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Radiotherapy Quality Assurance Using Statistical Process Control

  • Diana BinnyEmail author
  • Craig M. Lancaster
  • Tanya Kairn
  • Jamie V. Trapp
  • Scott B. Crowe
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 68/3)

Abstract

Statistical process control (SPC) is an analytical decision-making tool that employs statistics to measure and monitor a system process. The fundamental concept of SPC is to compare current statistics in a process with its previous corresponding statistic for a given period. Using SPC, a control chart is obtained to identify random and systematic variations based on the mean of the process and trends are observed to see how data can vary in each evaluated period. An upper and lower control limit in an SPC derived control chart indicate the range of the process calculated based on the standard deviations from the mean, thereby points that are outside these limits indicate the process to be out of control. Metrics such as: process capability and acceptability ratios were employed to assess whether an applied tolerance is applicable to the existing process. SPC has been applied in this study to assess and recommend quality assurance tolerances in the radiotherapy practice for helical tomotherapy. Various machine parameters such as beam output, energy, couch travel as well as treatment planning parameters such as minimum percentage of open multileaf collimators (MLC) during treatment, planned pitch (couch travel per gantry rotation) and modulation factor (beam intensity) were verified against their delivery quality assurance tolerances to produce SPC based tolerances. Results obtained were an indication of the current processes and mechanical capabilities in the department rather than a vendor recommended or a prescriptive approach based on machine technicalities. In this study, we have provided a simple yet effective method and analysis results to recommend tolerances for a radiotherapy practice. This can help improve treatment efficiency and reduce inaccuracies in dose delivery using an assessment tool that can identify systematic and random variations in a process and hence avoid potential hazardous outcomes.

Keywords

Radiation therapy Statistical process control Quality assurance Tomotherapy 

Notes

Conflict of Interest

This research did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors have no conflict of interest to declare.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Radiation Oncology CentresRedlandsAustralia
  2. 2.Queensland University of TechnologyBrisbaneAustralia
  3. 3.Cancer Care Services, Royal Brisbane and Women’s HospitalBrisbaneAustralia

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