A multi‐institutional evaluation of machine performance check system on treatment beam output and symmetry using statistical process control

Abstract

Background The automated and integrated machine performance check (MPC) tool was verified against independent detectors to evaluate its beam uniformity and output detection abilities to consider it suitable for daily quality assurance (QA). Methods Measurements were carried out on six linear accelerators (each located at six individual sites) using clinically available photon and electron energies for a period up to 12 months (n = 350). Daily constancy checks on beam symmetry and output were compared against independent devices such as the SNC Daily QA 3, PTW Farmer ionization chamber, and SNC field size QA phantom. MPC uniformity detection of beam symmetry adjustments was also assessed. Sensitivity of symmetry and output measurements were assessed using statistical process control (SPC) methods to derive tolerances for daily machine QA and baseline resets to account for drifts in output readings. I‐charts were used to evaluate systematic and nonsystematic trends to improve error detection capabilities based on calculated upper and lower control levels (UCL/LCL) derived using standard deviations from the mean dataset. Results This study investigated the vendor's method of uniformity detection. Calculated mean uniformity variations were within ± 0.5% of Daily QA 3 vertical symmetry measurements. Mean MPC output variations were within ± 1.5% of Daily QA 3 and ±0.5% of Farmer ionization chamber detected variations. SPC calculated UCL values were a measure of change observed in the output detected for both MPC and Daily QA 3. Conclusions Machine performance check was verified as a daily quality assurance tool to check machine output and symmetry while assessing against an independent detector on a weekly basis. MPC output detection can be improved by regular SPC‐based trend analysis to measure drifts in the inherent device and control systematic and random variations thereby increasing confidence in its capabilities as a QA device. A 3‐monthly MPC calibration assessment was recommended based on SPC capability and acceptability calculations.

Long‐term experience of MPC across multiple TrueBeam linacs: MPC concordance with conventional QC and sensitivity to real‐world faults

“…1,2 In recent years, automated QC programs utilizing the electronic portal imaging device have been proposed, 3,4 and Linac vendors have begun to incorporate QC applications into the Linac platforms. One such application is Machine There have been a number of publications evaluating and validating the accuracy of MPC [5][6][7][8][9][10] since it was first introduced by Varian in 2015. The testing of MPC to date has been via two methods: either comparing constancy over time against another established measurement method [5][6][7][8][9] or via the introduction of deliberate errors.…”

“…One such application is Machine There have been a number of publications evaluating and validating the accuracy of MPC [5][6][7][8][9][10] since it was first introduced by Varian in 2015. The testing of MPC to date has been via two methods: either comparing constancy over time against another established measurement method [5][6][7][8][9] or via the introduction of deliberate errors. [6][7][8]10 Methods for introducing deliberate errors included intentionally incorrectly calibrating a Linac parameter, for example, the Linac beam symmetry or MLC position calibration, [6][7][8] or by introducing solid water into the beam path, 10 or by applying known motions to the MPC phantom using a rotating/linear motion stage.…”

Determination of machine‐specific tolerances using statistical process control analysis of long‐term uniform scanning proton machine QA results

“…The application of SPC to control charts allows users to assess the temporal stability of each test parameter and determine whether the various parameters of the system are in statistical control. [2][3][4][5][6] Literature [2][3][4] has reported using control limits at AE3σ for detecting meaningful changes in system performance. The SPC helps in monitoring the process using the control charts, which are used to distinguish between the common and special cause variations.…”

“…[2][3][4] Several studies [2][3][4][5][6][7][8][9][10][11] highlighted the importance of using SPC analysis in the radiotherapy department. For instance, Binny et al 2,7 used the SPC to evaluate the beam output and symmetry of the linear accelerators. Shiraishi et al 11 and Stanley et al 5,6 assessed the stability of image quality parameters using SPC.…”

Study on the Necessity of Establishing Customized Limits for the Daily QA Program Performed With Daily QA3

“…However, the tolerance limits in AAPM TG-142 is the minimum requirement for quality control, which is mainly based on clinical efficacy without considering the differences during actual quality control process or just assuming that all quality control processes have the same deviation [3]. In addition, with the rapid development of equipment such as morning check equipment and smart radiotherapy platforms [4,5,6], some monthly QA procedures such as flatness and symmetry have gradually become check items for daily quality control. But, there is no corresponding tolerance limits for these new daily QA items currently and limits for the monthly or annual QA procedures have to be used in most cases recently.…”