Knowledge-based planning using pseudo-structures for volumetric modulated arc therapy (VMAT) of postoperative uterine cervical cancer: a multi-institutional study

Tatsuya Kamima; Yoshihiro Ueda; Jun-Ichi Fukunaga; Mikoto Tamura; Yumiko Shimizu; Yuta Muraki; Yasuo Yoshioka; Nozomi Kitamura; Yuya Nitta; Masakazu Otsuka; Hajime Monzen

doi:10.5603/RPOR.a2021.0089

Knowledge-based planning using pseudo-structures for volumetric modulated arc therapy (VMAT) of postoperative uterine cervical cancer: a multi-institutional study

Rep Pract Oncol Radiother. 2021 Dec 30;26(6):849-860. doi: 10.5603/RPOR.a2021.0089. eCollection 2021.

Authors

Affiliations

¹ Radiation Oncology Department, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
² Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan.
³ Division of Radiology, Department of Medical Technology, Kyushu University Hospital, Fukuoka, Japan.
⁴ Department of Medical Physics, Graduate School of Medical Sciences, Kindai University, Osaka, Japan.
⁵ Department of Radiology, Seirei Hamamatsu General Hospital, Shizuoka, Japan.

Abstract

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.

Keywords: RapidPlan; cervical cancer; knowledge-based planning; pseudo-structure.