Impact of deep learning on CT-based organ-at-risk delineation for flank irradiation in paediatric renal tumours: a SIOP-RTSG radiotherapy committee study
Year: 2025
Type: article
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 OARs were delineated on non-contrast CTs of renal tumour patients (ages 1-6). DL-based contours were generated using a model for paediatric abdominal cases. Delineation time was recorded, accuracy and IOV were assessed using the Dice similarity coefficient (DSC), 95th percentile Hausdorff distance, mean surface distance against a STAPLE consensus (threshold = 0.95), and an expert reference. Results: In total, 122 manual delineations and 254 DL-based revisions were collected. DL-based auto-contouring reduced delineation time by 59 %, from 25.5 to 10.2 min. The mean DSC of all eight OARs improved from 0.91 to 0.97 using STAPLE reference and from 0.89 to 0.93 using expert reference. The pancreas exhibited the largest gain, with mean DSC increases ranging from 0.18 to 0.25. Delineation accuracy was significantly improved for seven OARs (p < 0.05), while IOV significantly decreased for the pancreas and heart in both references (p < 0.05). Conclusion: Manually revising DL-based auto-contouring reduces delineation time, enhances accuracy, and reduces inter-observer variability in paediatric CT-based OAR delineation.
Institutions: University Medical Center Utrecht, Princess Máxima Center, Utrecht University, University Hospital Heidelberg, Université Paris Sciences et Lettres, Institut Curie, Fondazione IRCCS Istituto Nazionale dei Tumori, Oslo University Hospital, Universitair Ziekenhuis Leuven, Spitalului Clinic de Urgență pentru Copii Maria Sklodowska Curie, Ghent University Hospital, Saarland University, Wilhelmina Children's Hospital
Language: English
Subfield: Radiation
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,430
Award: G2963836419
OpenAlex ID: W4415648195
