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E-021 Quantitative Evaluation of Metal Artifact Reduction for Coiled Aneurysms in Cone-Beam CT
  1. D Ruijters1,
  2. P van de Haar1,
  3. G Kaila2,
  4. T Grünhagen1,
  5. J Moret3,
  6. L Spelle3
  1. 1Philips Healthcare, Best, Netherlands
  2. 2Trinity College Dublin, Dublin, Ireland
  3. 3Neuroradiologie interventionnelle, Hôpital Bicêtre, Hôpitaux universitaires Paris-Sud, Paris, France

Abstract

Purpose During minimally invasive embolization of brain aneurysms the aneurysm sac is filled with metal coils. The post-coiling cone-beam CT image quality is impaired by artifacts originating from the radiopaque metal mass. The artifact streaks run through the brain parenchyma, which hampers their inspection for hemorrhages and other events. Metal artifact reduction improves the image quality of cone-beam CT affected by streak artifacts. While several metal artifact reduction schemes have been described in the literature, there is little objective quantitative evaluation on clinical data. In this article we use pre- and post-coiling cone-beam CT data, and apply a metric (peak signal-to-noise ratio) to quantify the improvement in image quality.

Materials and methods For 22 retrospective aneurysm coiling cases, cone-beam CT acquisitions prior and post embolization were available. The former dataset was used as gold standard reference to evaluate the latter without and with metal artifact reduction. To this purpose the pre- and post-coiling datasets were co-registered, and the brain cavity and coiling mass were segmented. The metric was then applied to the non-coiled brain parenchyma.

Results The mean squared error improved for 20 out of 22 patients after metal artifact reduction was applied. The average mean squared error was reduced by 264 HU. The peak signal-to-noise ratio was improved by 6.8 dB. The average additional computation time for the metal artifact reduction algorithm amounted 20 seconds.

Conclusion Metal artifact reduction has been found to objectively improve the image quality quantified by the peak signal-to-noise ratio for most patients. It is therefore considered a useful tool for interventional use when the image contains metal parts.

Disclosures D. Ruijters: 5; C; Philips Healthcare. P. van de Haar: 5; C; Philips Healthcare. G. Kaila: None. T. Grünhagen: 5; C; Philips Healthcare. J. Moret: None. L. Spelle: None.

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work noncommercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

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