Departmental action limits for TQA energy variations defined by means of statistical process control methods.

Clicks: 325
ID: 41937
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #6 of 8 articles by views in australasian physical & engineering sciences in medicine

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
The purpose of this study is to define departmental action limits for energy percentage variation measured by means of step-wedge helical Tomotherapy quality assurance module. Individual charts using the Statistical Process Control techniques have been used to identify retrospectively out-of-control situations ascribable to documented actions performed on the Tomotherapy system. Using the in-control data of our analysis process capability indices (c, c, c and c) are calculated in order to document the real working condition of the Tomotherapy system. Our findings indicate use of an action limit of 1.0% for energy percentage variation difference between the measured and reference output is a good working condition of a Tomotherapy system. c and c indices are suggested as good indices that correctly report the system capability. A method for calculating and reporting Tomotherapy action limits for the integrated self-checking TQA energy check was shown in this study. SPC technique has proven to be efficient in defining departmental action limits from retrospective data for TQA energy measurements, hence optimally enabling corrective improvements in the process of quality assurance.
Reference Key
binny2019departmentalaustralasian Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Binny, Diana;Mezzenga, Emilio;Sarnelli, Anna;Kairn, Tanya;Crowe, Scott B;Trapp, Jamie V;
Journal australasian physical & engineering sciences in medicine
Year 2019
DOI
10.1007/s13246-019-00791-0
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.