ArticlePhysics and imaging in radiation oncology2024
Autodelineation methods in a simulated fully automated proton therapy workflow for esophageal cancer.
Article in Physics and imaging in radiation oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Reduction of organ of interest dose in proton therapy for oesophageal cancer through optimized setup robustness settings and online adaptation.Physics and imaging in radiation oncology · 2026Article
- Imaging, automation and workflow challenges for online adaptive proton therapy.Physics and imaging in radiation oncology · 2025Article
- Dynamic proton arc treatment planning study for oesophageal cancer.Physics and imaging in radiation oncology · 2025Article
- Potential of automated online adaptive proton therapy to reduce margins for oesophageal cancer.Physics and imaging in radiation oncology · 2025Article
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Authors and funding
7 authors.
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Abstract
Background and purpose: Proton Online Adaptive RadioTherapy (ProtOnART) harnesses the dosimetric advantage of protons and immediately acts upon anatomical changes. Here, we simulate the clinical application of delineation and planning within a ProtOnART-workflow for esophageal cancer. We aim to identify the most appropriate technique for autodelineation and evaluate full automation by replanning on autodelineated contours. Materials and methods: We evaluated 15 patients who started treatment between 11-2022 and 01-2024, undergoing baseline and three repeat computed tomography (CT) scans in treatment position. Quantitative and qualitative evaluations compared different autodelineation methods. For Organs-at-risk (OAR) deep learning segmentation (DLS), rigid and deformable propagation from baseline to repeat CT-scans were considered. For the clinical target volume (CTV), rigid and three deformable propagation methods (default, heart as controlling structure and with focus region) were evaluated. Adaptive treatment plans with 7 mm (ATP Results: Deformation was preferred for autodelineation of heart, lungs and spinal cord. DLS was preferred for all other OARs. For CTV, deformation with focus region was the preferred method although the difference with other deformation methods was small. Nominal ATPs passed evaluation goals for 87 % of ATP Conclusion: Autodelineation aids a ProtOnART-workflow for esophageal cancer. Currently available tools regularly require manual annotations to generate clinically acceptable ATPs.
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