| Jin Xiaoli,Wang Xuena,Guo Rui,et al.Correlation between plan complexity scores and dose verification pass rates in helical tomotherapy system[J].Chinese Journal of Radiological Medicine and Protection,2024,44(12):1020-1026 |
| Correlation between plan complexity scores and dose verification pass rates in helical tomotherapy system |
| Received:December 05, 2023 |
| DOI：10.3760/cma.j.cn112271-20231205-00197 |
| KeyWords:Helical tomotherapy Plan complexity Pricipal component analysis Plan complexity score |
| FundProject:山西省科学技术厅青年科学研究项目(202203021212108) |
| Author Name | Affiliation | | Jin Xiaoli | Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan 030032, China | | Wang Xuena | Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan 030032, China | | Guo Rui | Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan 030032, China | | Hou Xu | Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan 030032, China | | Lan Yue | Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan 030032, China | | Zhao Xiaojie | Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan 030032, China |
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| Abstract:: |
| Objective To calculate the normalized plan complexity scores (nPCSs), assess their correlations with dose verification pass rates, and utilize nPCSs to compare the complexity of treatment plans for various anatomical parts. Methods A retrospective analysis was conducted for 288 patients who underwent helical tomotherapy from January 2020 to November 2022, with 13 complexity parameters being extracted from the treatment plans. Principal components were extracted using principal component analysis (PCA), and those significantly correlated with the gamma pass rate based on the 3%/2 mm (global) criterion were selected to calculate the nPCSs. The correlations between nPCSs and gamma pass rates based on different criteria were assessed using multiple linear regression, and the complexity of treatment plans for different anatomical parts was compared. Results The four principal components, PC1, PC2, PC3, PC4, accounted for 33.5%, 24.4%, 11.4%, and 9.2% of the total variance, respectively, and 78.48% in total. PC1, PC2, and PC3 were linearly correlated with the gamma pass rate based on the 3%/2 mm (global) criterion (β= 0.34, 0.31, 0.62; P < 0.05). The nPCSs were linearly correlated with the gamma pass rates based on both the 3%/2 mm (global) and 1%/1 mm (global) criteria (β= 5.36, 32.51, P < 0.001). The head and neck plans and abdominal-pelvic plans exhibited similar nPCS distributions, with no statistically significant difference (P > 0.05). Conclusions The nPCSs based on PCA can effectively evaluate the feasibility of treatment plans and compare the complexity of different treatment plans. |
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