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Prediction of the minimum spacer thickness required for definitive radiotherapy with carbon ions and photons for pelvic tumors: an in silico planning study using virtual spacers
We aimed to predict the minimum distance between a tumor and the gastrointestinal (GI) tract that can satisfy the dose constraint by creating simulation plans with carbon-ion (C-ion) radiotherapy (RT) and photon RT for each case assuming insertion of virtual spacers of various thicknesses. We enroll...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8273800/ https://www.ncbi.nlm.nih.gov/pubmed/34059894 http://dx.doi.org/10.1093/jrr/rrab047 |
Sumario: | We aimed to predict the minimum distance between a tumor and the gastrointestinal (GI) tract that can satisfy the dose constraint by creating simulation plans with carbon-ion (C-ion) radiotherapy (RT) and photon RT for each case assuming insertion of virtual spacers of various thicknesses. We enrolled 55 patients with a pelvic tumor adjacent to the GI tract. Virtual spacers were defined as the overlap volume between the GI tract and the volume expanded 7–17 mm from the gross tumor volume (GTV). Simulation plans (70 Gy in 35 fractions for at least 95% of the planning target volume [PTV]) were created with the lowest possible dose to the GI tract under conditions that meet the dose constraints of the PTV. We defined the minimum thickness of virtual spacers meeting D2 cc of the GI tract <50 Gy as ‘MTS’. Multiple regression was used with explanatory variables to develop a model to predict MTS. We discovered that MTSs were at most 9 mm and 13 mm for C-ion RT and photon RT plans, respectively. The volume of overlap between the GI tract and a virtual spacer of 14 mm in thickness (OV14)-PTV was found to be the most important explanatory variable in the MTS prediction equation for both C-ion and photon RT plans. Multiple R(2) values for the regression model were 0.571 and 0.347 for C-ion RT and photon RT plans, respectively. In conclusion, regression equations were developed to predict MTS in C-ion RT and photon RT. |
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