Diana Binny

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

Abstract 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.

Investigating output and energy variations and their relationship to delivery QA results using Statistical Process Control for helical tomotherapy

The aims of this study were to investigate machine beam parameters using the TomoTherapy quality assurance (TQA) tool, establish a correlation to patient delivery quality assurance results and to evaluate the relationship between energy variations detected using different TQA modules. TQA daily measurement results from two treatment machines for periods of up to 4years were acquired. Analyses of beam quality, helical and static output variations were made. Variations from planned dose were also analysed using Statistical Process Control (SPC) technique and their relationship to output trends were studied. Energy variations appeared to be one of the contributing factors to delivery output dose seen in the analysis. Ion chamber measurements were reliable indicators of energy and output variations and were linear with patient dose verifications.

Radiotherapy Quality Assurance Using Statistical Process Control

Statistical process control (SPC) is an analytical decision-making tool that employs statistics to measure and monitor a system process. The fundamental concept of SPC is to compare current statistics in a process with its previous corresponding statistic for a given period. Using SPC, a control chart is obtained to identify random and systematic variations based on the mean of the process and trends are observed to see how data can vary in each evaluated period. An upper and lower control limit in an SPC derived control chart indicate the range of the process calculated based on the standard deviations from the mean, thereby points that are outside these limits indicate the process to be out of control. Metrics such as: process capability and acceptability ratios were employed to assess whether an applied tolerance is applicable to the existing process. SPC has been applied in this study to assess and recommend quality assurance tolerances in the radiotherapy practice for helical tomotherapy. Various machine parameters such as beam output, energy, couch travel as well as treatment planning parameters such as minimum percentage of open multileaf collimators (MLC) during treatment, planned pitch (couch travel per gantry rotation) and modulation factor (beam intensity) were verified against their delivery quality assurance tolerances to produce SPC based tolerances. Results obtained were an indication of the current processes and mechanical capabilities in the department rather than a vendor recommended or a prescriptive approach based on machine technicalities. In this study, we have provided a simple yet effective method and analysis results to recommend tolerances for a radiotherapy practice. This can help improve treatment efficiency and reduce inaccuracies in dose delivery using an assessment tool that can identify systematic and random variations in a process and hence avoid potential hazardous outcomes.

Tomotherapy treatment site specific planning using statistical process control

BACKGROUND This study investigated planned MLC distribution and treatment region specific plan parameters to recommend optimal delivery parameters based on statistical process techniques. METHODS A cohort of 28 head and neck, 19 pelvic and 23 brain pre-treatment plans were delivered on a helical tomotherapy system using 2.5 cm field width. Parameters such as gantry period, leaf open time (LOT), actual modulation factor, LOT sonogram, treatment duration and couch travel were investigated to derive optimal range for plans that passed acceptable delivery quality assurance. The results were compared against vendor recommendations and previous publications. RESULTS No correlation was observed between vendor recommended gantry period and percentage of minimum leaf open times. The range of gantry period (min-max) observed was 16-21 s for head and neck, 15-22 s for pelvis and 13-18 s for brain plans respectively. It was also noted that the highest percentage (average (X-) ± SD) of leaf open times for a minimum time of 100 ms was seen for brain plans (53.9 ± 9.2%) compared to its corresponding head and neck (34.5 ± 4.2%) and pelvic (32.0 ± 9.4%) plans respectively. CONCLUSIONS We have proposed that treatment site specific delivery parameters be used during planning that are based on the treatment centre and have detailed recommendations and limitations for the studied cohort. This may enable to improve efficiency of treatment deliveries by reducing inaccuracies in MLC distribution.