ArticlePhysics and imaging in radiation oncology2022
Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer.
Article in Physics and imaging in radiation oncology, 2022. 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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4 citing papers in PubMed.
- Optimizing Treatment Precision: Role of Adaptive Radiotherapy in Modern Anal Cancer Management.Cancers · 2025Review
- Evaluating the effect of higher Monte Carlo statistical uncertainties on accumulated doses after daily adaptive fractionated radiotherapy in prostate cancer.Physics and imaging in radiation oncology · 2024Article
- Full daily re-optimization improves plan quality during online adaptive radiotherapy.Physics and imaging in radiation oncology · 2024Article
- Towards real-time radiotherapy planning: The role of autonomous treatment strategies.Physics and imaging in radiation oncology · 2022Article
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12 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background/purpose: In daily plan adaptation the radiotherapy treatment plan is adjusted just prior to delivery. A simple approach is taking the planning objectives of the reference plan and directly applying these in re-optimization. Here we present a tested method to verify whether daily adaptation without tweaking of the objectives can maintain the plan quality throughout treatment. Materials/methods: For fifteen rectal cancer patients, automated treatment planning was used to generate plans mimicking manual reference plans on the planning scans. For 74 fraction scans (4-5 per patient) an automated plan and a daily adapted plan were generated, where the latter re-optimizes the reference plan objectives without any tweaking. To evaluate the robustness of the daily adaptation, the adapted plans were compared to the autoplanning plans. Results: Median differences between the autoplanning plans on the planning scans and the reference plans were between -1 and 0.2 Gy. The largest interquartile range (1 Gy) was seen for the Lumbar Skin D2%. For the daily scans the PTV D2% and D98% differences between autoplanning and adapted plans were within Conclusion: Automated treatment planning can be used to benchmark daily adaptation techniques. The investigated adaptation workflow can robustly perform high quality adaptations without daily adjusting of the patient-specific planning objectives for rectal cancer radiotherapy.
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