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Title: TU-FG-201-05: Varian MPC as a Statistical Process Control Tool

Abstract

Purpose: Quality assurance in radiotherapy requires the measurement of various machine parameters to ensure they remain within permitted values over time. In Truebeam release 2.0 the Machine Performance Check (MPC) was released allowing beam output and machine axis movements to be assessed in a single test. We aim to evaluate the Varian Machine Performance Check (MPC) as a tool for Statistical Process Control (SPC). Methods: Varian’s MPC tool was used on three Truebeam and one EDGE linac for a period of approximately one year. MPC was commissioned against independent systems. After this period the data were reviewed to determine whether or not the MPC was useful as a process control tool. Analyses on individual tests were analysed using Shewhart control plots, using Matlab for analysis. Principal component analysis was used to determine if a multivariate model was of any benefit in analysing the data. Results: Control charts were found to be useful to detect beam output changes, worn T-nuts and jaw calibration issues. Upper and lower control limits were defined at the 95% level. Multivariate SPC was performed using Principal Component Analysis. We found little evidence of clustering beyond that which might be naively expected such as beam uniformity andmore » beam output. Whilst this makes multivariate analysis of little use it suggests that each test is giving independent information. Conclusion: The variety of independent parameters tested in MPC makes it a sensitive tool for routine machine QA. We have determined that using control charts in our QA programme would rapidly detect changes in machine performance. The use of control charts allows large quantities of tests to be performed on all linacs without visual inspection of all results. The use of control limits alerts users when data are inconsistent with previous measurements before they become out of specification. A. Carver has received a speaker’s honorarium from Varian.« less

Authors:
;  [1]
  1. The Clatterbridge Cancer Centre NHS Foundation Trust, Bebington, Wirral (United Kingdom)
Publication Date:
OSTI Identifier:
22653987
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
07 ISOTOPES AND RADIATION SOURCES; 61 RADIATION PROTECTION AND DOSIMETRY; BEAMS; LINEAR ACCELERATORS; MULTIVARIATE ANALYSIS; PERFORMANCE; PROCESS CONTROL; QUALITY ASSURANCE

Citation Formats

Carver, A, and Rowbottom, C. TU-FG-201-05: Varian MPC as a Statistical Process Control Tool. United States: N. p., 2016. Web. doi:10.1118/1.4957528.
Carver, A, & Rowbottom, C. TU-FG-201-05: Varian MPC as a Statistical Process Control Tool. United States. doi:10.1118/1.4957528.
Carver, A, and Rowbottom, C. 2016. "TU-FG-201-05: Varian MPC as a Statistical Process Control Tool". United States. doi:10.1118/1.4957528.
@article{osti_22653987,
title = {TU-FG-201-05: Varian MPC as a Statistical Process Control Tool},
author = {Carver, A and Rowbottom, C},
abstractNote = {Purpose: Quality assurance in radiotherapy requires the measurement of various machine parameters to ensure they remain within permitted values over time. In Truebeam release 2.0 the Machine Performance Check (MPC) was released allowing beam output and machine axis movements to be assessed in a single test. We aim to evaluate the Varian Machine Performance Check (MPC) as a tool for Statistical Process Control (SPC). Methods: Varian’s MPC tool was used on three Truebeam and one EDGE linac for a period of approximately one year. MPC was commissioned against independent systems. After this period the data were reviewed to determine whether or not the MPC was useful as a process control tool. Analyses on individual tests were analysed using Shewhart control plots, using Matlab for analysis. Principal component analysis was used to determine if a multivariate model was of any benefit in analysing the data. Results: Control charts were found to be useful to detect beam output changes, worn T-nuts and jaw calibration issues. Upper and lower control limits were defined at the 95% level. Multivariate SPC was performed using Principal Component Analysis. We found little evidence of clustering beyond that which might be naively expected such as beam uniformity and beam output. Whilst this makes multivariate analysis of little use it suggests that each test is giving independent information. Conclusion: The variety of independent parameters tested in MPC makes it a sensitive tool for routine machine QA. We have determined that using control charts in our QA programme would rapidly detect changes in machine performance. The use of control charts allows large quantities of tests to be performed on all linacs without visual inspection of all results. The use of control limits alerts users when data are inconsistent with previous measurements before they become out of specification. A. Carver has received a speaker’s honorarium from Varian.},
doi = {10.1118/1.4957528},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • The same driving forces that are making businesses examine quality control of manufacturing processes are making laboratories reevaluate their quality control programs. Increased regulation (accountability), global competitiveness (profitability), and potential for litigation (defensibility) are the principal driving forces behind the development and implementation of QA/QC programs in the nuclear analytical laboratory. Both manufacturing and scientific quality control can use identical statistical methods, albeit with some differences in the treatment of the measured data. Today, the approaches to QC programs are quite different for most analytical laboratories as compared with manufacturing sciences. This is unfortunate because the statistical process control methodsmore » are directly applicable to measurement processes. It is shown that statistical process control methods can provide many benefits for laboratory QC data treatment.« less
  • Purpose: Statistical process control (SPC) is a quality control method used to ensure that a process is well controlled and operates with little variation. This study determined whether SPC was a viable technique for evaluating the proper operation of a high-dose-rate (HDR) brachytherapy treatment delivery system. Methods and Materials: A surrogate prostate patient was developed using Vyse ordnance gelatin. A total of 10 metal oxide semiconductor field-effect transistors (MOSFETs) were placed from prostate base to apex. Computed tomography guidance was used to accurately position the first detector in each train at the base. The plan consisted of 12 needles withmore » 129 dwell positions delivering a prescribed peripheral dose of 200 cGy. Sixteen accurate treatment trials were delivered as planned. Subsequently, a number of treatments were delivered with errors introduced, including wrong patient, wrong source calibration, wrong connection sequence, single needle displaced inferiorly 5 mm, and entire implant displaced 2 mm and 4 mm inferiorly. Two process behavior charts (PBC), an individual and a moving range chart, were developed for each dosimeter location. Results: There were 4 false positives resulting from 160 measurements from 16 accurately delivered treatments. For the inaccurately delivered treatments, the PBC indicated that measurements made at the periphery and apex (regions of high-dose gradient) were much more sensitive to treatment delivery errors. All errors introduced were correctly identified by either the individual or the moving range PBC in the apex region. Measurements at the urethra and base were less sensitive to errors. Conclusions: SPC is a viable method for assessing the quality of HDR treatment delivery. Further development is necessary to determine the most effective dose sampling, to ensure reproducible evaluation of treatment delivery accuracy.« less
  • Purpose: High-quality radiation therapy using highly conformal dose distributions and image-guided techniques requires optimum machine delivery performance. In this work, a monitoring system for multileaf collimator (MLC) performance, integrating semiautomated MLC quality control (QC) tests and statistical process control tools, was developed. The MLC performance monitoring system was used for almost a year on two commercially available MLC models. Control charts were used to establish MLC performance and assess test frequency required to achieve a given level of performance. MLC-related interlocks and servicing events were recorded during the monitoring period and were investigated as indicators of MLC performance variations. Methods:more » The QC test developed as part of the MLC performance monitoring system uses 2D megavoltage images (acquired using an electronic portal imaging device) of 23 fields to determine the location of the leaves with respect to the radiation isocenter. The precision of the MLC performance monitoring QC test and the MLC itself was assessed by detecting the MLC leaf positions on 127 megavoltage images of a static field. After initial calibration, the MLC performance monitoring QC test was performed 3–4 times/week over a period of 10–11 months to monitor positional accuracy of individual leaves for two different MLC models. Analysis of test results was performed using individuals control charts per leaf with control limits computed based on the measurements as well as two sets of specifications of ±0.5 and ±1 mm. Out-of-specification and out-of-control leaves were automatically flagged by the monitoring system and reviewed monthly by physicists. MLC-related interlocks reported by the linear accelerator and servicing events were recorded to help identify potential causes of nonrandom MLC leaf positioning variations. Results: The precision of the MLC performance monitoring QC test and the MLC itself was within ±0.22 mm for most MLC leaves and the majority of the apparent leaf motion was attributed to beam spot displacements between irradiations. The MLC QC test was performed 193 and 162 times over the monitoring period for the studied units and recalibration had to be repeated up to three times on one of these units. For both units, rate of MLC interlocks was moderately associated with MLC servicing events. The strongest association with the MLC performance was observed between the MLC servicing events and the total number of out-of-control leaves. The average elapsed time for which the number of out-of-specification or out-of-control leaves was within a given performance threshold was computed and used to assess adequacy of MLC test frequency. Conclusions: A MLC performance monitoring system has been developed and implemented to acquire high-quality QC data at high frequency. This is enabled by the relatively short acquisition time for the images and automatic image analysis. The monitoring system was also used to record and track the rate of MLC-related interlocks and servicing events. MLC performances for two commercially available MLC models have been assessed and the results support monthly test frequency for widely accepted ±1 mm specifications. Higher QC test frequency is however required to maintain tighter specification and in-control behavior.« less
  • The aim of this study is to introduce tools to improve the security of each IMRT patient treatment by determining action levels for the dose delivery process. To achieve this, the patient-specific quality control results performed with an ionization chamber--and which characterize the dose delivery process--have been retrospectively analyzed using a method borrowed from industry: Statistical process control (SPC). The latter consisted in fulfilling four principal well-structured steps. The authors first quantified the short term variability of ionization chamber measurements regarding the clinical tolerances used in the cancer center ({+-}4% of deviation between the calculated and measured doses) by calculatingmore » a control process capability (C{sub pc}) index. The C{sub pc} index was found superior to 4, which implies that the observed variability of the dose delivery process is not biased by the short term variability of the measurement. Then, the authors demonstrated using a normality test that the quality control results could be approximated by a normal distribution with two parameters (mean and standard deviation). Finally, the authors used two complementary tools--control charts and performance indices--to thoroughly analyze the IMRT dose delivery process. Control charts aim at monitoring the process over time using statistical control limits to distinguish random (natural) variations from significant changes in the process, whereas performance indices aim at quantifying the ability of the process to produce data that are within the clinical tolerances, at a precise moment. The authors retrospectively showed that the analysis of three selected control charts (individual value, moving-range, and EWMA control charts) allowed efficient drift detection of the dose delivery process for prostate and head-and-neck treatments before the quality controls were outside the clinical tolerances. Therefore, when analyzed in real time, during quality controls, they should improve the security of treatments. They also showed that the dose delivery processes in the cancer center were in control for prostate and head-and-neck treatments. In parallel, long term process performance indices (P{sub p}, P{sub pk}, and P{sub pm}) have been analyzed. Their analysis helped defining which actions should be undertaken in order to improve the performance of the process. The prostate dose delivery process has been shown statistically capable (0.08% of the results is expected to be outside the clinical tolerances) contrary to the head-and-neck dose delivery process (5.76% of the results are expected to be outside the clinical tolerances).« less
  • Purpose: The purpose of this project was to develop a process that utilizes the onboard kV and MV electronic portal imaging devices (EPIDs) to perform rapid acceptance testing (AT) of linacs in order to improve efficiency and standardize AT equipment and processes. Methods: In this study a Varian TrueBeam linac equipped with an amorphous silicon based EPID (aSi1000) was used. The conventional set of AT tests and tolerances was used as a baseline guide, and a novel methodology was developed to perform as many tests as possible using EPID exclusively. The developer mode on Varian TrueBeam linac was used tomore » automate the process. In the current AT process there are about 45 tests that call for customer demos. Many of the geometric tests such as jaw alignment and MLC positioning are performed with highly manual methods, such as using graph paper. The goal of the new methodology was to achieve quantitative testing while reducing variability in data acquisition, analysis and interpretation of the results. The developed process was validated on two machines at two different institutions. Results: At least 25 of the 45 (56%) tests which required customer demo can be streamlined and performed using EPIDs. More than half of the AT tests can be fully automated using the developer mode, while others still require some user interaction. Overall, the preliminary data shows that EPID-based linac AT can be performed in less than a day, compared to 2–3 days using conventional methods. Conclusions: Our preliminary results show that performance of onboard imagers is quite suitable for both geometric and dosimetric testing of TrueBeam systems. A standardized AT process can tremendously improve efficiency, and minimize the variability related to third party quality assurance (QA) equipment and the available onsite expertise. Research funding provided by Varian Medical Systems. Dr. Sasa Mutic receives compensation for providing patient safety training services from Varian Medical Systems, the sponsor of this study.« less