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The “central vein sign”: is there a place for susceptibility weighted imaging in possible multiple sclerosis?

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Abstract

Objectives

Susceptibility weighted imaging (SWI) may have the potential to depict the perivenous extent of white matter lesions (WMLs) in multiple sclerosis (MS). We aimed to assess the discriminatory value of the “central vein sign” (CVS).

Methods

In a 3-T magnetic resonance imaging (MRI) study, 28 WMLs in 14 patients with at least one circumscribed lesion >5 mm and not more than eight non-confluent lesions >3 mm were prospectively included. Only WMLs in FLAIR images with a maximum diameter of >5 mm were correlated to their SWI equivalent for CVS evaluation.

Results

Five patients fulfilled the revised McDonald criteria for MS and nine patients were given alternative diagnoses. Nineteen MS-WMLs and nine non-MS-WMLs >5 mm were detected. Consensus reading found a central vein in 16 out of 19 MS-WMLs (84 %) and in one out of nine non-MS-WMLs (11 %), respectively. The CVS proved to be a highly significant discriminator (P < 0.001) between MS-WMLs and non-MS-WMLs with a sensitivity, specificity, positive and negative predictive value and accuracy of 84 %, 89 %, 94 %, 73 % and 86 %, respectively. Inter-rater agreement was good (κ = 0.77).

Conclusions

Even though the CVS is not exclusively found in MS-WMLs, SWI may be a useful adjunct in patients with possible MS.

Key Points

• MRI continues to yield further information concerning MS lesions.

• SWI adds diagnostic information in patients with possible MS.

• The “central vein sign” was predominantly seen in MS lesions.

• The “central vein sign” helps discriminate between MS and non-MS lesions.

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Abbreviations

AP:

Antero-posterior

CDMS:

Clinically definite multiple sclerosis

CIS:

Clinically isolated syndrome

CV:

central vein

CVS:

Central vein sign

DD:

Differential diagnosis

DIS:

Dissemination in space

DIT:

Dissemination in time

FH:

Feet-head

FLAIR:

Fluid-attenuated inversion-recovery

mIP:

Minimum intensity projection

MS:

Multiple sclerosis

PACS:

Picture archiving and communication system

RIS:

Radiologically isolated syndrome

RL:

Right-left

SOCR:

Statistics Online Computational Resource

SWI:

Susceptibility weighted imaging

WML:

white matter lesion

References

  1. Noseworthy JH, Lucchinetti C, Rodriguez M, Weinshenker BG (2000) Multiple sclerosis. N Engl J Med 343:938–952

    Article  PubMed  CAS  Google Scholar 

  2. Renoux C, Vukusic S, Mikaeloff Y et al (2007) Natural history of multiple sclerosis with childhood onset. N Engl J Med 356:2603–2613

    Article  PubMed  CAS  Google Scholar 

  3. Okuda DT, Mowry EM, Beheshtian A et al (2009) Incidental MRI anomalies suggestive of multiple sclerosis: the radiologically isolated syndrome. Neurology 72:800–805

    Article  PubMed  CAS  Google Scholar 

  4. Poser CM, Paty DW, Scheinberg L et al (1983) New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1:227–231

    Article  Google Scholar 

  5. McDonald WI, Compston A, Edan G et al (2001) Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol 50:121–127

    Article  PubMed  CAS  Google Scholar 

  6. Tintoré M, Rovira A, Río J et al (2003) New diagnostic criteria for multiple sclerosis. Application in first demyelinating episode. Neurology 60:27–30

    Article  PubMed  Google Scholar 

  7. Polman CH, Reingold SC, Banwell B et al (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69:292–302

    Article  PubMed  Google Scholar 

  8. Filippi M, Rocca MA (2011) MR imaging of multiple sclerosis. Radiology 259:659–681

    Article  PubMed  Google Scholar 

  9. Fazekas F, Kleinert R, Offenbacher H et al (1991) The morphologic correlate of incidental punctate white matter hyperintensities on MR images. AJNR Am J Neuroradiol 12:915–921

    PubMed  CAS  Google Scholar 

  10. Breteler MM, van Swieten JC, Bots ML et al (1994) Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam Study. Neurology 44:1246–1252

    Article  PubMed  CAS  Google Scholar 

  11. de Leeuw FE, de Groot JC, Achten E et al (2001) Prevalence of cerebral white matter lesions in elderly people: a population based magnetic resonance imaging study. The Rotterdam Scan Study. J Neurol Neurosurg Psychiatry 70:9–14

    Article  PubMed  Google Scholar 

  12. Putnam TJ (1933) The pathogenesis of multiple sclerosis: a possible vascular factor. N Engl J Med 209:786–790

    Article  Google Scholar 

  13. Fog T (1965) The topography of plaques in multiple sclerosis with special reference to cerebral plaques. Acta Neurol Scand Suppl 15:1–161

    PubMed  CAS  Google Scholar 

  14. Horowitz AL, Kaplan RD, Grewe G, White RT, Salberg LM (1989) The ovoid lesion: a new MR observation in patients with multiple sclerosis. AJNR Am J Neuroradiol 10:303–305

    PubMed  CAS  Google Scholar 

  15. Filippi M, Rocca MA, Barkhof F et al (2012) Attendees of the Correlation between Pathological MRI findings in MS workshop. Association between pathological and MRI findings in multiple sclerosis. Lancet Neurol 11:349–360

    Article  PubMed  Google Scholar 

  16. Ge Y, Zohrabian VM, Grossman RI (2008) Seven-Tesla magnetic resonance imaging: new vision of microvascular abnormalities in multiple sclerosis. Arch Neurol 65:812–816

    Article  PubMed  Google Scholar 

  17. Tallantyre EC, Morgan PS, Dixon JE et al (2009) A comparison of 3T and 7T in the detection of small parenchymal veins within MS lesions. Invest Radiol 44:491–494

    Article  PubMed  Google Scholar 

  18. Grabner G, Dal-Bianco A, Schernthaner M, Vass K, Lassmann H, Trattnig S (2011) Analysis of multiple sclerosis lesions using a fusion of 3.0 T FLAIR and 7.0 T SWI phase: FLAIR SWI. J Magn Reson Imaging 33:543–549

    Article  PubMed  Google Scholar 

  19. Haacke EM, Xu Y, Cheng YC, Reichenbach JR (2004) Susceptibility weighted imaging (SWI). Magn Reson Med 52:612–618

    Article  PubMed  Google Scholar 

  20. Lummel N, Boeckh-Behrens T, Schoepf V, Burke M, Brückmann H, Linn J (2011) Presence of a central vein within white matter lesions on susceptibility weighted imaging: a specific finding for multiple sclerosis? Neuroradiology 53:311–317

    Article  PubMed  Google Scholar 

  21. Carmody DP, Dunn SM, Boddie-Willis AS, DeMarco JK, Lewis M (2004) A quantitative measure of myelination development in infants, using MR images. Neuroradiology 46:781–786

    Article  PubMed  Google Scholar 

  22. Dinov ID (2006) SOCR: Statistics Online Computational Resource. J Stat Softw 16:1–16

    Google Scholar 

  23. Jacobs DL, Beck RW, Simon JH et al (2000) Intramuscular interferon beta-1a therapy initiated during a first demyelinating event in multiple sclerosis. N Engl J Med 343:898–904

    Article  PubMed  CAS  Google Scholar 

  24. Enzinger C, Smith S, Fazekas F et al (2006) Lesion probability maps of white matter hyperintensities in elderly individuals: results of the Austrian stroke prevention study. J Neurol 253:1064–1070

    Article  PubMed  Google Scholar 

  25. Barkhof F, Filippi M, Miller DH et al (1997) Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis. Brain 120:2059–2069

    Article  PubMed  Google Scholar 

  26. Tan IL, van Schijndel RA, Pouwels PJ, van Walderveen MA, Reichenbach JR, Manoliu RA, Barkhof F (2000) MR venography of multiple sclerosis. AJNR Am J Neuroradiol 21:1039–1042

    PubMed  CAS  Google Scholar 

  27. Adams CWM, Poston RN, Buk SJ (1989) Pathology, histochemistry and immunocytochemistry of lesions in acute multiple sclerosis. J Neurol Sci 92:291–306

    Article  PubMed  CAS  Google Scholar 

  28. Ge Y, Zohrabian VM, Osa EO et al (2009) Diminished visibility of cerebral venous vasculature in multiple sclerosis by susceptibility-weighted imaging at 3.0 Tesla. J Magn Reson Imaging 29:1190–1194

    Article  PubMed  Google Scholar 

  29. Zivadinov R, Poloni GU, Marr K et al (2011) Decreased brain venous vasculature visibility on susceptibility-weighted imaging venography in patients with multiple sclerosis is related to chronic cerebrospinal venous insufficiency. BMC Neurol 11:128

    Article  PubMed  Google Scholar 

  30. Reichenbach JR, Venkatesan R, Schillinger DJ, Kido DK, Haacke EM (1997) Small vessels in the human brain: MR venography with deoxyhemoglobin as an intrinsic contrast agent. Radiology 204:272–277

    PubMed  CAS  Google Scholar 

  31. Hodel J, Rodallec M, Gerber S et al (2012) Susceptibility weighted magnetic resonance sequences “SWAN, SWI and VenoBOLD”: technical aspects and clinical applications. J Neuroradiol 39:71–86

    PubMed  CAS  Google Scholar 

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Acknowledgements

The abstract of this scientific paper (ctrl no. 2123) has been accepted for oral presentation at ECR 2013.

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Correspondence to Thomas Kau.

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Kau, T., Taschwer, M., Deutschmann, H. et al. The “central vein sign”: is there a place for susceptibility weighted imaging in possible multiple sclerosis?. Eur Radiol 23, 1956–1962 (2013). https://doi.org/10.1007/s00330-013-2791-4

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  • DOI: https://doi.org/10.1007/s00330-013-2791-4

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