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Dual-energy computed tomography in stroke imaging: technical and clinical considerations of virtual noncontrast images for detection of the hyperdense artery sign


Winklhofer, Sebastian; Vittoria de Martini, Ilaria; Nern, Chrisitian; Blume, Iris; Wegener, Susanne; Pangalu, Athina; Valavanis, Antonios; Alkadhi, Hatem; Guggenberger, Roman (2017). Dual-energy computed tomography in stroke imaging: technical and clinical considerations of virtual noncontrast images for detection of the hyperdense artery sign. Journal of Computer Assisted Tomography, 41(6):843-848.

Abstract

OBJECTIVE: The technical feasibility of virtual noncontrast (VNC) images from dual-energy computed tomography (DECT) for the detection of the hyperdense artery sign (HAS) in ischemic stroke patients was investigated.
METHODS: True noncontrast (TNC) scans of 60 patients either with or without HAS (n = 30 each) were investigated. Clot presence and characteristics were assessed on VNC images from DECT angiography and compared with TNC images. Clot characterization included the level of confidence for diagnosing HAS, a qualitative clot burden score, and quantitative attenuation (Hounsfield unit [HU]) measurements.
RESULTS: Sensitivity, specificity, and accuracy of VNC for diagnosing HAS were 97%, 90%, and 93%, respectively. No significant differences were found regarding the diagnostic confidence (P = 0.18) and clot burden score (P = 0.071). No significant HU differences were found among vessels with HAS in VNC (56 ± 7HU) and TNC (57 ± 8HU) (P = 0.691) images.
CONCLUSIONS: Virtual noncontrast images derived from DECT enable an accurate detection and characterization of HAS.

Abstract

OBJECTIVE: The technical feasibility of virtual noncontrast (VNC) images from dual-energy computed tomography (DECT) for the detection of the hyperdense artery sign (HAS) in ischemic stroke patients was investigated.
METHODS: True noncontrast (TNC) scans of 60 patients either with or without HAS (n = 30 each) were investigated. Clot presence and characteristics were assessed on VNC images from DECT angiography and compared with TNC images. Clot characterization included the level of confidence for diagnosing HAS, a qualitative clot burden score, and quantitative attenuation (Hounsfield unit [HU]) measurements.
RESULTS: Sensitivity, specificity, and accuracy of VNC for diagnosing HAS were 97%, 90%, and 93%, respectively. No significant differences were found regarding the diagnostic confidence (P = 0.18) and clot burden score (P = 0.071). No significant HU differences were found among vessels with HAS in VNC (56 ± 7HU) and TNC (57 ± 8HU) (P = 0.691) images.
CONCLUSIONS: Virtual noncontrast images derived from DECT enable an accurate detection and characterization of HAS.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Neurology
04 Faculty of Medicine > University Hospital Zurich > Clinic for Diagnostic and Interventional Radiology
04 Faculty of Medicine > University Hospital Zurich > Clinic for Neuroradiology
Dewey Decimal Classification:610 Medicine & health
Date:13 July 2017
Deposited On:31 Oct 2017 17:02
Last Modified:13 Jul 2018 00:00
Publisher:Lippincott Williams & Wilkins
ISSN:0363-8715
OA Status:Green
Publisher DOI:https://doi.org/10.1097/RCT.0000000000000638
PubMed ID:28708725

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