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Combining monoenergetic extrapolations from dual-energy CT with iterative reconstructions: reduction of coil and clip artifacts from intracranial aneurysm therapy


Winklhofer, Sebastian; Hinzpeter, Ricarda; Stocker, Daniel; Baltsavias, Gerasimos; Michels, Lars; Burkhardt, Jan-Karl; Regli, Luca; Valavanis, Antonios; Alkadhi, Hatem (2018). Combining monoenergetic extrapolations from dual-energy CT with iterative reconstructions: reduction of coil and clip artifacts from intracranial aneurysm therapy. Neuroradiology, 60(3):281-291.

Abstract

PURPOSE To compare and to combine iterative metal artifact reduction (MAR) and virtual monoenergetic extrapolations (VMEs) from dual-energy computed tomography (DECT) for reducing metal artifacts from intracranial clips and coils. METHODS Fourteen clips and six coils were scanned in a phantom model with DECT at 100 and 150SnkVp. Four datasets were reconstructed: non-corrected images (filtered-back projection), iterative MAR, VME from DECT at 120 keV, and combined iterative MAR + VME images. Artifact severity scores and visibility of simulated, contrast-filled, adjacent vessels were assessed qualitatively and quantitatively by two independent, blinded readers. RESULTS Iterative MAR, VME, and combined iterative MAR + VME resulted in a significant reduction of qualitative (p < 0.001) and quantitative clip artifacts (p < 0.005) and improved the visibility of adjacent vessels (p < 0.05) compared to non-corrected images, with lowest artifact scores found in combined iterative MAR + VME images. Titanium clips demonstrated less artifacts than Phynox clips (p < 0.05), and artifact scores increased with clip size. Coil artifacts increased with coil size but were reducible when applying iterative MAR + VME compared to non-corrected images. However, no technique improved the severe artifacts from large, densely packed coils. CONCLUSIONS Combining iterative MAR with VME allows for an improved metal artifact reduction from clips and smaller, loosely packed coils. Limited value was found for large and densely packed coils.

Abstract

PURPOSE To compare and to combine iterative metal artifact reduction (MAR) and virtual monoenergetic extrapolations (VMEs) from dual-energy computed tomography (DECT) for reducing metal artifacts from intracranial clips and coils. METHODS Fourteen clips and six coils were scanned in a phantom model with DECT at 100 and 150SnkVp. Four datasets were reconstructed: non-corrected images (filtered-back projection), iterative MAR, VME from DECT at 120 keV, and combined iterative MAR + VME images. Artifact severity scores and visibility of simulated, contrast-filled, adjacent vessels were assessed qualitatively and quantitatively by two independent, blinded readers. RESULTS Iterative MAR, VME, and combined iterative MAR + VME resulted in a significant reduction of qualitative (p < 0.001) and quantitative clip artifacts (p < 0.005) and improved the visibility of adjacent vessels (p < 0.05) compared to non-corrected images, with lowest artifact scores found in combined iterative MAR + VME images. Titanium clips demonstrated less artifacts than Phynox clips (p < 0.05), and artifact scores increased with clip size. Coil artifacts increased with coil size but were reducible when applying iterative MAR + VME compared to non-corrected images. However, no technique improved the severe artifacts from large, densely packed coils. CONCLUSIONS Combining iterative MAR with VME allows for an improved metal artifact reduction from clips and smaller, loosely packed coils. Limited value was found for large and densely packed coils.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Diagnostic and Interventional Radiology
04 Faculty of Medicine > University Hospital Zurich > Clinic for Neurosurgery
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:22 January 2018
Deposited On:06 Feb 2018 13:37
Last Modified:29 Jun 2018 06:51
Publisher:Springer
ISSN:0028-3940
OA Status:Closed
Publisher DOI:https://doi.org/10.1007/s00234-018-1981-9
PubMed ID:29356855

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