PURPOSE: Applying statistical process control (SPC) to intensity-modulated radiotherapy (IMRT)/volumetric modulated arc therapy (VMAT) patient-specific quality assurance (PSQA) program was recommended by the American Association of Physics in Medicine Task Group 218 report, but a comprehensive analysis of PSQA processes with non-normal distributions is lacking. This study investigates SPC and process capability analysis (PCA) methods for non-normal IMRT/VMAT PSQA processes. METHODS: 1119 VMAT PSQAs were performed on three beam-matched linear accelerators (linacs), using gamma analysis. The Anderson-Darling statistic was used to test normality. The control charts for each PSQA process were obtained using three non-normal-based methods and compared with the conventional Shewhart method. The ability of each PSQA process to produce an output within the specification limit was measured using the C pk index; in this study, the C pk index was calculated using two transformation methods and compared with that calculated using the conventional method. The performances of the three linacs were assessed using SPC and PCA methods. RESULTS: All three PSQA processes were non-normal (P < 0.005). Compared to the non-normal-based SPC and PCA methods, the false alarm rates of the conventional method for linac1, linac2, and linac3 were 0.83%, 3.77%, and 4.95% respectively; the minimum overestimated C pk values were 0.59, 0.87, and 1.49, respectively. The process capabilities of the three beam-matched linacs were at different levels. CONCLUSION: For non-normal VMAT PSQA processes, the conventional SPC and PCA methods increase the false alarm rates and overestimate process capabilities. Instead, non-normal-based SPC and PCA methods are more reliable and accurate in non-normal PSQA processes. Statistical process control and PCA are useful tools for assessing the performance of beam-matched linacs.
PURPOSE: Applying statistical process control (SPC) to intensity-modulated radiotherapy (IMRT)/volumetric modulated arc therapy (VMAT) patient-specific quality assurance (PSQA) program was recommended by the American Association of Physics in Medicine Task Group 218 report, but a comprehensive analysis of PSQA processes with non-normal distributions is lacking. This study investigates SPC and process capability analysis (PCA) methods for non-normal IMRT/VMAT PSQA processes. METHODS: 1119 VMAT PSQAs were performed on three beam-matched linear accelerators (linacs), using gamma analysis. The Anderson-Darling statistic was used to test normality. The control charts for each PSQA process were obtained using three non-normal-based methods and compared with the conventional Shewhart method. The ability of each PSQA process to produce an output within the specification limit was measured using the C pk index; in this study, the C pk index was calculated using two transformation methods and compared with that calculated using the conventional method. The performances of the three linacs were assessed using SPC and PCA methods. RESULTS: All three PSQA processes were non-normal (P < 0.005). Compared to the non-normal-based SPC and PCA methods, the false alarm rates of the conventional method for linac1, linac2, and linac3 were 0.83%, 3.77%, and 4.95% respectively; the minimum overestimated C pk values were 0.59, 0.87, and 1.49, respectively. The process capabilities of the three beam-matched linacs were at different levels. CONCLUSION: For non-normal VMAT PSQA processes, the conventional SPC and PCA methods increase the false alarm rates and overestimate process capabilities. Instead, non-normal-based SPC and PCA methods are more reliable and accurate in non-normal PSQA processes. Statistical process control and PCA are useful tools for assessing the performance of beam-matched linacs.