BACKGROUND AND PURPOSE: This study aims to investigate the process of monitor unit verification using control charts. Control charts is a key tool within statistical process control (SPC), through which process characteristics can be visualized, usually chronologically with statistically determined limits. MATERIAL AND METHODS: Our group has developed a monitor unit verification software that has been adopted at several Swedish institutions for pre-treatment verification of radiotherapy treatments. Deviations between point dose calculations using the treatment planning systems and using the independent monitor unit verification software from 9219 treatment plans and five different institutions were included in this multicenter study. The process of monitor unit verification was divided into subprocesses. Each subprocess was analyzed using probability plots and control charts. RESULTS: Differences in control chart parameters for the investigated subprocesses were found between different treatment sites and different institutions, as well as between different treatment techniques. 19 of 37 subprocesses met the clinical specification (± 5%), i.e. process capability index was equal to or above one. CONCLUSIONS: Control charts were found to be a useful tool for continuous analysis of data from the monitor unit verification software for patient specific quality control, as well as for comparisons between different institutions and treatment sites. The derived control chart limits were in agreement with AAPM TG114 guidelines on action levels.
BACKGROUND AND PURPOSE: This study aims to investigate the process of monitor unit verification using control charts. Control charts is a key tool within statistical process control (SPC), through which process characteristics can be visualized, usually chronologically with statistically determined limits. MATERIAL AND METHODS: Our group has developed a monitor unit verification software that has been adopted at several Swedish institutions for pre-treatment verification of radiotherapy treatments. Deviations between point dose calculations using the treatment planning systems and using the independent monitor unit verification software from 9219 treatment plans and five different institutions were included in this multicenter study. The process of monitor unit verification was divided into subprocesses. Each subprocess was analyzed using probability plots and control charts. RESULTS: Differences in control chart parameters for the investigated subprocesses were found between different treatment sites and different institutions, as well as between different treatment techniques. 19 of 37 subprocesses met the clinical specification (± 5%), i.e. process capability index was equal to or above one. CONCLUSIONS: Control charts were found to be a useful tool for continuous analysis of data from the monitor unit verification software for patient specific quality control, as well as for comparisons between different institutions and treatment sites. The derived control chart limits were in agreement with AAPM TG114 guidelines on action levels.