Correlation between gamma passing rate and complexity of IMRT plan due to MLC position errors. (March 2018)

• Record Type: Journal Article
• Authors: Wang, Yewei; Pang, Xueying; Feng, Lina; Wang, Helong; Bai, Yanling
• Is Part Of: Physica medica. Volume 47(2018)
• Page Start: 112
• Page End: 120
• Publication Date: 2018-03
• Subjects: ArcCHECK -- Gamma passing rate -- MLC -- Complexity; Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2018.03.003
• Languages: English
• ISSNs: 1120-1797

Abstract

Highlights: Γ passing rate gradient was calculated indicating γ results decreasing per MLC error. There is a linear correlation between γ gradient and complexity metric. Correlation between γ and complexity metric is independent of delivery techniques. The impact of imperceptible MLC errors on IMRT plans has been explored. The result can provide a guideline in analyzing the failure of DQA. Abstract: Purpose: This study evaluates the correlation between the susceptibility of the γ passing rate of IMRT plans to the multi-leaf collimator (MLC) position errors and a quantitative plan complexity metric. Methods: Twenty patients were selected for this study. For each patient, two IMRT plans were generated using sliding window and step-&-shoot techniques, respectively. Modulation complexity score (MCS) was calculated for all IMRT plans, and symmetric MLC leaf bank errors, ranging from 0.3 mm to 1 mm, were introduced. Original and modified plans were delivered using Varian's Clinac iX. The obtained dose distribution using ArcCHECK was then compared with the TPS calculated dose distribution of the original plans. 3D gamma analysis was performed for each verification with passing criteria of 2%/2 mm. The γ passing rate decreasing gradient were calculated to evaluate relationship between variation of γ passing rate due to MLC errors and complexity. Results: A linear regression analysis was applied between γ gradient and complexity, and the results showed a linear correlation ( R 2 = 0.81 and 0.82 for open and closed MLC error types, respectively) indicating the more complex plans are more susceptible to MLC leaf bank errors. Meanwhile, correlation of re-normalized γ passing rate and complexity for all errors scenarios also presented a strong correlation (r > 0.75). Conclusion: The statistics results revealed variation relationship of dosimetry robust of plans with various complexities to MLC errors. Our results also suggested that the observed susceptibility is independent of the delivery techniques.