Knowledge-based planning using pseudo-structures for volumetric modulated arc therapy (VMAT) of postoperative uterine cervical cancer: a multi-institutional study
Abstract
Background: The aim of this study was to investigate the performance of the RapidPlan (RP) using models registered pseudo-structures, 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 Dmax, V50Gy, and V40Gy 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.
Keywords: knowledge-based planningRapidPlancervical cancerpseudo-structure
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