Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Publication Preview--Ahead of Print
    • Past Issue Archive
    • Case of the Week Archive
    • Classic Case Archive
    • Case of the Month Archive
  • For Authors
  • About Us
    • About AJNR
    • Editors
    • American Society of Neuroradiology
  • Submit a Manuscript
  • Podcasts
    • Subscribe on iTunes
    • Subscribe on Stitcher
  • More
    • Subscribers
    • Permissions
    • Advertisers
    • Alerts
    • Feedback
  • Other Publications
    • ajnr

User menu

  • Subscribe
  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

  • Subscribe
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Publication Preview--Ahead of Print
    • Past Issue Archive
    • Case of the Week Archive
    • Classic Case Archive
    • Case of the Month Archive
  • For Authors
  • About Us
    • About AJNR
    • Editors
    • American Society of Neuroradiology
  • Submit a Manuscript
  • Podcasts
    • Subscribe on iTunes
    • Subscribe on Stitcher
  • More
    • Subscribers
    • Permissions
    • Advertisers
    • Alerts
    • Feedback
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds
Research ArticleInterventional

Evaluation of a Metal Artifacts Reduction Algorithm Applied to Postinterventional Flat Panel Detector CT Imaging

D.A. Stidd, H. Theessen, Y. Deng, Y. Li, B. Scholz, C. Rohkohl, M.D. Jhaveri, R. Moftakhar, M. Chen and D.K. Lopes
American Journal of Neuroradiology November 2014, 35 (11) 2164-2169; DOI: https://doi.org/10.3174/ajnr.A4079
D.A. Stidd
aFrom the Departments of Neurosurgery (D.A.S., R.M., M.C., D.K.L.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
H. Theessen
dSiemens Healthcare Sector (B.S., C.R., H.T.), Erlangen, Germany.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Y. Deng
bInternal Medicine (Y.D., Y.L.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Y. Li
bInternal Medicine (Y.D., Y.L.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
B. Scholz
dSiemens Healthcare Sector (B.S., C.R., H.T.), Erlangen, Germany.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
C. Rohkohl
dSiemens Healthcare Sector (B.S., C.R., H.T.), Erlangen, Germany.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
M.D. Jhaveri
cRadiology (M.D.J.), Rush University Medical Center, Chicago, Illinois
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
R. Moftakhar
aFrom the Departments of Neurosurgery (D.A.S., R.M., M.C., D.K.L.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
M. Chen
aFrom the Departments of Neurosurgery (D.A.S., R.M., M.C., D.K.L.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
D.K. Lopes
aFrom the Departments of Neurosurgery (D.A.S., R.M., M.C., D.K.L.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • References
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Fig 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 1.

    A graphic depiction of the metal artifacts prototype algorithm used for the flat panel detector CT images. An initial volume is reconstructed from the raw data containing metal artifacts. The metallic implant is then segmented, creating a binary volume of the implant, which is forward-projected onto the first reconstruction to identify data corrupted by artifacts. The corrupted data are replaced by a nonlinear interpolation procedure by using the data along the metal region boundaries (depicted in green). A new MAR-corrected volume is reconstructed. The segmented metallic implant is overlaid back onto the dataset for the final reconstruction.

  • Fig 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 2.

    A, A phantom aneurysm model constructed of silicone elastomer tubing used to test the MAR algorithm prototype. Platinum coils were deployed in the aneurysm, and a small piece of polyurethane was placed inside a stent deployed across the aneurysm neck to model a clot. B and C, Uncorrected FDCT images acquired of the model constructed with stent, coils, and the simulated clot show streak artifacts created by the metal alloys of the stent and coils. D and E, Corresponding MAR-corrected FDCT images show reduced artifacts.

  • Fig 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 3.

    Flat panel detector CT uncorrected (A–D) and corresponding MAR-corrected (E–H) images depicting reduction of streak artifacts caused by coils deployed to treat intracranial aneurysms. The images were independently scored for the amount of metal artifacts and the number of visualized vessel segments within a 3-cm radius surrounding the metal objects.

  • Fig 4.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 4.

    Sample FDCT images of various metallic objects causing streak artifacts and the application of the MAR algorithm. A and E, Onyx embolization of an intracranial AVM. The MAR algorithm was less effective at reducing the artifacts caused by Onyx. B and F, A bullet lodged within the cervical spine. C and G, A vascular clip used to treat an intracranial aneurysm. D and H, Stent-assisted coil embolization of an intracranial aneurysm. This example is similar to the phantom model created to evaluate the MAR algorithm. The stent is completely obscured by the metal artifacts but is visible after the application of the MAR algorithm.

  • Fig 5.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 5.

    Relative frequencies of metal artifacts scores assigned to FDCT scans for areas immediately adjacent to the implanted metal object (A) or 3 cm away from the implanted metal object (B). The median P value for the uncorrected and MAR-corrected image pairs adjacent to the metal object was P = .05, and the median P value for the image pairs 3 cm away was P = .03. The uncorrected and MAR-corrected images were independently evaluated by 7 clinicians on a 3-point scale (n = 59).

  • Fig 6.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 6.

    The mean number of visualized vessel segments within a 30-cm radius of the implanted metal object before and after MAR correction. The images were independently evaluated by 7 clinicians. The error bars represent the standard error of the mean (n = 25).

Tables

  • Figures
    • View popup
    Table 1:

    Datasets included for MAR evaluation

    Metal ObjectsNo. of Datasets
    Coils only19
    Clips10
    Stent3
    Onyx3
    Stent and coils21
    Other (bullet, spinal screws, mandibular fixtures)3
    • View popup
    Table 2:

    Score used to quantify the amount of metal artifacts

    ScoreDefinition
    0No metal artifacts; relevant surrounding anatomy well-visualized
    1Moderate metal artifacts; relevant anatomy visible but affected by artifacts
    2Severe artifacts; relevant anatomy not visible
PreviousNext
Back to top

In this issue

American Journal of Neuroradiology: 35 (11)
American Journal of Neuroradiology
Vol. 35, Issue 11
1 Nov 2014
  • Table of Contents
  • Index by author
  • Complete Issue (PDF)
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Evaluation of a Metal Artifacts Reduction Algorithm Applied to Postinterventional Flat Panel Detector CT Imaging
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Evaluation of a Metal Artifacts Reduction Algorithm Applied to Postinterventional Flat Panel Detector CT Imaging
D.A. Stidd, H. Theessen, Y. Deng, Y. Li, B. Scholz, C. Rohkohl, M.D. Jhaveri, R. Moftakhar, M. Chen, D.K. Lopes
American Journal of Neuroradiology Nov 2014, 35 (11) 2164-2169; DOI: 10.3174/ajnr.A4079

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Evaluation of a Metal Artifacts Reduction Algorithm Applied to Postinterventional Flat Panel Detector CT Imaging
D.A. Stidd, H. Theessen, Y. Deng, Y. Li, B. Scholz, C. Rohkohl, M.D. Jhaveri, R. Moftakhar, M. Chen, D.K. Lopes
American Journal of Neuroradiology Nov 2014, 35 (11) 2164-2169; DOI: 10.3174/ajnr.A4079
del.icio.us logo Digg logo Reddit logo Twitter logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Purchase

Jump to section

  • Article
    • Abstract
    • ABBREVIATIONS:
    • Materials and Methods
    • Results
    • Discussion
    • Conclusions
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • References
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • The impact of software-based metal artifact reduction on the liquid embolic agent Onyx in cone-beam CT: a systematic in vitro and in vivo study
  • Clinical Impact of Flat Panel Volume CT Angiography in Evaluating the Accurate Intraoperative Deployment of Flow-Diverter Stents
  • Separating the wheat from the chaff: region of interest combined with metal artifact reduction for completion angiography following cerebral aneurysm treatment
  • Metal artifact reduction for flat panel detector intravenous CT angiography in patients with intracranial metallic implants after endovascular and surgical treatment
  • High-Resolution C-Arm CT and Metal Artifact Reduction Software: A Novel Imaging Modality for Analyzing Aneurysms Treated with Stent-Assisted Coil Embolization
  • Crossref
  • Google Scholar

This article has not yet been cited by articles in journals that are participating in Crossref Cited-by Linking.

More in this TOC Section

  • Treatment of Proximal Posterior Inferior Cerebellar Artery Aneurysms by Intrasaccular Flow Disruption: A Multicenter Experience
  • Emergency Department Visits for Chronic Subdural Hematomas within 30 Days after Surgical Evacuation with and without Middle Meningeal Artery Embolization
  • Effect of the Shelving Technique on the Outcome of Embolization in Intracranial Bifurcation Aneurysms
Show more Interventional

Similar Articles

Advertisement

News and Updates

  • Lucien Levy Best Research Article Award
  • Thanks to our 2021 Distinguished Reviewers
  • Press Releases

Resources

  • Evidence-Based Medicine Level Guide
  • How to Participate in a Tweet Chat
  • AJNR Podcast Archive
  • Ideas for Publicizing Your Research
  • Librarian Resources
  • Terms and Conditions

Opportunities

  • Share Your Art in Perspectives
  • Get Peer Review Credit from Publons
  • Moderate a Tweet Chat

American Society of Neuroradiology

  • Neurographics
  • ASNR Annual Meeting
  • Fellowship Portal
  • Position Statements

© 2022 by the American Society of Neuroradiology | Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire