Effects of different grid spacing and statistical uncertainty in MC algorithm of Monaco TPS on gamma pass rate
10.3760/cma.j.cn113030-20240202-00041
- VernacularTitle:Monaco的蒙特卡罗算法网格间距和不确定度对γ通过率的影响
- Author:
Yong SANG
1
;
Jun DANG
;
Jiajun CAI
Author Information
1. 国家癌症中心/国家肿瘤临床医学研究中心/中国医学科学院北京协和医学院肿瘤医院深圳医院放疗科，深圳 518116
- Keywords:
Monte Carlo;
Gamma pass rate;
Statistical uncertainty;
Grid spacing
- From:
Chinese Journal of Radiation Oncology
2024;33(11):1056-1063
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To compare the impact of Monte Carlo (MC) algorithm grid spacing (GS) and statistical uncertainty (SU) of Monaco on clinical plan validation gamma pass rate, and to provide reference for daily patient-specific quality assurance (PSQA).Methods:Twenty patients treated in Chinese Academy of Medical Sciences and Peking Union Medical College Cancer Hospital & Shenzhen Hospital from July to November 2023 were retrospectively selected, including 5 cases of nasopharyngeal carcinoma in the head, 2 cases of lung cancer, 3 cases of esophageal cancer, 5 cases of breast cancer in the chest, 4 cases of cervical cancer, 1 case of rectal cancer in the abdomen, respectively. All selected patient plans were re-measured on the same day by the same physicist on the same machine to obtain dose distribution files. Three types of GS of Monaco, including 2 mm, 3 mm, and 4 mm (GS2、GS3、GS4), and 5 types percentage of SU, including SU CP1, SU CP2, SU CP3, SU CP4, and SU CL1 were selected. The validation plans were recalculated, with a total of 15 validation plans for each clinical plan. Using a 3%/2 mm evaluation standard, the gamma pass rates of each plan at different GS and SU were analyzed. The gamma pass rates of different GS and SU in the same case plan were analyzed by paired sample t-test. Results:Based on the gamma pass rate of GS2, the differences in gamma pass rates between different GS for the same SU were statistically significant (all P<0.05). For SU CP1, the gamma pass rates of GS3 and GS4 were decreased by 0.4% and 1.4% compared to GS2, respectively. For SU CP2, the gamma pass rates of GS3 and GS4 were decreased by 0.5% and 1.5% compared to GS2, respectively. For SU CP3, the gamma pass rates of GS3 and GS4 were decreased by 0.5% and 1.5% compared to GS2, respectively. For SU CP4, the gamma pass rates of GS3 and GS4 were decreased by 0.5% and 1.5% compared to GS2, respectively. For SU CL1, the gamma pass rates of GS3 and GS4 were decreased by 0.7% and 2.0% compared to GS2, respectively. Based on the gamma pass rate of SU CP1, for the same GS but different SU, there was no statistically significant difference in the gamma pass rate of the SU selected in this study at GS2. However, at GS3 and GS4, the difference between SU CP4 and SU CL1 compared to SU CP1 was statistically significant (at GS3, P=0.049 and 0.012; at GS4, P=0.045 and <0.001), with gamma pass rates reduced by 0.1%, 0.4%, 0.2% and 0.6%, respectively. Conclusions:Both GS and SU values affect the gamma pass rate of PSQA to a certain extent. It is recommended to use Monaco MC algorithm for daily PSQA, selecting GS2 and SU with SU CL1 to calculate the validation plan.
