• Title of article

    Assessment of cerebral venous sinus ‎thrombosis using T2*-weighted ‎gradient echo magnetic resonance ‎imaging sequences

  • Author/Authors

    Bidar، Fatemeh نويسنده ‎Department of Radiology Technology, School of Allied Medical Sciences, Shahid ‎Beheshti University of Medical Sciences; Tehran, Iran Bidar, Fatemeh , Faeghi، Fariborz نويسنده Radiology Technology Department, School of Paramedicine , , Ghorbani، Askar نويسنده Department of Neurology, School of Medicine, Tehran University of Medical ‎Sciences, Tehran, Iran Ghorbani, Askar

  • Issue Information
    فصلنامه با شماره پیاپی 0 سال 2016
  • Pages
    4
  • From page
    96
  • To page
    99
  • Abstract

    Background: The purpose of this study is to demonstrate the advantages of gradient echo (GRE) sequences in the detection and characterization of cerebral venous sinus thrombosis compared to conventional magnetic resonance sequences.

    Methods: A total of 17 patients with cerebral venous thrombosis (CVT) were evaluated using different magnetic resonance imaging (MRI) sequences. The MRI sequences included T1-weighted spin echo (SE) imaging, -weighted turbo SE (TSE), fluid attenuated inversion recovery (FLAIR), -weighted conventional GRE, and diffusion weighted imaging (DWI). MR venography (MRV) images were obtained as the golden standard.

    Results: Venous sinus thrombosis was best detectable in -weighted conventional GRE sequences in all patients except in one case. Venous thrombosis was undetectable in DWI. -weighted GRE sequences were superior to -weighted TSE, T1-weighted SE, and FLAIR. Enhanced MRV was successful in displaying the location of thrombosis.

    Conclusion: -weighted conventional GRE sequences are probably the best method for the assessment of cerebral venous sinus thrombosis. The mentioned method is non-invasive; therefore, it can be employed in the clinical evaluation of cerebral venous sinus thrombosis.
  • Journal title
    Iranian Journal of Neurology
  • Serial Year
    2016
  • Journal title
    Iranian Journal of Neurology
  • Record number

    2395529