Virtual Noncontrast Images From Portal Venous Phase Spectral-Detector CT Acquisitions for Adrenal Lesion Characterization.
Adenoma
/ diagnostic imaging
Adrenal Gland Neoplasms
/ diagnostic imaging
Adrenal Glands
/ diagnostic imaging
Aged
Aged, 80 and over
Humans
Male
Middle Aged
Radiographic Image Interpretation, Computer-Assisted
/ methods
Retrospective Studies
Sensitivity and Specificity
Tomography, X-Ray Computed
User-Computer Interface
Journal
Journal of computer assisted tomography
ISSN: 1532-3145
Titre abrégé: J Comput Assist Tomogr
Pays: United States
ID NLM: 7703942
Informations de publication
Date de publication:
Historique:
pubmed:
14
3
2020
medline:
29
1
2021
entrez:
14
3
2020
Statut:
ppublish
Résumé
The aim of this study was to investigate if Hounsfield unit (HU) values from virtual noncontrast (VNC) images derived from portal venous phase spectral-detector computed tomography can help to differentiate adrenal adenomas and metastases. Spectral-detector computed tomography datasets of 33 patients with presence of adrenal lesions and standard of reference for lesion origin by follow-up/prior examinations or dedicated magnetic resonance imaging were included. Conventional and VNC images were reconstructed from the same scan. Region of interest-based image analysis was performed in adrenal lesions and contralateral healthy adrenal tissue. The 33 lesions consisted of 23 adenomas and 10 metastases. Hounsfield unit values of all lesions in VNC images were significantly lower compared with conventional images (18.2 ± 12.6 HU vs 59.6 ± 21.7 HU, P < 0.001). Hounsfield unit values in adenomas were significantly lower in VNC images (11.3 ± 6.5 HU vs 34.1 ± 9.1 HU, P < 0.001). Virtual noncontrast HU values differed significantly between adrenal adenomas and metastases and can therefore be used for improved characterization of incidental adrenal lesions and definition of adrenal adenomas.
Identifiants
pubmed: 32168080
pii: 00004728-202101000-00006
doi: 10.1097/RCT.0000000000000982
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
24-28Informations de copyright
Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.
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