Virtual Monochromatic Image Quality from Dual-Layer Dual-Energy Computed Tomography for Detecting Brain Tumors.
Brain neoplasms
Image enhancement
Radiography, Dual-energy scanned projection
Tomography, X-ray computed
Journal
Korean journal of radiology
ISSN: 2005-8330
Titre abrégé: Korean J Radiol
Pays: Korea (South)
ID NLM: 100956096
Informations de publication
Date de publication:
06 2021
06 2021
Historique:
received:
25
05
2020
revised:
13
09
2020
accepted:
08
10
2020
pubmed:
12
2
2021
medline:
29
9
2021
entrez:
11
2
2021
Statut:
ppublish
Résumé
To evaluate the usefulness of virtual monochromatic images (VMIs) obtained using dual-layer dual-energy CT (DL-DECT) for evaluating brain tumors. This retrospective study included 32 patients with brain tumors who had undergone non-contrast head CT using DL-DECT. Among them, 15 had glioblastoma (GBM), 7 had malignant lymphoma, 5 had high-grade glioma other than GBM, 3 had low-grade glioma, and 2 had metastatic tumors. Conventional polychromatic images and VMIs (40-200 keV at 10 keV intervals) were generated. We compared CT attenuation, image noise, contrast, and contrast-to-noise ratio (CNR) between tumor and white matter (WM) or grey matter (GM) between VMIs showing the highest CNR (optimized VMI) and conventional CT images using the paired t test. Two radiologists subjectively assessed the contrast, margin, noise, artifact, and diagnostic confidence of optimized VMIs and conventional images on a 4-point scale. The image noise of VMIs at all energy levels tested was significantly lower than that of conventional CT images ( In head CT for patients with brain tumors, compared with conventional CT images, 40 keV VMIs from DL-DECT yielded superior tumor contrast and diagnostic confidence, especially for brain tumors located in the WM.
Identifiants
pubmed: 33569932
pii: 22.e6
doi: 10.3348/kjr.2020.0677
pmc: PMC8154786
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
951-958Informations de copyright
Copyright © 2021 The Korean Society of Radiology.
Déclaration de conflit d'intérêts
The authors have no potential conflicts of interest to disclose.
Références
Eur J Radiol. 2018 Nov;108:177-183
pubmed: 30396652
J Neurooncol. 2018 Apr;137(2):367-377
pubmed: 29285591
Eur Radiol. 2017 Jul;27(7):2717-2725
pubmed: 27966043
Neuroimaging Clin N Am. 2017 Aug;27(3):429-443
pubmed: 28711203
Eur Radiol. 2018 Apr;28(4):1719-1730
pubmed: 29063254
J Neuroradiol. 2016 Oct;43(5):346-52
pubmed: 27255679
Pediatr Radiol. 2017 Nov;47(12):1648-1658
pubmed: 28656326
J Comput Assist Tomogr. 2016 Mar-Apr;40(2):320-5
pubmed: 26720206
Jpn J Radiol. 2018 Feb;36(2):69-80
pubmed: 29119457
J Comput Assist Tomogr. 2018 Jul/Aug;42(4):648-654
pubmed: 29787496
AJNR Am J Neuroradiol. 2012 May;33(5):865-72
pubmed: 22241388
J Comput Assist Tomogr. 2011 Mar-Apr;35(2):294-7
pubmed: 21412106
Med Phys. 2011 Dec;38(12):6371-9
pubmed: 22149820
J Comput Assist Tomogr. 1980 Aug;4(4):489-91
pubmed: 6771308
Radiology. 2013 Jan;266(1):318-25
pubmed: 23074259
Eur Radiol. 2018 Jul;28(7):2745-2755
pubmed: 29404773
Jpn J Radiol. 2013 Apr;31(4):293-8
pubmed: 23408047
Pediatr Radiol. 2017 May;47(6):710-717
pubmed: 28293707
J Natl Compr Canc Netw. 2014 Nov;12(11):1561-8
pubmed: 25361803
J Neurotrauma. 2019 Apr 15;36(8):1375-1381
pubmed: 30328766
J Clin Imaging Sci. 2016 Jun 29;6:27
pubmed: 27512615
Eur J Radiol. 2011 Nov;80(2):612-9
pubmed: 21376494