Skip to main content

Advertisement

SpringerLink
Log in

Metal artifacts in patients with large dental implants and bridges: combination of metal artifact reduction algorithms and virtual monoenergetic images provides an approach to handle even strongest artifacts

  • Computed Tomography
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

This study compares reduction of strong metal artifacts from large dental implants/bridges using spectral detector CT-derived virtual monoenergetic images (VMI), metal artifact reduction algorithms/reconstructions (MAR), and a combination of both methods (VMIMAR) to conventional CT images (CI).

Methods

Forty-one spectral detector CT (SDCT) datasets of patients that obtained additional MAR reconstructions due to strongest artifacts from large oral implants were included. CI, VMI, MAR, and VMIMAR ranging from 70 to 200 keV (10 keV increment) were reconstructed. Objective image analyses were performed ROI-based by measurement of attenuation (HU) and standard deviation in most pronounced hypo-/hyperdense artifacts as well as artifact impaired soft tissue (mouth floor/soft palate). Extent of artifact reduction, diagnostic assessment of soft tissue, and appearance of new artifacts were rated visually by two radiologists.

Results

The hypo-/hyperattenuating artifacts showed an increase and decrease of HU values in MAR and VMIMAR (CI/MAR/VMIMAR-200keV: − 369.8 ± 239.6/− 37.3 ± 109.6/− 46.2 ± 71.0 HU, p < 0.001 and 274.8 ± 170.2/51.3 ± 150.8/36.6 ± 56.0, p < 0.001, respectively). Higher keV values in hyperdense artifacts allowed for additional artifact reduction; however, this trend was not significant. Artifacts in soft tissue were reduced significantly by MAR and VMIMAR. Visually, high-keV VMI, MAR, and VMIMAR reduced artifacts and improved diagnostic assessment of soft tissue. Overcorrection/new artifacts were reported that mostly did not hamper diagnostic assessment. Overall interrater agreement was excellent (ICC = 0.85).

Conclusions

In the presence of strong artifacts due to large oral implants, MAR is a powerful mean for artifact reduction. For hyperdense artifacts, MAR should be supplemented by VMI ranging from 140 to 200 keV. This combination yields optimal artifact reduction and improves the diagnostic image assessment in imaging of the head and neck.

Key Points

• Large oral implants can cause strong artifacts.

• MAR is a powerful tool for artifact reduction considering such strong artifacts.

• Hyperdense artifact reduction is supplemented by VMI of 140–200 keV from SDCT.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

CI:

Conventional images

MAR:

Metal artifact reduction algorithm

SD:

Standard deviation

SDCT:

Spectral detector CT

VMI:

Virtual monoenergetic images

VMIMAR :

Combination of virtual monoenergetic images and metal artifact reduction algorithms

References

  1. Fayad LM, Patra A, Fishman EK (2009) Value of 3D CT in defining skeletal complications of orthopedic hardware in the postoperative patient. AJR Am J Roentgenol 193:1155–1163

    Article  PubMed  Google Scholar 

  2. 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 27:791–803

    Article  PubMed  Google Scholar 

  3. Mori I, Machida Y, Osanai M, Iinuma K (2013) Photon starvation artifacts of X-ray CT: their true cause and a solution. Radiol Phys Technol 6:130–141

    Article  PubMed  Google Scholar 

  4. Boas FE, Fleischmann D (2012) CT artifacts: causes and reduction techniques. Imaging Med 4:229–240

    Article  Google Scholar 

  5. Kidoh M, Nakaura T, Nakamura S et al (2014) Reduction of dental metallic artefacts in CT: value of a newly developed algorithm for metal artefact reduction (O-MAR). Clin Radiol 69:e11–e16

    Article  CAS  PubMed  Google Scholar 

  6. Philips CT Clinical Science (2012) Metal Artifact Reduction for Orthopedic Implants (O-MAR) [Philips NetForum Community]. Jan 8, 2012. Available at: http://clinical.netforum.healthcare.philips.com/us_en/Explore/White-Papers/CT/Metal-Artifact-Reduction-for-Orthopedic-Implants-(O-MAR). Accessed 1 Jul 2017

  7. Große Hokamp N, Hellerbach A, Gierich A et al (2018) Reduction of artifacts caused by deep brain stimulating electrodes in cranial computed tomography imaging by means of virtual monoenergetic images, metal artifact reduction algorithms, and their combination. Invest Radiol 53:421–431

  8. Huang JY, Kerns JR, Nute JL et al (2015) An evaluation of three commercially available metal artifact reduction methods for CT imaging. Phys Med Biol 60:1047–1067

    Article  PubMed  PubMed Central  Google Scholar 

  9. Laukamp KR, Lennartz S, Neuhaus VF et al (2018) CT metal artifacts in patients with total hip replacements: for artifact reduction monoenergetic reconstructions and post-processing algorithms are both efficient but not similar. Eur Radiol 28(11)4524–4533

  10. Boomsma MF, Warringa N, Edens MA et al (2016) Quantitative analysis of orthopedic metal artefact reduction in 64-slice computed tomography scans in large head metal-on-metal total hip replacement, a phantom study. Springerplus 5:405

    Article  PubMed  PubMed Central  Google Scholar 

  11. Bolstad K, Flatabø S, Aadnevik D, Dalehaug I, Vetti N (2018) Metal artifact reduction in CT, a phantom study: subjective and objective evaluation of four commercial metal artifact reduction algorithms when used on three different orthopedic metal implants. Acta Radiol 59(9):1110–1118

  12. Große Hokamp N, Neuhaus V, Abdullayev N et al (2017) Reduction of artifacts caused by orthopedic hardware in the spine in spectral detector CT examinations using virtual monoenergetic image reconstructions and metal-artifact-reduction algorithms. Skeletal Radiol 47(2):195–201

  13. Flohr TG, McCollough CH, Bruder H et al (2006) First performance evaluation of a dual-source CT (DSCT) system. Eur Radiol 16:256–268

    Article  PubMed  Google Scholar 

  14. Lewis M, Reid K, Toms AP (2013) Reducing the effects of metal artefact using high keV monoenergetic reconstruction of dual energy CT (DECT) in hip replacements. Skelet Radiol 42:275–282

    Article  Google Scholar 

  15. Wellenberg RH, Boomsma MF, van Osch JA et al (2017) Quantifying metal artefact reduction using virtual monochromatic dual-layer detector spectral CT imaging in unilateral and bilateral total hip prostheses. Eur J Radiol 88:61–70

  16. McCollough CH, Leng S, Yu L, Fletcher JG (2015) Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology 276:637–653

    Article  PubMed  Google Scholar 

  17. Johnson TR (2012) Dual-energy CT: general principles. AJR Am J Roentgenol 199:S3–S8

    Article  PubMed  Google Scholar 

  18. Alvarez RE, Macovski A (1976) Energy-selective reconstructions in X-ray computerized tomography. Phys Med Biol 21:733–744

    Article  CAS  PubMed  Google Scholar 

  19. Silva AC, Morse BG, Hara AK, Paden RG, Hongo N, Pavlicek W (2011) Dual-energy (spectral) CT: applications in abdominal imaging. Radiographics 31:1031–1046

  20. Große Hokamp N, Laukamp KR, Lennartz S et al (2018) Artifact reduction from dental implants using virtual monoenergetic reconstructions from novel spectral detector CT. Eur J Radiol 104:136–142

    Article  PubMed  Google Scholar 

  21. Große Hokamp N, Höink AJ, Doerner J et al (2017) Assessment of arterially hyper-enhancing liver lesions using virtual monoenergetic images from spectral detector CT: phantom and patient experience. Abdom Radiol (NY) 43(8):2066–2074

  22. 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 21:1424–1429

  23. Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20:37–46

    Article  Google Scholar 

  24. Fleiss JL, Cohen J (1973) The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educ Psychol Meas 33:613–619

    Article  Google Scholar 

  25. Willemink MJ, De Jong PA, Leiner T et al (2013) Iterative reconstruction techniques for computed tomography part 1: technical principles. Eur Radiol 23:1623–1631

    Article  PubMed  Google Scholar 

  26. Aissa J, Thomas C, Sawicki LM et al (2017) Iterative metal artefact reduction in CT: can dedicated algorithms improve image quality after spinal instrumentation? Clin Radiol 72:428.e7–428.e12

    Article  CAS  Google Scholar 

  27. Mangold S, Gatidis S, Luz O et al (2014) Single-source dual-energy computed tomography: use of monoenergetic extrapolation for a reduction of metal artifacts. Invest Radiol 49:788–793

    Article  PubMed  Google Scholar 

  28. 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 22:1331–1340

  29. Dong Y, Shi AJ, Wu JL et al (2016) Metal artifact reduction using virtual monochromatic images for patients with pedicle screws implants on CT. Eur Spine J 25:1754–1763

    Article  PubMed  Google Scholar 

  30. Albrecht MH, Trommer J, Wichmann JL et al (2016) Comprehensive comparison of virtual monoenergetic and linearly blended reconstruction techniques in third-generation dual-source dual-energy computed tomography angiography of the thorax and abdomen. Invest Radiol 51:582–590

    Article  CAS  PubMed  Google Scholar 

  31. Guggenberger R, Winklhofer S, Osterhoff G et al (2012) Metallic artefact reduction with monoenergetic dual-energy CT: systematic ex vivo evaluation of posterior spinal fusion implants from various vendors and different spine levels. Eur Radiol 22:2357–2364

  32. Kalisz K, Buethe J, Saboo SS, Abbara S, Halliburton S, Rajiah P (2016) Artifacts at cardiac CT: physics and solutions. Radiographics 36:2064–2083

  33. Kuchenbecker S, Faby S, Sawall S, Lell M, Kachelrieß M (2015) Dual energy CT: how well can pseudo-monochromatic imaging reduce metal artifacts? Med Phys 42:1023–1036

  34. Cha J, Kim HJ, Kim ST, Kim YK, Kim HY, Park GM (2017) Dual-energy CT with virtual monochromatic images and metal artifact reduction software for reducing metallic dental artifacts. Acta Radiol 58:1312–1319

  35. Neuhaus V, Große Hokamp N, Abdullayev N et al (2017) Metal artifact reduction by dual-layer computed tomography using virtual monoenergetic images. Eur J Radiol 93:143–148

    Article  PubMed  Google Scholar 

  36. Bongers MN, Schabel C, Thomas C et al (2015) Comparison and combination of dual-energy- and iterative-based metal artefact reduction on hip prosthesis and dental implants. PLoS One 10:e0143584

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

  1. Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Straße 62, 50937, Cologne, Germany

    Kai Roman Laukamp, David Zopfs, Simon Lennartz, Lenhard Pennig, David Maintz, Jan Borggrefe & Nils Große Hokamp

  2. Department of Radiology, Case Western Reserve University, Cleveland, OH, USA

    Kai Roman Laukamp

  3. Department of Radiology, University Hospitals Medical Center, Cleveland, OH, USA

    Kai Roman Laukamp

Authors
  1. Kai Roman Laukamp
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David Zopfs
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Simon Lennartz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lenhard Pennig
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David Maintz
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jan Borggrefe
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Nils Große Hokamp
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kai Roman Laukamp.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Kai Roman Laukamp.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: David Maintz, Jan Borggrefe, and Nils Große Hokamp received speakers’ honoraria from Philips Healthcare.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• experimental

• performed at one institution

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Laukamp, K.R., Zopfs, D., Lennartz, S. et al. Metal artifacts in patients with large dental implants and bridges: combination of metal artifact reduction algorithms and virtual monoenergetic images provides an approach to handle even strongest artifacts. Eur Radiol 29, 4228–4238 (2019). https://doi.org/10.1007/s00330-018-5928-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-018-5928-7

Keywords

Search

Navigation