Statistical process control and process capability analysis for non-normal volumetric modulated arc therapy patient-specific quality assurance processes.

Abstract

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. 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 index; in this study, the 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. 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 values were 0.59, 0.87, and 1.49, respectively. The process capabilities of the three beam-matched linacs were at different levels. 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.