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European Radiology

, Volume 23, Issue 8, pp 2137–2145 | Cite as

Frequency split metal artefact reduction in pelvic computed tomography

  • M. M. Lell
  • E. Meyer
  • M. Schmid
  • R. Raupach
  • M. S. May
  • M. Uder
  • M. Kachelriess
Computed Tomography

Abstract

Objectives

Artefacts from total hip replacement affect image quality and the visualisation of pelvic lesions on computed tomography (CT). We propose a frequency split (FS) approach in addition to the normalised metal artefact reduction (NMAR) algorithm that aims to suppress artefacts and improves image quality in patients with orthopaedic hardware.

Methods

Data from ten consecutive patients with metal artefacts from uni- (n = 5) and bilateral (n = 4) total hip replacement or osteosynthesis (n = 1) were reconstructed with filtered back projection (FBP), linear interpolation MAR (LIMAR), NMAR, FSLIMAR and FSNMAR and analysed for image quality and severity of artefacts.

Results

NMAR and FSNMAR significantly improved the assessment of the pelvic organs, lymph nodes and vessels compared with FBP, LIMAR or FSLIMAR (P < 0.05). Assessment of the metal hardware, joint and capsule was improved with the addition of FS (FSLIMAR, FSNMAR). No algorithm-related artefacts were detected in regions that did not contain metal.

Conclusions

NMAR, FSLIMAR and FSNMAR have the potential to improve image quality in patients with artefacts from metal hardware and to improve the diagnostic accuracy of CT of the organs of the pelvis. Although introducing some algorithm-related artefacts, FSNMAR most accurately displayed adjacent bone and tissue next to metal implants.

Key Points

Orthopaedic metallic hardware often creates serious artefacts in computed tomography, hindering diagnosis.

The normalised metal artefact reduction (NMAR) algorithm was developed to suppress such artefacts.

NMAR improves CT assessment of pelvic organs in patients with orthopaedic hardware.

Addition of the frequency split technique (FSNMAR) helps assess tissue near metal hardware.

NMAR and FSNMAR are robust and computationally effective sinogram interpolation algorithms.

Keywords

Computed tomography Metal artefact reduction Total hip replacement Sinogram interpolation Frequency split 

Notes

Acknowledgments

The first two authors contributed equally in this study.

References

  1. 1.
    Greess H, Wolf H, Baum U et al (2000) Dose reduction in computed tomography by attenuation-based on-line modulation of tube current: evaluation of six anatomical regions. Eur Radiol 10:391–394PubMedCrossRefGoogle Scholar
  2. 2.
    Kachelriess M, Watzke O, Kalender WA (2001) Generalized multi-dimensional adaptive filtering for conventional and spiral single-slice, multi-slice, and cone-beam CT. Med Phys 28:475–490PubMedCrossRefGoogle Scholar
  3. 3.
    Kalender WA, Buchenau S, Deak P et al (2008) Technical approaches to the optimisation of CT. Phys Med 24:71–79PubMedCrossRefGoogle Scholar
  4. 4.
    Glover GH, Pelc NJ (1981) An algorithm for the reduction of metal clip artifacts in CT reconstructions. Med Phys 8:799–807PubMedCrossRefGoogle Scholar
  5. 5.
    Kalender WA, Hebel R, Ebersberger J (1987) Reduction of CT artifacts caused by metallic implants. Radiology 164:576–577PubMedGoogle Scholar
  6. 6.
    Mahnken AH, Raupach R, Wildberger JE et al (2003) A new algorithm for metal artifact reduction in computed tomography: in vitro and in vivo evaluation after total hip replacement. Invest Radiol 38:769–775PubMedCrossRefGoogle Scholar
  7. 7.
    Veldkamp WJ, Joemai RM, van der Molen AJ, Geleijns J (2010) Development and validation of segmentation and interpolation techniques in sinograms for metal artifact suppression in CT. Med Phys 37:620–628PubMedCrossRefGoogle Scholar
  8. 8.
    Yu L, Li H, Mueller J et al (2009) Metal artifact reduction from reformatted projections for hip prostheses in multislice helical computed tomography: techniques and initial clinical results. Invest Radiol 44:691–696PubMedCrossRefGoogle Scholar
  9. 9.
    Meyer E, Raupach R, Lell M, Schmidt B, Kachelriess M (2010) Normalized metal artifact reduction (NMAR) in computed tomography. Med Phys 37:5482–5493PubMedCrossRefGoogle Scholar
  10. 10.
    Lell MM, Meyer E, Kuefner MA et al (2012) Normalized metal artifact reduction in head and neck computed tomography. Invest Radiol 47:415–421PubMedCrossRefGoogle Scholar
  11. 11.
    Meyer E, Raupach R, Lell M, Schmidt B, Kachelriess M (2012) Frequency split metal artifact reduction (FSMAR) in computed tomography. Med Phys 39:1904–1916PubMedCrossRefGoogle Scholar
  12. 12.
    Abdoli M, Ay MR, Ahmadian A, Dierckx RA, Zaidi H (2010) Reduction of dental filling metallic artifacts in CT-based attenuation correction of PET data using weighted virtual sinograms optimized by a genetic algorithm. Med Phys 37:6166–6177PubMedCrossRefGoogle Scholar
  13. 13.
    Kennedy JA, Israel O, Frenkel A, Bar-Shalom R, Azhari H (2007) The reduction of artifacts due to metal hip implants in CT-attenuation corrected PET images from hybrid PET/CT scanners. Med Biol Eng Comput 45:553–562PubMedCrossRefGoogle Scholar
  14. 14.
    Lee MJ, Kim S, Lee SA et al (2007) Overcoming artifacts from metallic orthopedic implants at high-field-strength MR imaging and multi-detector CT. Radiographics 27:791–803PubMedCrossRefGoogle Scholar
  15. 15.
    Bamberg F, Dierks A, Nikolaou K, Reiser MF, Becker CR, Johnson TR (2011) Metal artifact reduction by dual energy computed tomography using monoenergetic extrapolation. Eur Radiol 21:1424–1429PubMedCrossRefGoogle Scholar
  16. 16.
    Zhou C, Zhao YE, Luo S et al (2011) Monoenergetic imaging of dual-energy CT reduces artifacts from implanted metal orthopedic devices in patients with factures. Acad Radiol 18:1252–1257PubMedCrossRefGoogle Scholar
  17. 17.
    Lee YH, Park KK, Song HT, Kim S, Suh JS (2012) Metal artefact reduction in gemstone spectral imaging dual-energy CT with and without metal artefact reduction software. Eur Radiol 22:1331–1340PubMedCrossRefGoogle Scholar
  18. 18.
    Prell D, Kyriakou Y, Kachelriess M, Kalender WA (2010) Reducing metal artifacts in computed tomography caused by hip endoprostheses using a physics-based approach. Invest Radiol 45:747–754PubMedCrossRefGoogle Scholar
  19. 19.
    De Man B, Nuyts J, Dupont P, Marchal G, Suetens P (2001) An iterative maximum-likelihood polychromatic algorithm for CT. IEEE Trans Med Imaging 20:999–1008PubMedCrossRefGoogle Scholar
  20. 20.
    Lemmens C, Faul D, Nuyts J (2009) Suppression of metal artifacts in CT using a reconstruction procedure that combines MAP and projection completion. IEEE Trans Med Imaging 28:250–260PubMedCrossRefGoogle Scholar
  21. 21.
    Wang G, Frei T, Vannier MW (2000) Fast iterative algorithm for metal artifact reduction in X-ray CT. Acad Radiol 7:607–614PubMedCrossRefGoogle Scholar
  22. 22.
    Wang G, Snyder DL, O’Sullivan JA, Vannier MW (1996) Iterative deblurring for CT metal artifact reduction. IEEE Trans Med Imaging 15:657–664PubMedCrossRefGoogle Scholar
  23. 23.
    Wang G, Vannier MW, Cheng PC (1999) Iterative X-ray cone-beam tomography for metal artifact reduction and local region reconstruction. Microsc Microanal 5:58–65PubMedCrossRefGoogle Scholar
  24. 24.
    Zhang X, Wang J, Xing L (2011) Metal artifact reduction in X-ray computed tomography (CT) by constrained optimization. Med Phys 38:701–711PubMedCrossRefGoogle Scholar
  25. 25.
    Aootaphao S, Pintavirooj C, Sotthivirat S (2008) Penalized-likelihood reconstruction for metal artifact reduction in cone-beam CT. Conf Proc IEEE Eng Med Biol Soc 2008:2733–2736PubMedGoogle Scholar
  26. 26.
    Buzug T, Oehler M (2007) Statistical image reconstruction for inconsistent CT projection data. Methods Inf Med 46:261–269PubMedGoogle Scholar
  27. 27.
    Naranjo V, Llorens R, Alcaniz M, Lopez-Mir F (2011) Metal artifact reduction in dental CT images using polar mathematical morphology. Comput Methods Programs Biomed 102:64–74PubMedCrossRefGoogle Scholar
  28. 28.
    Rinkel J, Dillon WP, Funk T, Gould R, Prevrhal S (2008) Computed tomographic metal artifact reduction for the detection and quantitation of small features near large metallic implants: a comparison of published methods. J Comput Assist Tomogr 32:621–629PubMedCrossRefGoogle Scholar
  29. 29.
    Watzke O, Kalender WA (2004) A pragmatic approach to metal artifact reduction in CT: merging of metal artifact reduced images. Eur Radiol 14:849–856PubMedCrossRefGoogle Scholar
  30. 30.
    Liu PT, Pavlicek WP, Peter MB, Spangehl MJ, Roberts CC, Paden RG (2009) Metal artifact reduction image reconstruction algorithm for CT of implanted metal orthopedic devices: a work in progress. Skeletal Radiol 38:797–802PubMedCrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2013

Authors and Affiliations

  • M. M. Lell
    • 1
    • 2
  • E. Meyer
    • 3
    • 4
  • M. Schmid
    • 5
  • R. Raupach
    • 4
  • M. S. May
    • 1
  • M. Uder
    • 1
    • 2
  • M. Kachelriess
    • 3
    • 6
  1. 1.Department of RadiologyUniversity of ErlangenErlangenGermany
  2. 2.Imaging Science Institute (ISI)University of ErlangenErlangenGermany
  3. 3.Institute of Medical PhysicsUniversity of ErlangenErlangenGermany
  4. 4.Siemens HealthcareForchheimGermany
  5. 5.Department of Medical Informatics, Biometry and EpidemiologyUniversity of ErlangenErlangenGermany
  6. 6.German Cancer Research Center (DKFZ)HeidelbergGermany

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