%0 Journal Article %T Statistical Process Control in Monitoring Radiotherapy Quality Assurance Program: An Institutional Experience. %J Iranian Journal of Medical Physics %I Mashhad University of Medical Sciences %Z 2345-3672 %A R, Vysakh %A Ganapathi Raman, R %A Niyas, P %A Aflah, P %D 2022 %\ 05/01/2022 %V 19 %N 3 %P 189-198 %! Statistical Process Control in Monitoring Radiotherapy Quality Assurance Program: An Institutional Experience. %K Radiotherapy Quality Assurance Patient %K Specific Quality Assurance Statistical Process Control %R 10.22038/ijmp.2021.55869.1931 %X Introduction: Statistical process control (SPC) is a handy and powerful tool for monitoring quality assurance (QA) programs in radiotherapy. This study explains the institutional experience in monitoring weekly output constancy QA and patient-specific quality assurance (PSQA) using SPC tools.Material and Methods: Prospective monitoring of output constancy has been demonstrated by the simultaneous usage of Shewhart's I-MR charts and time-weighted control charts. PSQA results were retrospectively analysed in a combined γ and dose volume histogram (DVH) based analysis using control charts and process capability indices. A PSQA analysis method has been illustrated in which the site-specific action limits (AL) and control limits (CL) for γ and DVH based analysis were obtained using SPC.               Results: The simultaneous use of different control charts indicated a systematic error in the output constancy of Linac as successive measurement points fell above the CL. The reason for failure was found and process was monitored further. The obtained AL and CL for γ and DVH based analysis were used to decide pass or fail criteria in PSQA. Among the analysed treatment plans, fourteen plans of different treatment sites failed the PSQA analysis. Cause-and-effect analysis of these failed treatment plans in PSQA pointed out six primary potential sources of errors in the results.Conclusion: SPC tools can be adopted among institutions for consistent and comparable QA programs. If the QA process monitored using SPC falls outside the CL, cause-and-effect diagrams can be used to extract all possible contributing factors that lead to such a process state. %U https://ijmp.mums.ac.ir/article_18605_e37f220a9dfffeed8a74f3f0dae0f733.pdf