Feasibility method for reducing the total monitor units in Eclipse TPS
10.3760/cma.j.issn.1673-4181.2019.02.011
- VernacularTitle:在Eclipse计划系统中减少治疗野总MU数的可行方法
- Author:
Kuo LI
1
,
2
;
Youjiu ZHANG
;
Linlin LI
;
Cheng LI
;
Danqing SHEN
;
Rui HU
Author Information
1. 苏州大学医学部放射医学与防护学院 215123
2. 南京医科大学附属苏州医院
- Keywords:
Eclipse TPS;
Nasopharyngeal carcinoma;
Fluence;
Monitor units
- From:
International Journal of Biomedical Engineering
2019;42(2):150-153,160
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the feasibility of using the optimization parameters modification and optimization processes modification to reduce the total monitor units ( MUs ) in the Eclipse radiotherapy treatment planning system (TPS). Methods Based on the radiotherapy plan of 10 patients with nasopharyngeal carcinoma, a total of 90 plans were designed for 9 groups using different optimization parameters and processes. The total MUs and the exposure dose of the organs among the different plans were compared. Results There was no significant difference in the doses of the organs at risk (class I) under the premise of target dose requirements (all P>0.05). The increase of the weight of the target area and the organs at risk will increase the total MUs. The increase of the preset limit value of the minimum MUs in the subfield will reduce the total MUs. The increase of the fluence smoothness in the X and Y directions will increase the total MUs. An unreasonable minimum MU value will increase the total MUs. Under the condition that the organ exposure is not changed significantly, the influencing factors of MU are ranked as weight>fluence smoothness>minimum MUs. Conclusions Parameter setting and process planning can reduce the total MUs to a certain extent. However, due to the complexity of the influence of optimization parameters on the plan, the optimization process should be preferred. Especially in the Eclipse TPS, the method of gradual optimization to achieve the final dose distribution requirement and then remove the fluence re-optimization is more convenient and effective for reducing the total MUs.
