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Knowledge-based planning using pseudo-structures for volumetric modulated arc therapy (VMAT) of postoperative uterine cervical cancer: a multi-institutional study
BACKGROUND: The aim of this study was to investigate the performance of the RapidPlan (RP ) using models registered pseudostructures, and to determine how many structures are required for automatic optimization of volumetric modulated arc therapy (VMAT) for postoperative uterine cervical cancer. MAT...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Via Medica
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8726433/ https://www.ncbi.nlm.nih.gov/pubmed/34992856 http://dx.doi.org/10.5603/RPOR.a2021.0089 |
Sumario: | BACKGROUND: The aim of this study was to investigate the performance of the RapidPlan (RP ) using models registered pseudostructures, and to determine how many structures are required for automatic optimization of volumetric modulated arc therapy (VMAT) for postoperative uterine cervical cancer. MATERIALS AND METHODS: Pseudo-structures around the PTV were retrospectively contoured for patients who had completed treatment at five institutions. For 22 common patients, plans were generated with a single optimization for models with two (RP_2), four (RP_4), and five (RP_5) registered structures, and the dosimetric parameters of these models were compared with a clinical plan with several optimizations. RESULTS: Most dosimetric parameters showed no major differences between each RP model. In particular, the rectum D(max), V(50Gy), and V(40Gy) with RP_2, RP_4, and RP_5 were not significantly different, and were lower than those of the clinical plan. The average proportions of plans achieving acceptable criteria for dosimetric parameters were close to 100% for all models. Using RP_2, the average time for the VMAT planning was reduced by 88 minutes compared with the clinical plan. CONCLUSION: The RapidPlan model with two registered pseudo-structures could generate clinically acceptable plans while saving time. |
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