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

机译:使用统计过程控制对机器性能检查系统进行处理束输出和对称性的多机构评估

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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.
机译:背景技术自动化和集成的机器性能检查(MPC)工具已通过独立检测器进行了验证,以评估其光束均匀性和输出检测能力,从而认为它适合日常质量保证(QA)。方法使用临床上可用的光子和电子能量在六个线性加速器(每个位于六个位置)上进行长达12个月的测量(n = 350)。与独立设备(例如SNC Daily QA 3,PTW Farmer电离室和SNC场大小QA幻像)相比,对每天的光束对称性和输出的稳定性进行了比较。还评估了光束对称性调整的MPC均匀性检测。使用统计过程控制(SPC)方法评估对称性和输出测量的敏感性,以得出每日机器质量检查和基线重置的公差,以解决输出读数中的偏差。 I图表用于评估系统趋势和非系统趋势,以基于使用均值数据的标准偏差得出的上,下控制水平(UCL / LCL)来提高错误检测能力。结果本研究调查了供应商的均匀性检测方法。计算出的平均均匀度变化在每日QA 3垂直对称测量的±0.5%范围内。 MPC的平均输出变化在每日QA 3的±1.5%之内,而Farmer电离室检测到的变化在±0.5%之内。 SPC计算出的UCL值是对MPC和每日质量检查3所检测到的输出中观察到的变化的一种度量。结论机器性能检查已被确认为每日质量保证工具,用于检查机器的输出和对称性,同时每周对独立检测器进行评估。可以通过基于SPC的常规趋势分析来改善MPC输出检测,以测量固有设备中的漂移并控制系统性和随机性变化,从而增强对其作为QA设备功能的信心。建议根据SPC能力和可接受性计算,每三个月进行一次MPC校准评估。

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