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Non-contrast computed tomography in the diagnosis of cerebral venous sinus thrombosis Cover

Non-contrast computed tomography in the diagnosis of cerebral venous sinus thrombosis

Free to read
|Jul 2016

Abstract

Background

The aim of the study was to investigate the sensitivity and specificity of non-contrast computed tomography (NCCT) in the diagnosis of cerebral venous sinus thrombosis (CVST).

Methods. Screening our neurological department database, we identified 53 patients who were admitted to neurological emergency department with clinical signs of CVST. Two independent observers assessed the NCCT scans for the presence of CVST. CT venography and/or MR venography were used as a reference standard. Interobserver agreement between the two readers was assessed using Kappa statistic. Attenuation inside the cerebral venous sinuses was measured and compared between the patient and the control group.

Results

CVST was confirmed in 13 patients. Sensitivity and specificity of NCCT for overall presence of CVST were 100% and 83%, respectively, with Kappa value of 0.72 (a good agreement between observers). The attenuation values between CVST patients and control group were significantly different (73.4 ± 14.12 HU vs. 58.1 ± 7.58 HU; p = 0.000). The ROC analysis showed an area under the curve (AUC) of 0.916 (95% CI, 0.827 – 1.00) and an optimal cutoff value of 64 HU, leading to a sensitivity of 85% and specificity of 87%.

Conclusions

NCCT as a first-line investigation has a high value for diagnosis of CVST in the emergency setting. The additional measurement of the sinus attenuation may improve the diagnostic value of the examination.

DOI: https://doi.org/10.1515/raon-2016-0026 | Journal eISSN: 1581-3207 | Journal ISSN: 1318-2099
Language: English
Page range: 263 - 268
Submitted on: Feb 9, 2015
Accepted on: Mar 6, 2016
Published on: Jul 19, 2016
Published by: Association of Radiology and Oncology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2016 Jernej Avsenik, Janja Pretnar Oblak, Katarina Surlan Popovic, published by Association of Radiology and Oncology
This work is licensed under the Creative Commons License.