Preliminary Retrospective Analysis of Daily Tomotherapy Output Constancy Checks Using Statistical Process Control

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.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Binny

Aland

Archibald-Heeren³

et al. 2019

“…Quality control (QC) protocols involve assessing if the machine performance is within specified tolerance levels and taking planned, systematic actions to ensure the same 2, 3, 4. QC of the treatment couch is important as it is a major component in patient localization during treatment, and various tests are recommended to ensure its optimal functioning at all times 1, 4, 5.…”

Section: Introductionmentioning

confidence: 99%

“…In order to ensure that the results of QC tests are within specified criteria, quality assurance (QA) tools like fault‐tree analysis, statistical process control (SPC) and other computational assessments have been applied in health care 3, 11, 12, 13, 14, 15, 16, 17, 18, 19. A few studies1, 8, 9, 20, 21 have been performed to test the mechanical and dosimetric capability of the high‐performance (HP) couch and other TomoTherapy machine parameters; however, there has been no studies that applied control charts to couch offset constancy measurements or verified positional accuracy of the HP couch at the isocenter.…”

Section: Introductionmentioning

confidence: 99%

“…SPC employs a process to convert data to information by using statistical techniques,16 in this case to identify random and systematic errors in the current process of couch testing using the aluminum step wedge in a helical beam. The control chart obtained from this technique shows how the process varies over time 3, 12, 16. A bold center line (CL) in this control chart corresponds to the average of the process which is also the reference for data point dispersion.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Statistical process control and verifying positional accuracy of a cobra motion couch using step‐wedge quality assurance tool

Binny

Lancaster

Trapp

et al. 2017

This study utilizes process control techniques to identify action limits for TomoTherapy couch positioning quality assurance tests. A test was introduced to monitor accuracy of the applied couch offset detection in the TomoTherapy Hi‐Art treatment system using the TQA “Step‐Wedge Helical” module and MVCT detector. Individual X‐charts, process capability (cp), probability (P), and acceptability (cpk) indices were used to monitor a 4‐year couch IEC offset data to detect systematic and random errors in the couch positional accuracy for different action levels. Process capability tests were also performed on the retrospective data to define tolerances based on user‐specified levels. A second study was carried out whereby physical couch offsets were applied using the TQA module and the MVCT detector was used to detect the observed variations.Random and systematic variations were observed for the SPC‐based upper and lower control limits, and investigations were carried out to maintain the ongoing stability of the process for a 4‐year and a three‐monthly period. Local trend analysis showed mean variations up to ±0.5 mm in the three‐monthly analysis period for all IEC offset measurements. Variations were also observed in the detected versus applied offsets using the MVCT detector in the second study largely in the vertical direction, and actions were taken to remediate this error. Based on the results, it was recommended that imaging shifts in each coordinate direction be only applied after assessing the machine for applied versus detected test results using the step helical module. User‐specified tolerance levels of at least ±2 mm were recommended for a test frequency of once every 3 months to improve couch positional accuracy. SPC enables detection of systematic variations prior to reaching machine tolerance levels. Couch encoding system recalibrations reduced variations to user‐specified levels and a monitoring period of 3 months using SPC facilitated in detecting systematic and random variations. SPC analysis for couch positional accuracy enabled greater control in the identification of errors, thereby increasing confidence levels in daily treatment setups.

Applying the six‐sigma methodology to determine the limits of quality control (QC) tests for a specific linear accelerator

Ma,

Li,

Zhang

et al. 2024

PurposeWe aimed to show the framework of the six‐sigma methodology (SSM) that can be used to determine the limits of QC tests for the linear accelerator (Linac). Limits for QC tests are individually determined using the SSM.Methods and MaterialsThe SSM is based on the define‐measure‐analyze‐improve‐control (DMAIC) stages to improve the process. In the “define” stage, the limits of QC tests were determined. In the “measure” stage, a retrospective collection of daily QC data using a Machine Performance Check platform was performed from January 2020 to December 2022. In the “analyze” stage, the process of determining the limits was proposed using statistical analyses and process capability indices. In the “improve” stage, the capability index was used to calculate the action limits. The tolerance limit was established using the larger one of the control limits in the individual control chart (I‐chart). In the “control” stage, daily QC data were collected prospectively from January 2023 to May 2023 to monitor the effect of action limits and tolerance limits.ResultsA total of 798 sets of QC data including beam, isocenter, collimation, couch, and gantry tests were collected and analyzed. The Collimation Rotation offset test had the min‐Cp, min‐Cpk, min‐Pp, and min‐Ppk at 2.53, 1.99, 1.59, and 1.25, respectively. The Couch Rtn test had the max‐Cp, max‐Cpk, max‐Pp, and max‐Ppk at 31.5, 29.9, 23.4, and 22.2, respectively. There are three QC tests with higher action limits than the original tolerance. Some data on the I‐chart of the beam output change, isocenter KV offset, and jaw X1 exceeded the lower tolerance and action limit, which indicated that a system deviation occurred and reminded the physicist to take action to improve the process.ConclusionsThe SSM is an excellent framework to use in determining the limits of QC tests. The process capability index is an important parameter that provides quantitative information on determining the limits of QC tests.