Efficient proton arc optimization and delivery through energy layer pre-selection and post-filtering Article Swipe
S. Wuyckens
,
V. Wase
,
O. Marthin
,
Johan Sundström
,
Guillaume Janssens
,
E. Borderias-Villarroel
,
Kevin Souris
,
Edmond Sterpin
,
Erik Engwall
,
J. A. Lee
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2309.08507
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2309.08507
Proton arc therapy (PAT) has emerged as a promising approach for improving dose distribution, but also enabling simpler and faster treatment delivery in comparison to conventional proton treatments. However, the delivery speed achievable in proton arc relies on dedicated algorithms, which currently do not generate plans with a clear speed-up and sometimes even result in increased delivery time. This study aims to address the challenge of minimizing delivery time through a hybrid method combining a fast geometry-based energy layer (EL) pre-selection with a dose-based EL filtering. Three methods of EL filtering were developed; The unrestricted method filters the lowest weighted EL while the SU gap filtering removes the EL around a new SU to minimize the gantry rotation braking. The SU filtering removes the lowest weighted group of EL that includes a SU. These filters were combined with the RayStation dynamic proton arc optimization framework (ELSA). Four bilateral oropharyngeal and four lung cancer patients' data were used for evaluation. Objective function values, target coverage robustness, organ-at-risk doses and NTCP evaluations, as well as comparisons to IMPT plans, were used to assess plan quality. The SU gap filtering algorithm performed best in five out of the eight cases, maintaining plan quality within tolerance while reducing beam delivery time, in particular for the oropharyngeal cohort. It achieved up to approximately 22% and 15% reduction in delivery time for oropharyngeal and lung treatment sites, respectively. The unrestricted filtering algorithm followed closely. In contrast, the SU filtering showed limited improvement, suppressing one or two SU without substantial delivery time shortening. Robust target coverage was kept within 1% of variation compared to the PAT baseline plan while organs-at-risk doses slightly decreased or kept about the same for all patients.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2309.08507
- https://arxiv.org/pdf/2309.08507
- OA Status
- green
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386839817
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386839817Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2309.08507Digital Object Identifier
- Title
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Efficient proton arc optimization and delivery through energy layer pre-selection and post-filteringWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-09-15Full publication date if available
- Authors
-
S. Wuyckens, V. Wase, O. Marthin, Johan Sundström, Guillaume Janssens, E. Borderias-Villarroel, Kevin Souris, Edmond Sterpin, Erik Engwall, J. A. LeeList of authors in order
- Landing page
-
https://arxiv.org/abs/2309.08507Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2309.08507Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2309.08507Direct OA link when available
- Concepts
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Proton therapy, Robustness (evolution), Dosimetry, Computer science, Proton, Mathematics, Nuclear medicine, Medicine, Physics, Chemistry, Nuclear physics, Gene, BiochemistryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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24Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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