Retrospective analysis of linear accelerator output constancy checks using process control techniques

Abstract

Shewhart control charts have previously been suggested as a process control tool for use in routine linear accelerator (linac) output verifications. However, a comprehensive approach to process control has not been investigated for linac output verifications. The purpose of this work is to investigate a comprehensive process control approach to linac output constancy quality assurance (QA). The RBA‐3 dose constancy check was used to verify outputs of photon beams and electron beams delivered by a Varian Clinac 21EX linac. The data were collected during 2009 to 2010. Shewhart‐type control charts, exponentially weighted moving average (EWMA) charts, and capability indices were applied to these processes. The Shewhart‐type individuals chart (X‐chart) was used and the number of data points used to calculate the control limits was varied. The parameters tested for the EWMA charts (smoothing parameter (λ) and the control limit width (L)) were λ=0.05, normalL=2.492; λ=0.10, normalL=2.703; and λ=0.20, normalL=2.860, as well as the number of points used to estimate the initial process mean and variation. Lastly, the number of in‐control data points used to determine process capability (Cp) and acceptability (Cpk) were investigated, comparing the first in‐control run to the longest in‐control run of the process data. Cnormalp and Cpk values greater than 1.0 were considered acceptable. The 95% confidence intervals were reported. The X‐charts detected systematic errors (e.g., device setup errors). In‐control run lengths on the X‐charts varied from 5 to 30 output measurements (about one to seven months). EWMA charts showed in‐control runs ranging from 9 to 33 output measurements (about two to eight months). The Cnormalp and Cpk ratios are higher than 1.0 for all energies, except 12 and 20 MeV. However, 10 MV and 6, 9, and 16 MeV were in question when considering the 95% confidence limits. The X‐chart should be calculated using 8–12 data points. For EWMA chart, using 4 data points is sufficient to calculate the initial mean and variance of the process. The EWMA limits should be calculated with λ=0.10, normalL=2.703. At least 25–30 in‐control data points should be used to calculate the Cnormalp and Cpk indices.PACS number: 89

Output trends, characteristics, and measurements of three megavoltage radiotherapy linear accelerators

“…The frequency and action level can be modified based on the results of this type of studies along with comprehensive statistical analysis of the type done by Sanghangthum et al 7 .…”

Dosimetric and Mechanical Stability of CyberKnife Robotic Radiosurgery Unit: 5 Years’ Clinical Experience

“…Dosimetric and mechanical QC of a linac is the process of keeping the accuracy of machine functions within suggested tolerance limits. [1,2] Reports and documents for these suggested values have been published by the International Atomic Energy Agency (IAEA), the American Association of Physicists in Medicine (AAPM), the European Society for Therapeutic Radiology and Oncology (ESTRO), and by several other national and international organizations. [3] The main purpose of all these QA programs is to standardize function of the treatment and measurement equipment used in RT facilities, and thus to maximize quality of patient care.…”

What can statistical process control show us about ionization chamber stability?

“…Nevertheless, medical physics departments have a great deal of stored historical data regarding many controlled systems (Sanghangthum et al, 2013b;Gagneur and Ezzell, 2014). In our opinion, these vast data sets can be contrasted against an SPC monitoring system, as we have done here, before starting ambitious blind-prospective SPC experiments.…”

“…We did not want to neglect this recommendation and so we verified our samples with the Ryan-Joiner test as well and obtained a p>0.100 in all cases. With regard to a lack of normality, one can also work with the exponentially weighted moving average (EWMA) control chart, which is not sensitive to non-normality, although its ability to detect small shifts makes it suitable only when the process under study is well within control (Gérard et al, 2009;Sanghangthum et al, 2013b). Finally, other capability indices have been derived to deal with non-normal data.…”

“…In recent years several groups have published work which illustrates how SPC can be applied to the different systems controlled by medical physicists in the various radiotherapy processes related to linear particle accelerator (linac) monitoring (Pawlicki et al, 2005;Able et al, 2011;de la Vega et al, 2012;Sanghangthum et al, 2013b;Létourneau et al, 2014;López-Tarjuelo et al, 2015), image guided radiation therapy (IGRT; Ung and Wee, 2011), monitor-unit verifications (Nordström et al, 2012), high-dose rate (HDR) brachytherapy treatments (Able et al, 2013), proton therapy beams (Rah et al, 2014), and different aspects of intensity-modulated treatment quality assurance (Breen et al, 2008;Pawlicki et al, 2008a;Pawlicki et al, 2008b;Gérard et al, 2009;Sanghangthum et al, 2013c;Sanghangthum et al, 2013a;Gagneur and Ezzell, 2014).…”