CT Users Group

P Nowik, R Bujila, H Andersson and C Jonsson

Karolinska University Hospital,
Stockholm, Sweden

Abstract

Background: The purpose of Quality Control (QC) in Computed Tomography (CT) is to verify that a CT system delivers expected image quality with acceptable patient doses. International guidelines and national (Swedish) regulations state that QC should be performed at least once annually on all CT systems. The condition of a CT system during the period between annual QC is unknown by medical physicists in terms of measurable quantities because it is not feasible to perform routine QC on a CT more than once a year using conventional methods.

Purpose: The purpose of this work was to analyze the relationships between QC parameters currently obtainable during annual QC of a CT system and to identify key performance indicators. Key performance indicators pertain to measurable or determinable parameters that are influenced by other parameters, where a stable key performance indicator implies that the underlying parameters are stable as well. Furthermore, to develop a method of performing QC on CT systems by automatically monitoring key performance indicators on a daily basis and a method of troubleshooting a CT system when a key performance indicator deviates, in order to systematically locate the cause of the deviation. The aim of this project is to supplement the currently established QC methodology by making it possible to follow a CT scanners condition between annual QC tests.

Material and Methods: A literature study of QC parameters in CT and the relationship between them, obtainable in a manufacturer's QC phantom, was made in order to identify key performance indicators. 2 scan protocols were developed, 1 for the monitoring of key performance indicators and 1 for the systematic localization of deviating underlying parameters when a key performance indicator is out of tolerance. The key performance indicators were verified with phantom studies and the results were compared to theory. An application that can automatically analyze phantom images sent to a DICOM receiver and report the results was developed. A pilot study was commenced where a scan of the manufacturer's QC phantom was made by CT technologists and sent to the developed application on a daily basis. The pilot study remains ongoing.

Results: The key performance indicators include noise, uniformity, CT numbers and positioning. Experimental results show that the key performance indicators compare well with theory and that a deviating underlying parameter can be found systematically. The testing procedure is straightforward and simple and can be made with little effort by CT technologists.

Conclusion: QC of a CT scanner by automatic monitoring of key performance indicators on a daily basis is a powerful tool that can be used to supplement established QC methodologies. Medical physicists, or other concerned parties, are able to obtain an indication of the current and historical (trends) status of a CT system with little effort so that actions can be taken directly to ensure the quality of CT examinations and patient safety.

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