Literature DB >> 25125663

Evaluation of a metal artifacts reduction algorithm applied to postinterventional flat panel detector CT imaging.

D A Stidd1, H Theessen2, Y Deng3, Y Li3, B Scholz2, C Rohkohl2, M D Jhaveri4, R Moftakhar1, M Chen1, D K Lopes5.   

Abstract

BACKGROUND AND
PURPOSE: Flat panel detector CT images are degraded by streak artifacts caused by radiodense implanted materials such as coils or clips. A new metal artifacts reduction prototype algorithm has been used to minimize these artifacts. The application of this new metal artifacts reduction algorithm was evaluated for flat panel detector CT imaging performed in a routine clinical setting.
MATERIALS AND METHODS: Flat panel detector CT images were obtained from 59 patients immediately following cerebral endovascular procedures or as surveillance imaging for cerebral endovascular or surgical procedures previously performed. The images were independently evaluated by 7 physicians for metal artifacts reduction on a 3-point scale at 2 locations: immediately adjacent to the metallic implant and 3 cm away from it. The number of visible vessels before and after metal artifacts reduction correction was also evaluated within a 3-cm radius around the metallic implant.
RESULTS: The metal artifacts reduction algorithm was applied to the 59 flat panel detector CT datasets without complications. The metal artifacts in the reduction-corrected flat panel detector CT images were significantly reduced in the area immediately adjacent to the implanted metal object (P = .05) and in the area 3 cm away from the metal object (P = .03). The average number of visible vessel segments increased from 4.07 to 5.29 (P = .1235) after application of the metal artifacts reduction algorithm to the flat panel detector CT images.
CONCLUSIONS: Metal artifacts reduction is an effective method to improve flat panel detector CT images degraded by metal artifacts. Metal artifacts are significantly decreased by the metal artifacts reduction algorithm, and there was a trend toward increased vessel-segment visualization.
© 2014 by American Journal of Neuroradiology.

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Year:  2014        PMID: 25125663     DOI: 10.3174/ajnr.A4079

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  8 in total

1.  Contrast-enhanced angiographic cone-beam computed tomography without pre-diluted contrast medium.

Authors:  K I Jo; S R Kim; J H Choi; K H Kim; P Jeon
Journal:  Neuroradiology       Date:  2015-08-21       Impact factor: 2.804

2.  Metal artifact reduction algorithm for image quality improvement of cone-beam CT images of medium or large cerebral aneurysms treated with stent-assisted coil embolization.

Authors:  Satoshi Murai; Masafumi Hiramatsu; Yuji Takasugi; Yu Takahashi; Naoya Kidani; Shingo Nishihiro; Yukei Shinji; Jun Haruma; Tomohito Hishikawa; Kenji Sugiu; Isao Date
Journal:  Neuroradiology       Date:  2019-11-07       Impact factor: 2.804

3.  Evaluation of a metal artifact reduction algorithm applied to post-interventional flat detector CT in comparison to pre-treatment CT in patients with acute subarachnoid haemorrhage.

Authors:  Angelika Mennecke; Stanislav Svergun; Bernhard Scholz; Kevin Royalty; Arnd Dörfler; Tobias Struffert
Journal:  Eur Radiol       Date:  2016-04-16       Impact factor: 5.315

4.  Clinical Evaluation of an Innovative Metal-Artifact-Reduction Algorithm in FD-CT Angiography in Cerebral Aneurysms Treated by Endovascular Coiling or Surgical Clipping.

Authors:  Felix Eisenhut; Manuel Alexander Schmidt; Alexander Kalik; Tobias Struffert; Julian Feulner; Sven-Martin Schlaffer; Michael Manhart; Arnd Doerfler; Stefan Lang
Journal:  Diagnostics (Basel)       Date:  2022-05-04

5.  Evaluation of an optimized metal artifact reduction algorithm for flat-detector angiography compared to DSA imaging in follow-up after neurovascular procedures.

Authors:  Nadine Amelung; Volker Maus; Daniel Behme; Ismini E Papageorgiou; Johanna Rosemarie Leyhe; Michael Knauth; Marios Nikos Psychogios
Journal:  BMC Med Imaging       Date:  2019-08-14       Impact factor: 1.930

6.  Efficiency of Iterative Metal Artifact Reduction Algorithm (iMAR) Applied to Brain Volume Perfusion CT in the Follow-up of Patients after Coiling or Clipping of Ruptured Brain Aneurysms.

Authors:  Arsany Hakim; Manuela Pastore-Wapp; Sonja Vulcu; Tomas Dobrocky; Werner J Z'Graggen; Franca Wagner
Journal:  Sci Rep       Date:  2019-12-19       Impact factor: 4.379

7.  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.

Authors:  Niclas Schmitt; Charlotte S Weyland; Lena Wucherpfennig; Christof M Sommer; Martin Bendszus; Markus A Möhlenbruch; Dominik F Vollherbst
Journal:  J Neurointerv Surg       Date:  2021-08-25       Impact factor: 8.572

8.  Metal artifact reduction for flat panel detector intravenous CT angiography in patients with intracranial metallic implants after endovascular and surgical treatment.

Authors:  Rastislav Pjontek; Belgin Önenköprülü; Bernhard Scholz; Yiannis Kyriakou; Gerrit A Schubert; Omid Nikoubashman; Ahmed Othman; Martin Wiesmann; Marc A Brockmann
Journal:  J Neurointerv Surg       Date:  2015-09-07       Impact factor: 5.836

  8 in total

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