Impact of deep learning on CT-based organ-at-risk delineation for flank irradiation in paediatric renal tumours: a SIOP-RTSG radiotherapy committee study.

ABSTRACT:

Background and purpose

Integrating deep learning (DL) for auto-contouring has significantly improved organ-at-risk (OAR) delineation in adult radiotherapy. However, its application in paediatric radiotherapy remains limited. This study evaluates DL-based auto-contouring of OARs, followed by manual revisions, for paediatric flank irradiation, focusing on delineation time, accuracy, and inter-observer variability (IOV).

Materials and methods

Twelve paediatric radiation oncologists from nine countries affiliated with the SIOP Renal Tumour Study Group participated in a two-day workshop. Participants were randomly divided into two groups: one performed manual delineation first, followed by DL-based revision, while the other group performed in reverse order. Eight thoracoabdominal

SUBMITTER: Ding M 

PROVIDER: S-EPMC12553021 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature