Kristine Gulliksrud1, Caroline Stokke2, Anne Catrine Trægde Martinsen3. 1. The Intervention Centre, Oslo University Hospital, Rikshospitalet, Oslo, Norway. Electronic address: krgull@ous-hf.no. 2. The Intervention Centre, Oslo University Hospital, Rikshospitalet, Oslo, Norway; Faculty of Health Sciences, Oslo and Akershus University College of Applied Sciences, Oslo, Norway. 3. The Intervention Centre, Oslo University Hospital, Rikshospitalet, Oslo, Norway; Department of Physics, University of Oslo, Oslo, Norway. Electronic address: uxneti@ous-hf.no.
Abstract
PURPOSE: Quality assurance (QA) phantoms for testing different image quality parameters in computed tomography (CT) are commercially available. Such phantoms are also used as reference for acceptance in the specifications of CT-scanners. The aim of this study was to analyze the characteristics of the most commonly used QA phantom in CT: Catphan 500/504/600. METHODS: Nine different phantoms were scanned on the same day, on one CT-scanner with the same parameter settings. Interphantom variations in CT-number values, image uniformity and low contrast resolution were evaluated for the phantoms. Comparisons between manual image analysis and results obtained from the automatic evaluation software QAlite were performed. RESULTS: Some interphantom variations were observed in the low contrast resolution and the CT-number modules of the phantoms. Depending on the chosen regulatory framework, the variations in CT-numbers can be interpreted as substantial. The homogenous modules were found more invariable. However, the automatic image analysis software QAlite measures image uniformity differently than recommended in international standards, and will not necessarily give results in agreement with these standards. CONCLUSIONS: It is important to consider the interphantom variations in relation to ones framework, and to be aware of which phantom is used to study CT-numbers and low contrast resolution for a specific scanner. Comparisons with predicted values from manual and acceptance values should be performed with care and consideration. If automatic software-based evaluations are to be used, users should be aware that large differences can exist for the image uniformity testing.
PURPOSE: Quality assurance (QA) phantoms for testing different image quality parameters in computed tomography (CT) are commercially available. Such phantoms are also used as reference for acceptance in the specifications of CT-scanners. The aim of this study was to analyze the characteristics of the most commonly used QA phantom in CT: Catphan 500/504/600. METHODS: Nine different phantoms were scanned on the same day, on one CT-scanner with the same parameter settings. Interphantom variations in CT-number values, image uniformity and low contrast resolution were evaluated for the phantoms. Comparisons between manual image analysis and results obtained from the automatic evaluation software QAlite were performed. RESULTS: Some interphantom variations were observed in the low contrast resolution and the CT-number modules of the phantoms. Depending on the chosen regulatory framework, the variations in CT-numbers can be interpreted as substantial. The homogenous modules were found more invariable. However, the automatic image analysis software QAlite measures image uniformity differently than recommended in international standards, and will not necessarily give results in agreement with these standards. CONCLUSIONS: It is important to consider the interphantom variations in relation to ones framework, and to be aware of which phantom is used to study CT-numbers and low contrast resolution for a specific scanner. Comparisons with predicted values from manual and acceptance values should be performed with care and consideration. If automatic software-based evaluations are to be used, users should be aware that large differences can exist for the image uniformity testing.
Authors: Simon M F Triphan; Jürgen Biederer; Kerstin Burmester; Iven Fellhauer; Claus F Vogelmeier; Rudolf A Jörres; Hans-Ulrich Kauczor; Claus P Heußel; Mark O Wielpütz; Bertram J Jobst Journal: PLoS One Date: 2018-07-05 Impact factor: 3.240
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