Literature DB >> 29514948

Value of the central vein sign at 3T to differentiate MS from seropositive NMOSD.

Rosa Cortese1, Lise Magnollay2, Carmen Tur2, Khaled Abdel-Aziz2, Anu Jacob2, Floriana De Angelis2, Marios C Yiannakas2, Ferran Prados2, Sebastien Ourselin2, Tarek A Yousry2, Frederik Barkhof2, Olga Ciccarelli2.   

Abstract

OBJECTIVE: To assess the value of the central vein sign (CVS) on a clinical 3T scanner to distinguish between multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD).
METHODS: Eighteen aquaporin-4-antibody-positive patients with NMOSD, 18 patients with relapsing-remitting MS, and 25 healthy controls underwent 3T MRI. The presence of a central vein in white matter lesions on susceptibility-weighted imaging, defined as a thin hypointense line or a small dot, was recorded.
RESULTS: The proportion of lesions with the CVS was higher in MS than NMOSD (80% vs 32%, p < 0.001). A greater proportion of lesions with the CVS predicted the diagnosis of MS, rather than NMOSD (odds ratio 1.10, 95% confidence interval [CI] 1.04 to 1.16, p = 0.001), suggesting that each percent unit increase in the proportion of lesions with the CVS in an individual patient was associated with a 10% increase in the risk of the same patient having MS. If more than 54% of the lesions on any given scan show the CVS, then the patient can be given a diagnosis of MS with an accuracy of 94% (95% CIs 81.34, 99.32, p < 0.001, sensitivity/specificity 90%/100%).
CONCLUSION: The clinical value of the CVS in the context of the differential diagnosis between MS and NMOSD, previously suggested using 7T scanners, is now extended to clinical 3T scanners, thereby making a step towards the use of CVS in clinical practice. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that the CVS on 3T MRI accurately distinguishes patients with MS from those with seropositive NMOSD.
© 2018 American Academy of Neurology.

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Year:  2018        PMID: 29514948     DOI: 10.1212/WNL.0000000000005256

Source DB:  PubMed          Journal:  Neurology        ISSN: 0028-3878            Impact factor:   9.910


  15 in total

1.  The "central vein sign" in patients with diagnostic "red flags" for multiple sclerosis: A prospective multicenter 3T study.

Authors:  Pietro Maggi; Martina Absinta; Pascal Sati; Gaetano Perrotta; Luca Massacesi; Bernard Dachy; Caroline Pot; Reto Meuli; Daniel S Reich; Massimo Filippi; Renaud Du Pasquier; Marie Théaudin
Journal:  Mult Scler       Date:  2019-09-19       Impact factor: 6.312

Review 2.  The current role of MRI in differentiating multiple sclerosis from its imaging mimics.

Authors:  Ruth Geraldes; Olga Ciccarelli; Frederik Barkhof; Nicola De Stefano; Christian Enzinger; Massimo Filippi; Monika Hofer; Friedemann Paul; Paolo Preziosa; Alex Rovira; Gabriele C DeLuca; Ludwig Kappos; Tarek Yousry; Franz Fazekas; Jette Frederiksen; Claudio Gasperini; Jaume Sastre-Garriga; Nikos Evangelou; Jacqueline Palace
Journal:  Nat Rev Neurol       Date:  2018-03-09       Impact factor: 42.937

3.  SWAN-Venule: An Optimized MRI Technique to Detect the Central Vein Sign in MS Plaques.

Authors:  M I Gaitán; P Yañez; M E Paday Formenti; I Calandri; E Figueiredo; P Sati; J Correale
Journal:  AJNR Am J Neuroradiol       Date:  2020-02-13       Impact factor: 3.825

4.  The Central Vein Sign in Radiologically Isolated Syndrome.

Authors:  S Suthiphosuwan; P Sati; M Guenette; X Montalban; D S Reich; A Bharatha; J Oh
Journal:  AJNR Am J Neuroradiol       Date:  2019-04-18       Impact factor: 3.825

Review 5.  Autoimmune diseases of the brain, imaging and clinical review.

Authors:  Ghazal Shadmani; Tyrell J Simkins; Reza Assadsangabi; Michelle Apperson; Lotfi Hacein-Bey; Osama Raslan; Vladimir Ivanovic
Journal:  Neuroradiol J       Date:  2021-09-07

Review 6.  A window into the future? MRI for evaluation of neuromyelitis optica spectrum disorder throughout the disease course.

Authors:  Jacqueline M Solomon; Friedemann Paul; Claudia Chien; Jiwon Oh; Dalia L Rotstein
Journal:  Ther Adv Neurol Disord       Date:  2021-05-09       Impact factor: 6.570

7.  CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis.

Authors:  Pietro Maggi; Mário João Fartaria; João Jorge; Francesco La Rosa; Martina Absinta; Pascal Sati; Reto Meuli; Renaud Du Pasquier; Daniel S Reich; Meritxell Bach Cuadra; Cristina Granziera; Jonas Richiardi; Tobias Kober
Journal:  NMR Biomed       Date:  2020-03-03       Impact factor: 4.478

Review 8.  Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines.

Authors:  Massimo Filippi; Paolo Preziosa; Brenda L Banwell; Frederik Barkhof; Olga Ciccarelli; Nicola De Stefano; Jeroen J G Geurts; Friedemann Paul; Daniel S Reich; Ahmed T Toosy; Anthony Traboulsee; Mike P Wattjes; Tarek A Yousry; Achim Gass; Catherine Lubetzki; Brian G Weinshenker; Maria A Rocca
Journal:  Brain       Date:  2019-07-01       Impact factor: 13.501

9.  Predicting conversion from clinically isolated syndrome to multiple sclerosis-An imaging-based machine learning approach.

Authors:  Haike Zhang; Esther Alberts; Viola Pongratz; Mark Mühlau; Claus Zimmer; Benedikt Wiestler; Paul Eichinger
Journal:  Neuroimage Clin       Date:  2018-11-05       Impact factor: 4.881

10.  The MRI central vein marker; differentiating PPMS from RRMS and ischemic SVD.

Authors:  Amal P R Samaraweera; Yasser Falah; Alain Pitiot; Robert A Dineen; Paul S Morgan; Nikos Evangelou
Journal:  Neurol Neuroimmunol Neuroinflamm       Date:  2018-09-26
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