ArticleRadiation oncology (London, England)2023
Fully automated volumetric modulated arc therapy planning for locally advanced rectal cancer: feasibility and efficiency.
Article in Radiation oncology (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Objective-function-guided automated VMAT planning reduces OAR dose, low-dose exposure, and inter-planner variability in breast radiotherapy.Scientific reports · 2026Article
- Personalized intensity modulation radiation therapy auto-planning for esophageal cancer.Scientific reports · 2025Article
- Fully automated intensity-modulated radiotherapy plans for rectal cancer based on deep learning predictions of three-dimensional dose distributions.Quantitative imaging in medicine and surgery · 2025Article
- An extension to the OVH concept for knowledge-based dose volume histogram prediction in lung tumor volumetric-modulated arc therapy.Journal of applied clinical medical physics · 2025Article
- An isodose-constrained automatic treatment planning strategy using a multicriteria predicted dose rating.Medical physics · 2025Article
- Deformable registration for nasopharyngeal carcinoma using adaptive mask and weight allocation strategy based CycleFCNs model.Radiation oncology (London, England) · 2025Article
- Automated VMAT planning for short-course radiotherapy in locally advanced rectal cancer.PloS one · 2025Article
- Article
- Development and validation of an automated Tomotherapy planning method for cervical cancer.Radiation oncology (London, England) · 2024Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVolumetric modulated arc therapy (VMAT) for locally advanced rectal cancer (LARC) has emerged as a promising technique, but the planning process can be time-consuming and dependent on planner expertise. We aimed to develop a fully automated VMAT planning program for LARC and evaluate its feasibility and efficiency.
methodsA total of 26 LARC patients who received VMAT treatment and the computed tomography (CT) scans were included in this study. Clinical target volumes and organs at risk were contoured by radiation oncologists. The automatic planning program, developed within the Raystation treatment planning system, used scripting capabilities and a Python environment to automate the entire planning process. The automated VMAT plan (auto-VMAT) was created by our automated planning program with the 26 CT scans used in the manual VMAT plan (manual-VMAT) and their regions of interests. Dosimetric parameters and time efficiency were compared between the auto-VMAT and the manual-VMAT created by experienced planners. All results were analyzed using the Wilcoxon signed-rank sum test.
resultsThe auto-VMAT achieved comparable coverage of the target volume while demonstrating improved dose conformity and uniformity compared with the manual-VMAT. V30 and V40 in the small bowel were significantly lower in the auto-VMAT compared with those in the manual-VMAT (p < 0.001 and < 0.001, respectively); the mean dose of the bladder was also significantly reduced in the auto-VMAT (p < 0.001). Furthermore, auto-VMAT plans were consistently generated with less variability in quality. In terms of efficiency, the auto-VMAT markedly reduced the time required for planning and expedited plan approval, with 93% of cases approved within one day.
conclusionWe developed a fully automatic feasible VMAT plan creation program for LARC. The auto-VMAT maintained target coverage while providing organs at risk dose reduction. The developed program dramatically reduced the time to approval.
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