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Cerebral Venous Thrombosis: A Challenging Diagnosis; A New Nonenhanced Computed Tomography Standardized Semi-Quantitative Method

Authors :
Andrea Romano
Maria Camilla Rossi-Espagnet
Luca Pasquini
Alberto Di Napoli
Francesco Dellepiane
Giulia Butera
Giulia Moltoni
Olga Gagliardo
Alessandro Bozzao
Source :
Tomography, Vol 8, Iss 1, Pp 1-9 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Cerebral venous sinus thrombosis (CVST) on non-contrast CT (NCCT) is often challenging to detect. We retrospectively selected 41 children and 36 adults with confirmed CVST and two age-matched control groups with comparable initial symptoms. We evaluated NCCT placing four small circular ROIs in standardized regions of the cerebral dural venous system. The mean and maximum HU values were considered from each ROI, and the relative percentage variations were calculated (mean % variation and maximum % variation). We compared the highest measured value to the remaining three HU values through an ad-hoc formula based on the assumption that the thrombosed sinus has higher attenuation compared with the healthy sinuses. Percentage variations were employed to reflect how the attenuation of the thrombosed sinus deviates from the unaffected counterparts. The attenuation of the affected sinus was increased in patients with CVST, and consequently both the mean % and maximum % variations were increased. A mean % variation value of 12.97 and a maximum % variation value of 10.14 were found to be useful to distinguish patients with CVST from healthy subjects, with high sensitivity and specificity. Increased densitometric values were present in the site of venous thrombosis. A systematic, blind evaluation of the brain venous system can assist radiologists in identifying patients who need or do not need further imaging.

Details

Language :
English
ISSN :
2379139X and 23791381
Volume :
8
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Tomography
Publication Type :
Academic Journal
Accession number :
edsdoj.4afefca46c844e090af5ad092c3a15d
Document Type :
article
Full Text :
https://doi.org/10.3390/tomography8010001