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Correlation between the γ passing rates of IMRT plans and the volumes of air cavities and bony structures in head and neck cancer

Authors :
Zhengwen Shen
Xia Tan
Ying Wang
Fu Jin
Huanli Luo
Xiu-Mei Tian
Shi Li
Source :
Radiation Oncology, Vol 16, Iss 1, Pp 1-8 (2021), Radiation Oncology (London, England)
Publication Year :
2021
Publisher :
Springer Science and Business Media LLC, 2021.

Abstract

Background Both patient-specific dose recalculation and γ passing rate analysis are important for the quality assurance (QA) of intensity modulated radiotherapy (IMRT) plans. The aim of this study was to analyse the correlation between the γ passing rates and the volumes of air cavities (Vair) and bony structures (Vbone) in target volume of head and neck cancer. Methods Twenty nasopharyngeal carcinoma and twenty nasal natural killer T-cell lymphoma patients were enrolled in this study. Nine-field sliding window IMRT plans were produced and the dose distributions were calculated by anisotropic analytical algorithm (AAA), Acuros XB algorithm (AXB) and SciMoCa based on the Monte Carlo (MC) technique. The dose distributions and γ passing rates of the targets, organs at risk, air cavities and bony structures were compared among the different algorithms. Results The γ values obtained with AAA and AXB were 95.6 ± 1.9% and 96.2 ± 1.7%, respectively, with 3%/2 mm criteria (p > 0.05). There were significant differences (p Vair (R2 = 0.674) and inversely proportional to the natural logarithm of Vbone (R2 = 0.816). When the Vair in the targets was smaller than approximately 80 cc or the Vbone in the targets was larger than approximately 6 cc, the γ values of AAA were below 95%. Using AXB, no significant relationship was found between the γ values and Vair or Vbone. Conclusion In clinical head and neck IMRT QA, greater attention should be paid to the effect of Vair and Vbone in the targets on the γ passing rates when using different dose calculation algorithms.

Details

ISSN :
1748717X
Volume :
16
Database :
OpenAIRE
Journal :
Radiation Oncology
Accession number :
edsair.doi.dedup.....c2afb547e7277eea056be4a4cef9c955