A multi-centre evaluation of deep learning based radiotherapy planning for left-sided node-negative breast cancer.

ABSTRACT:

Background and purpose

Deep learning based planning (DLP) has the potential to improve consistency and efficiency in radiotherapy treatment planning. However, its clinical applicability remains limited, partly due to the need to translate a predicted dose into a deliverable dose. This study evaluated the generalisability of an institution specific DLP solution across multiple institutions by assessing its performance and developing a standardised translation parameter set.

Materials and methods

Four institutions provided clinical treatment plans of 15 patients with left-sided node-negative breast cancer. Treatment plans delivering 40.05 Gy were generated using a deep learning prediction model trained on data from one institution. External validation was performed using natio

SUBMITTER: Besouw M 

PROVIDER: S-EPMC12492285 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature