Metal artefact reduction in low-dose computed tomography: Benefits of tin prefiltration versus postprocessing of dual-energy datasets over conventional CT imaging.

Dual-energy Metal artefact reduction Spectral shaping Tin prefiltration Virtual monoenergetic imaging

Journal

Radiography (London, England : 1995)
ISSN: 1532-2831
Titre abrégé: Radiography (Lond)
Pays: Netherlands
ID NLM: 9604102

Informations de publication

Date de publication:
08 2022
Historique:
received: 23 03 2022
revised: 01 05 2022
accepted: 30 05 2022
pubmed: 22 6 2022
medline: 8 7 2022
entrez: 21 6 2022
Statut: ppublish

Résumé

The purpose of this study was to determine the potential for metal artefact reduction in low-dose multidetector CT as these pose a frequent challenge in clinical routine. Investigations focused on whether spectral shaping via tin prefiltration, virtual monoenergetic imaging or virtual blend imaging (VBI) offers superior image quality in comparison with conventional CT imaging. Using a third-generation dual-source CT scanner, two cadaveric specimens with different metal implants (dental, cervical spine, hip, knee) were examined with acquisition protocols matched for radiation dose with regards to tube voltage and current. In order to allow for precise comparison, and due to the relatively short scan lengths, automatic tube current modulation was disabled. Specifically, the following scan protocals were examined: conventional CT protocols (100/120 kVp), tin prefiltration (Sn 100/Sn 150 kVp), VBI and virtual monoenergetic imaging (VME 100/120/150 keV). Mean attenuation and image noise were measured in hyperdense and hypodense artefacts, in artefact-impaired and artefact-free soft tissue. Subjective image quality was rated independently by three radiologists. Objectively, Sn 150 kVp allowed for the best reduction of hyperdense streak artefacts (p < 0.001), while VME 150 keV and Sn 150 kVp protocols facilitated equally good reduction of hypodense artefacts (p = 0.173). Artefact-impaired soft tissue attenuation was lowest in Sn 150 kVp protocols (p ≤ 0.011), whereas all VME showed significantly less image noise compared to conventional or tin-filtered protocols (p ≤ 0.001). Subjective assessment favoured Sn 150 kVp regarding hyperdense streak artefacts and delineation of cortical bone (p ≤ 0.005). The intraclass correlation coefficient was 0.776 (95% confidence interval: 0.712-0.831; p < 0.001) indicating good interrater reliability. In the presence of metal implants in our cadaveric study, tin prefiltration with 150 kVp offers superior artefact reduction for low-dose CT imaging of osseous tissue compared with virtual monoenergetic images of dual-energy datasets. The delineation of cortical boundaries seems to benefit particularly from spectral shaping. Low-dose CT imaging of osseous tissue in combination with tin prefiltration allows for superior metal artefact reduction when compared to virtual monoenergetic images of dual-energy datasets. Employing this technique ought to be considered in daily routine when metal implants are present within the scan volume as findings suggest it allows for radiation dose reduction and facilitates diagnosis relevant to further treatment.

Identifiants

pubmed: 35728278
pii: S1078-8174(22)00069-4
doi: 10.1016/j.radi.2022.05.006
pii:
doi:

Substances chimiques

Metals 0
Tin 7440-31-5

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

690-696

Informations de copyright

Copyright © 2022 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest statement Jan-Peter Grunz was funded by the Interdisciplinary Center of Clinical Research Würzburg, Germany [grant number Z-2/CSP-06] and serves as a research consultant for Siemens Healthcare GmbH. The Department of Diagnostic and Interventional Radiology received a Siemens research grant. The other authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Auteurs

H Huflage (H)

Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany. Electronic address: Huflage_h@ukw.de.

J-P Grunz (JP)

Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany. Electronic address: Grunz_J@ukw.de.

C Hackenbroch (C)

Department of Diagnostic and Interventional Radiology and Neuroradiology, German Armed Forces Hospital Ulm, Oberer Eselsberg 40, 89081 Ulm, Germany; Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany. Electronic address: CarstenHackenbroch@bundeswehr.org.

D Halt (D)

Department of Diagnostic and Interventional Radiology and Neuroradiology, German Armed Forces Hospital Ulm, Oberer Eselsberg 40, 89081 Ulm, Germany. Electronic address: DanielHalt@bundeswehr.org.

K S Luetkens (KS)

Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany. Electronic address: Luetkens_K@ukw.de.

A M Alfred Schmidt (AM)

Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany. Electronic address: Schmidt_A10@ukw.de.

T S Patzer (TS)

Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany. Electronic address: Patzer_T@ukw.de.

S Ergün (S)

Institute of Anatomy and Cell Biology, University of Würzburg, Koellikerstraße 6, 97070 Würzburg, Germany. Electronic address: Sueleyman.Erguen@uni-wuerzburg.de.

T A Bley (TA)

Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany. Electronic address: Bley_T@ukw.de.

A S Kunz (AS)

Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany. Electronic address: Kunz_A@ukw.de.

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Classifications MeSH