ArticlePhysics and imaging in radiation oncology2019
Development of a multicentre automated model to reduce planning variability in radiotherapy of prostate cancer.
Article in Physics and imaging in radiation oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 35 citations in OpenAlex.
- Personalising treatment plan quality review with knowledge-based planning in the TROG 15.03 trial for stereotactic ablative body radiotherapy in primary kidney cancer.Radiation oncology (London, England) · 2021Trial
- A rule-based, feedback-driven framework for fully automated prostate VMAT planning.Journal of applied clinical medical physics · 2026Article
- Version upgrades in treatment planning Systems affect clinical application of a multi-Centre knowledge-based planning model.Technical innovations & patient support in radiation oncology · 2026Article
- Prospective blinded clinical evaluation of a fully automated workflow for prostate radiotherapy.Physics and imaging in radiation oncology · 2026Article
- A comparative assessment of deep learning and knowledge-based dose prediction models for advanced radiotherapy planning of prostate cancer with focal boosting.Physics and imaging in radiation oncology · 2026Article
- Automated deep learning segmentation and planning for left-sided breast radiotherapy with minimised adaptations based on dose, TCP and NTCP criteria.Physics and imaging in radiation oncology · 2026Article
- Efficient knowledge-based planning model construction in institutions with limited cases using plan quality metrics.Radiological physics and technology · 2025Article
- Dosimetric evaluation of Ethos 2.0 high-fidelity mode for single-isocenter SRS.Journal of applied clinical medical physics · 2025Article
- Article
- A Preliminary Study on Deep Learning-Based Plan Quality Prediction in Gamma Knife Radiosurgery for Brain Metastases.Cancers · 2025Article
- Knowledge-Based RapidPlan Volumetric Modulated Arc Therapy Model in Nasopharyngeal Carcinoma.Advances in radiation oncology · 2025Article
- Validating knowledge-based volumetric modulated arc therapy plans with a multi-institution model (broad model) using a complete open-loop dataset for prostate cancer.Physical and engineering sciences in medicine · 2025Article
- Guidance on selecting and evaluating AI auto-segmentation systems in clinical radiotherapy: insights from a six-vendor analysis.Physical and engineering sciences in medicine · 2025Article
- Critical assessment of knowledge-based models for craniospinal irradiation of paediatric patients.Physics and imaging in radiation oncology · 2025Article
- Artificial Intelligence and the future of radiotherapy planning: The Australian radiation therapists prepare to be ready.Journal of medical radiation sciences · 2024Article
- Comparative Study of Eclipse and RayStation Multi-Criteria Optimization-Based Prostate Radiotherapy Treatment Planning Quality.Diagnostics (Basel, Switzerland) · 2024Article
- A geometry and dose-volume based performance monitoring of artificial intelligence models in radiotherapy treatment planning for prostate cancer.Physics and imaging in radiation oncology · 2023Article
- Evaluation of the clinical impact of the differences between planned and delivered dose in prostate cancer radiotherapy based on CT-on-rails IGRT and patient-reported outcome scores.Journal of applied clinical medical physics · 2023Article
- Using feasibility dose-volume histograms to reduce intercampus plan quality variability for head-and-neck cancer.Journal of applied clinical medical physics · 2023Article
- A comparison of in-house and shared RapidPlan models for prostate radiation therapy planning.Physical and engineering sciences in medicine · 2022Article
Corrections and comments
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Authors and funding
17 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeInter-institutional studies highlighted correlation between consistent radiotherapy quality and improved overall patient survival. In treatment planning automation has the potential to address differences due to user-experience and training, promoting standardisation. The aim of this study was to evaluate implementation and clinical effect of a multicentre collaboratively-developed automated planning model for Intensity-Modulated Radiation Therapy/Volumetric-Modulated Arc Therapy of prostate. The model was built using a variety of public institutions' clinical plans, incorporating different contouring and dose protocols, aiming at minimising their variation. METHODS AND MATERIALS: A model using 110 clinically approved and treated prostate plans provided by different radiotherapy centres was built with RapidPlan (RP), for use on intact and post-prostatectomy prostate cases. The model was validated, distributed and introduced into clinical practice in all institutions. To investigate its impact a total of 126 patients, originally manually inverse planned (OP), were replanned using RP without additional planner manual intervention. Target and organ-at-risk (OAR) metrics were statistically compared between original and automated plans.
resultsFor all centres combined and individually, RP provided plans comparable or superior to OP for all dose metrics. Statistically significant reductions with RP were found in bladder (V40Gy) and rectal (V50Gy) low doses (within 2.3% and 3.4% for combined and 4% and 10% individually). No clinically significant changes were seen for the PTV, independently of seminal vesicle inclusion.
conclusionThis project showed it is feasible to develop, share and implement RP models created with plans from different institutions treated with a variety of techniques and dose protocols, with the potential of improving treatment planning results and/or efficiency despite the original variability.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.