Comparison of MLC error sensitivity of various commercial devices for VMAT pre‐treatment quality assurance

Abstract

The purpose of this study was to compare the MLC error sensitivity of various measurement devices for VMAT pre‐treatment quality assurance (QA). This study used four QA devices (Scandidos Delta4, PTW 2D‐array, iRT systems IQM, and PTW Farmer chamber). Nine retrospective VMAT plans were used and nine MLC error plans were generated for all nine original VMAT plans. The IQM and Farmer chamber were evaluated using the cumulative signal difference between the baseline and error‐induced measurements. In addition, to investigate the sensitivity of the Delta4 device and the 2D‐array, global gamma analysis (1%/1, 2%/2, and 3%/3 mm), dose difference (1%, 2%, and 3%) were used between the baseline and error‐induced measurements. Some deviations of the MLC error sensitivity for the evaluation metrics and MLC error ranges were observed. For the two ionization devices, the sensitivity of the IQM was significantly better than that of the Farmer chamber (P < 0.01) while both devices had good linearly correlation between the cumulative signal difference and the magnitude of MLC errors. The pass rates decreased as the magnitude of the MLC error increased for both Delta4 and 2D‐array. However, the small MLC error for small aperture sizes, such as for lung SBRT, could not be detected using the loosest gamma criteria (3%/3 mm). Our results indicate that DD could be more useful than gamma analysis for daily MLC QA, and that a large‐area ionization chamber has a greater advantage for detecting systematic MLC error because of the large sensitive volume, while the other devices could not detect this error for some cases with a small range of MLC error.

Error sensitivity of a log file analysis tool compared with a helical diode array dosimeter for VMAT delivery quality assurance

“…Many studies evaluated the sensitivity of different QA methods by including different kinds of errors. For example, MLC misalignments errors were investigated by Masahide Saito et al with different QA methods such as Delta 4 15 . The results obtained when trying to detect MLC errors of our AC protocols are comparable with the results of their study.…”

“…Masahide Saito et al with different QA methods such as Delta 4 15. The results obtained when trying to detect MLC errors of our AC protocols are comparable with the results of their study.Delta 4 shows the same behavior as the ArcCHECK Phantom for both global gamma protocols with 3%/3 mm and 2%/2 mm.Moliner et al investigated, among other QA tools, the AC detector.…”

A comprehensive and clinical‐oriented evaluation criteria based on DVH information and gamma passing rates analysis for IMRT plan 3D verification

“…In order to ensure the patient's safety, patient-specific quality assurance (QA) is an essential key link before delivery of IMRT plan 3 . Patient-specific QA analyzes and evaluates the deviation between the predicted dose and the measured dose of patient plan in phantom by film dosimetry 4 , ionization chambers 5 , electronic portal imaging device (EPID) 6 , two-dimensional (2D) array detector [7][8][9] , three-dimensional (3D) dosimetric systems, and the gel dosimetry 10,11 , etc. For performing quantitative evaluation to the calculation accuracy of TPS system and the delivery precision of linear accelerator, Low et al 12 proposed the gamma analysis method.…”

An artificial neural network to model response of a radiotherapy beam monitoring system

“…Literature is becoming available on the characteristics and the performance of the device. [7][8][9][10] The treatment beam is validated by comparing the measured IQM detector signal with the corresponding predicted signal calculated by an analytic numerical model. The calculation model 9 requires extensive measurement to characterize the radiation delivery unit (Linac) and IQM detector, and interactions between them.…”

“…This system enables the efficiency of validating beam delivery, both as a pretreatment plan QA and also during daily treatment. Literature is becoming available on the characteristics and the performance of the device . The treatment beam is validated by comparing the measured IQM detector signal with the corresponding predicted signal calculated by an analytic numerical model.…”