ESTRO 2025 - Abstract Book

S4327

RTT - Treatment planning, OAR and target definitions

ESTRO 2025

Conclusion: This study provided important information towards uniformization and improvement of the plan quality for RT of WB with nodal involvement in our institution. There were substantial deviations in the DV-values for the left lung. The values of these metrics are strongly correlated to the acceptance level of the plan and actions aiming to minimize their variability are required.

Keywords: Plan quality, breast cancer, radiotherapy

792

Digital Poster an evaluation of the accuracy of deep learning-based auto segmentation for organs at risk delineation in the radiotherapy of left breast cancer Christy Poon Radiotherapy, HKSH, Hong Kong, Hong Kong Purpose/Objective: The high incidence of breast cancer in Hong Kong is one main factor that accounts for an increasing workload in radiotherapy departments in Hong Kong. Contouring, a critical step in planning radiotherapy, contributes to the increased workload. The aim of this study is to evaluate the accuracy and feasibility of the auto segmentation model developed for the treatment planning in left breast cancer patients.