A multi‐institutional evaluation of machine performance check system on treatment beam output and symmetry using statistical process control
| Autor: | Diana Binny, Trent Aland, Jamie Trapp, Scott Crowe, Ben Archibald-Heeren, Tanya Kairn |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Quality Assurance
Health Care Statistics as Topic Imaging phantom Standard deviation 02.70.Rr 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Calibration Humans Radiation Oncology Physics Radiology Nuclear Medicine and imaging Sensitivity (control systems) Radiometry Instrumentation Simulation Mathematics machine performance check (MPC) Photons Radiation Phantoms Imaging business.industry Radiotherapy Planning Computer-Assisted Detector Radiotherapy Dosage Statistical process control statistical process control (SPC) 87.52.-G quality assurance (QA) 030220 oncology & carcinogenesis Ionization chamber Radiotherapy Intensity-Modulated Particle Accelerators business EPID Quality assurance |
| Zdroj: | Journal of Applied Clinical Medical Physics |
| ISSN: | 1526-9914 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text