department, B.P. Koirala Memorial Cancer Hospital, Bharatpur, Nepal. 5 Medical Physics, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Roma, Italy. 6 Medical Physics Unit, Department of Advanced Technology, Azienda USL-IRCCS di Reggio Emilia of Advanced Technology, Reggio Emilia, Italy. 7 Medical Physics Unit, Istituto Nazionale dei Tumori Regina Elena, Roma, Italy. 8 Medical Physics Dept, University Hospital of Parma AOUP, Parma, Italy. 9 SOC Fisica Sanitaria, ASU FC Udine, Udine, Italy. 10 UOC di Radioterapia Oncologica, Ospedale Isola Tiberina, Roma, Italy Purpose/Objective: Knowledge-based planning (KBP) models predict radiotherapy doses based on prior dose-geometry relationships and have the potential to improve the quality and efficiency of radiotherapy planning. Moreover, KBP models enable knowledge transfer, supporting the standardization of radiotherapy practices across multiple centers. However, applying these models to new contexts without local testing may lead to suboptimal outcomes. This study evaluates the transferability of KBP models developed from a multicenter dataset in Italy to a low- and middle income country setting in a Nepalese hospital. Material/Methods: The Mikapoco collaboration developed benchmark KBP models for left- and right-sided postoperative breast radiotherapy using tangential fields (TF), based on data from seven Italian centers. These models, created with RapidPlan (Varian Medical Systems) and based on a principal component analysis (PCA) dose prediction algorithm, were transferred to B.P. Koirala Memorial Cancer Hospital in Nepal and tested on a local sample of 20 patients (10 left breast, 10 right breast). Principal component 1 (PC1) for organs at risk (OAR)—the heart and ipsilateral lung— was calculated and compared to the Italian benchmark. Model transferability was deemed optimal if PC1 values fell