Application of the second derivative-based small monitor unit beam deletion optimization to CyberKnife planning of heads
10.3760/cma.j.cn112271-20221114-00445
- VernacularTitle:基于二阶导数的小跳数射野删减优化在射波刀头部计划中的应用
- Author:
Yongchao XIONG
1
;
Zhiyong YANG
;
Jing YANG
;
Junping CHENG
;
Bin HU
;
Ye WANG
;
Zhenjun PENG
;
Sheng ZHANG
Author Information
1. 华中科技大学同济医学院附属协和医院放疗科，武汉 430022
- Keywords:
CyberKnife;
Second derivative;
Plan optimization;
Brain metastasis
- From:
Chinese Journal of Radiological Medicine and Protection
2023;43(3):198-203
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the effects of different small monitor unit (MU) beam deletion optimization method in the CyberKnife treatment planning system on the calculated planned dose to brain tumors.Methods:A total of 17 patients with brain metastases treated in our hospital from June, 2021 to February, 2022 were selected for this study. A treatment plan was designed for each patient using the multiPlan system in the CyberKnife VSI system as the group without optimization. To improve the efficiency, the generated original plans should be optimized first by deleting some small MUs, forming an experience group and an optimization group for each patient. For the experience group, beams below 30 MU were deleted according to experience. For the optimization group, beams below the MU value calculated based on the second derivative method were deleted. Finally, the parameters of the two groups were statistically compared. The main evaluation parameters included the node number, the beam number, the total number of MUs, the estimated treatment duration, doses to 2% and 95% planning target volumes (PTV D2 and PTV D95), average dose to PTV ( Dmean), average dose to brain tissue ( Dmean-Brain), conformity index (CI), new conformity index (nCI), gradient index (GI), coverage, and the maximum doses to the brainstem and left and right lens ( Dmax-BS, Dmax-LL, and Dmax-RL), and the average doses to the dose shells 20 mm and 40 mm away from PTV (Shell20 and Shell40). Results:The two optimization method met the requirements for the prescription dose delivery to more than 98% PTV. There were statistical differences in the node number ( H = 7.97, P< 0.05) and estimated treatment duration ( H = 6.60, P < 0.05) among the group without MP optimization, the experience group, and the optimization group, with the estimated treatment duration and node number of the optimization group less than those of the group without MP optimization ( P < 0.05). There were no statistically significant differences in other parameters among the three groups ( P > 0.05). The PTV was moderately positively correlated with the treatment duration ( r=0.79, P < 0.01) and beam number ( r=0.78, P < 0.01) of the experience group, and was also moderately positively correlated with the treatment duration ( r=0.69, P < 0.01) and beam number ( r=0.71, P < 0.01) of the optimization group. Conclusions:For the CyberKnife planning of heads, the small MU beam deletion optimization method based on the second derivative can further shorten the treatment duration while ensuring no significant differences in the distribution of doses to organs at risk and targets. Moreover, this method is more effective in optimizing the plans for a large PTV volume.
