ArticleJournal of applied clinical medical physics2025
Replacing manual planning with automatic iterative planning for locally advanced rectal cancer VMAT treatment.
Article in Journal of applied clinical medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Replacing manual planning with automatic iterative planning for locally advanced rectal cancer VMAT treatment.Journal of applied clinical medical physics · 2025Article
- Automated VMAT planning for short-course radiotherapy in locally advanced rectal cancer.PloS one · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
purposeTo develop and implement a fully automatic iterative planning (AIP) system in the clinical practice, generating volumetric-modulated arc therapy plans combined with simultaneous integrated boost technique VMAT (SIB-VMAT) for locally advanced rectal cancer (LARC) patients.
methodThe designed AIP system aimed to automate the entire planning process through a web-based service, including auxiliary structure generation, plan creation, field configuration, plan optimization, dose calculation, and plan assessment. The system was implemented based on the Eclipse scripting application programming interface and an efficient iterative optimization algorithm was proposed to reduce the required iterations in the optimization process. To verify the performance of the implemented AIP system, we retrospectively selected a total of 106 patients and performed dosimetric comparisons between the automatic plans (APs) and the manual plans (MPs), in terms of dose-volume histogram (DVH) metrics, homogeneity index (HI), and conformity index (CI) for different volumes of interest.
resultThe AIP system has successfully created 106 APs within clinically acceptable timeframes. The average planning time per case was 36.8 ± 6.5 min, with an average iteration number of 6.8 (±1.1) in plan optimization. Compared to MPs, APs exhibited better performance in the planning target volume conformity and hotspot control (
conclusionAn AIP system has been implemented and integrated into the clinical treatment planning workflow. The AIP-generated SIB-VMAT plans for LARC have demonstrated superior plan quality and consistency compared with the manual counterparts. In the meantime, the planning time has been reduced by the AIP approach. Based on the reported results, the implemented AIP framework has been proven to improve plan quality and planning efficiency, liberating planners from the laborious parameter-tuning in the optimization phase.
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Registered trials
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