ArticleRadiation oncology (London, England)2022
Knowledge-based DVH estimation and optimization for breast VMAT plans with and without avoidance sectors.
Article in Radiation oncology (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 18 citations in OpenAlex.
- Evaluation of 3D-CRT vs. VMAT for radiotherapy of whole breast with simultaneous integrated boost.Acta oncologica (Stockholm, Sweden) · 2026Article
- Explicit modeling of beam geometry improves three-dimensional dose prediction for esophageal cancer radiotherapy under heterogeneous beam configurations.Radiation oncology (London, England) · 2026Article
- Implementation and Dosimetric Evaluation of a Knowledge-Based IMRT Model for Left-Sided Breast Radiotherapy with DIBH.Journal of applied clinical medical physics · 2026Article
- Dosimetric comparison of IMRT and VMAT with deep inspiration breath hold or free breathing for right-sided whole breast irradiation.BMC cancer · 2026Article
- Integrating static angle ports and dynamic collimator rotation in volumetric modulated arc therapy for hypofractionated whole breast irradiation in Chinese females: a single-centre dosimetric study.Radiation oncology (London, England) · 2026Article
- Development and Evaluation of Knowledge-Based Treatment Plans for Chest Wall and Regional Lymph Node Irradiation.Cureus · 2026Article
- Systematic implementation of rapidplan for prostate cancer: toward a unified knowledge-based planning model.Scientific reports · 2025Article
- Improvement of plan quality in whole-breast radiation following BCS using feasibility DVH by less-experienced planners.Physical and engineering sciences in medicine · 2025Article
- Quality and mechanical efficiency of automated knowledge-based planning for volumetric-modulated arc therapy in head and neck cancer.Journal of applied clinical medical physics · 2025Article
- Effect of physical parameter differences on the performance of a knowledge-based partial arc VMAT RapidPlan model for left breast cancer.Frontiers in oncology · 2025Article
- Effectiveness of multi-criteria optimization in combination with knowledge-based modeling in radiotherapy of left-sided breast including regional nodes.Physics and imaging in radiation oncology · 2024Article
- Optimising craniospinal irradiation for medulloblastoma: a dosimetric comparison of two VMAT planning methods.Ecancermedicalscience · 2024Article
- Knowledge-based versus deep learning based treatment planning for breast radiotherapy.Physics and imaging in radiation oncology · 2024Article
- Study on the transferability of the knowledge-based VMAT model to predict IMRT plans in prostate cancer radiotherapy.European journal of medical research · 2023Article
- Effectiveness of RapidPlan in Combination with Multicriteria Optimization for Cervix Radiotherapy Planning.Journal of medical physicsArticle
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo analyze RapidPlan knowledge-based models for DVH estimation of organs at risk from breast cancer VMAT plans presenting arc sectors en-face to the breast with zero dose rate, feature imposed during the optimization phase (avoidance sectors AS).
methodsCT datasets of twenty left breast patients in deep-inspiration breath-hold were selected. Two VMAT plans, PartArc and AvoidArc, were manually generated with double arcs from ~ 300 to ~ 160°, with the second having an AS en-face to the breast to avoid contralateral breast and lung direct irradiation. Two RapidPlan models were generated from the two plan sets. The two models were evaluated in a closed loop to assess the model performance on plans where the AS were selected or not in the optimization.
resultsThe PartArc plans model estimated DVHs comparable with the original plans. The AvoidArc plans model estimated a DVH pattern with two steps for the contralateral structures when the plan does not contain the AS selected in the optimization phase. This feature produced mean doses of the contralateral breast, averaged over all patients, of 0.4 ± 0.1 Gy, 0.6 ± 0.2 Gy, and 1.1 ± 0.2 Gy for the AvoidArc plan, AvoidArc model estimation, RapidPlan generated plan, respectively. The same figures for the contralateral lung were 0.3 ± 0.1 Gy, 1.6 ± 0.6 Gy, and 1.2 ± 0.5 Gy. The reason was found in the possible incorrect information extracted from the model training plans due to the lack of knowledge about the AS. Conversely, in the case of plans with AS set in the optimization generated with the same AvoidArc model, the estimated and resulting DVHs were comparable. Whenever the AvoidArc model was used to generate DVH estimation for a plan with AS, while the optimization was made on the plan without the AS, the optimizer evidentiated the limitation of a minimum dose rate of 0.2 MU/°, resulting in an increased dose to the contralateral structures respect to the estimation.
conclusionsThe RapidPlan models for breast planning with VMAT can properly estimate organ at risk DVH. Attention has to be paid to the plan selection and usage for model training in the presence of avoidance sectors.
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