Visual grading evaluation of commercially available metal artefact reduction techniques in hip prosthesis computed tomography

Research output: Contribution to journalArticle


Objective: To evaluate metal artefact reduction (MAR) techniques from four CT vendors in hip prosthesis imaging. Methods: Bilateral hip prosthesis phantom images, obtained by using MAR algorithms for single-energy CT data or dual-energy CT (DECT) data and by monoenergetic reconstructions of DECT data, were visually graded by five radiologists using 10 image quality criteria. Comparisons between the MAR images and a reference image were performed for each scanner separately. Ordinal probit regression analysis was used. Results: The MAR algorithms in general improved the image quality based on the majority of the criteria (up to between 8/10 and 10/10) with a statistical improvement in overall image quality (p<0.001). However, degradation of image quality, such as new artefacts, was seen in some cases. A few monoenergetic reconstruction series improved the image quality (p<0.004) for one of the DECT scanners, but it was only improved for some of the criteria (up to 5/10). Monoenergetic reconstructions resulted in worse image quality for the majority of the criteria (up to 7/10) for the other DECT scanner. Conclusion: The MAR algorithms improved the image quality of the hip prosthesis CT images. However, since additional artefacts and degradation of image quality were seen in some cases, all algorithms should be carefully evaluated for every clinical situation. Monoenergetic reconstructions were in general concluded to be insufficient for reducing metal artefacts. Advances in knowledge: Qualitative evaluation of the usefulness of several MAR techniques from different vendors in CT imaging of hip prosthesis.


  • Karin M. Andersson
  • Eva Norrman
  • Håkan Geijer
  • Wolfgang Krauss
  • Yang Cao
  • Johan Jendeberg
  • Mats Geijer
  • Mats Lidén
  • Per Thunberg
External organisations
  • Örebro University
  • Karolinska Institutet
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Radiology, Nuclear Medicine and Medical Imaging
Original languageEnglish
Article number20150993
JournalBritish Journal of Radiology
Issue number1063
Publication statusPublished - 2016
Publication categoryResearch