The central vein sign (CVS) has been shown to help in the differential diagnosis of multiple sclerosis (MS), but most prior studies are retrospective.
Objectives:
To prospectively assess the diagnostic predictive value of the CVS in diagnostically difficult cases.
Methods:
In this prospective multicenter study, 51 patients with suspected MS who had clinical, imaging, or laboratory “red flags” (i.e. features atypical for MS) underwent 3T fluid-attenuated inversion recovery (FLAIR*) magnetic resonance imaging (MRI) for CVS assessment. After the diagnostic work-up, expert clinicians blinded to the results of the CVS assessment came to a clinical diagnosis. The value of the CVS to prospectively predict an MS diagnosis was assessed.
Results:
Of the 39 patients who received a clinical diagnosis by the end of the study, 27 had MS and 12 received a non-MS diagnosis that included systemic lupus erythematosus, sarcoidosis, migraine, Sjögren disease, SPG4-spastic-paraparesis, neuromyelitis optica, and Susac syndrome. The percentage of perivenular lesions was higher in MS (median = 86%) compared to non-MS (median = 21%; p < 0.0001) patients. A 40% perivenular lesion cutoff was associated with 97% accuracy and a 96% positive/100% negative predictive value.
Conclusion:
The CVS detected on 3T FLAIR* images can accurately predict an MS diagnosis in patients suspected to have MS, but with atypical clinical, laboratory, and imaging features.
ReichDSLucchinettiCFCalabresiPA.Multiple sclerosis. N Engl J Med2018; 378: 169–180.
2.
ThompsonAJBanwellBLBarkhofF, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol2018; 17: 162–173.
3.
SolomonAJCorboyJR. The tension between early diagnosis and misdiagnosis of multiple sclerosis. Nat Rev Neurol2017; 13(9): 567–572.
4.
GeraldesRCiccarelliOBarkhofF, et al. The current role of MRI in differentiating multiple sclerosis from its imaging mimics. Nat Rev Neurol2018; 14: 199–213.
5.
SatiPOhJConstableRT, et al. The central vein sign and its clinical evaluation for the diagnosis of multiple sclerosis: A consensus statement from the North American Imaging in Multiple Sclerosis Cooperative. Nat Rev Neurol2016; 12(12): 714–722.
6.
MaggiPAbsintaMGrammaticoM, et al. Central vein sign differentiates multiple sclerosis from central nervous system inflammatory vasculopathies. Ann Neurol2018; 83: 283–294.
7.
AbsintaMNairGMonacoMCG, et al. The “central vein sign” in inflammatory demyelination: The role of fibrillar collagen type I. Ann Neurol2019; 85(6): 934–942.
8.
SolomonAJSchindlerMKHowardDB, et al. “Central vessel sign” on 3T FLAIR* MRI for the differentiation of multiple sclerosis from migraine. Ann Clin Transl Neurol2016; 3: 82–87.
9.
SolomonAJWattsROntanedaD, et al. Diagnostic performance of central vein sign for multiple sclerosis with a simplified three-lesion algorithm. Mult Scler2018; 24: 750–757.
10.
TallantyreECDixonJEDonaldsonI, et al. Ultra-high-field imaging distinguishes MS lesions from asymptomatic white matter lesions. Neurology2011; 76(6): 534–539.
11.
CorteseRMagnollayLTurC, et al. Value of the central vein sign at 3T to differentiate MS from seropositive NMOSD. Neurology2018; 90(14): e1183–e1190.
12.
WuerfelJSinneckerTRingelsteinEB, et al. Lesion morphology at 7 Tesla MRI differentiates Susac syndrome from multiple sclerosis. Mult Scler2012; 18(11): 1592–1599.
13.
MillerDWeinshenkerBFilippiM, et al. Differential diagnosis of suspected multiple sclerosis: A consensus approach. Mult Scler2008; 14(9): 1157–1174.
14.
ToledanoMWeinshenkerBGSolomonAJ.A clinical approach to the differential diagnosis of multiple sclerosis. Curr Neurol Neurosci Rep2015; 15: 57.
15.
SolomonAJNaismithRTCrossAH.Misdiagnosis of multiple sclerosis: Impact of the 2017 McDonald criteria on clinical practice. Neurology2019; 92(1): 26–33.
16.
CharilAYousryTARovarisM, et al. MRI and the diagnosis of multiple sclerosis: Expanding the concept of “no better explanation.”Lancet Neurol2006; 5: 841–852.
17.
FilippiMPreziosaPBanwellBL, et al. Assessment of lesions on magnetic resonance imaging in multiple sclerosis: Practical guidelines. Brain2019; 142: 1858–1875.
18.
StangelMFredriksonSMeinlE, et al. The utility of cerebrospinal fluid analysis in patients with multiple sclerosis. Nat Rev Neurol2013; 9(5): 267–276.
19.
SatiPGeorgeICSheaCD, et al. FLAIR*: A combined MR contrast technique for visualizing white matter lesions and parenchymal veins. Radiology2012; 265(3): 926–932.
20.
MistryNAbdel-FahimRSamaraweeraA, et al. Imaging central veins in brain lesions with 3-T T2*-weighted magnetic resonance imaging differentiates multiple sclerosis from microangiopathic brain lesions. Mult Scler2016; 22(10): 1289–1296.
21.
PetriMOrbaiA-MAlarconGS, et al. Derivation and validation of the Systemic Lupus International Collaborating Clinics classification criteria for systemic lupus erythematosus. Arthritis Rheum2012; 64(8): 2677–2686.
22.
SternBJRoyalW3rdGelfandJM, et al. Definition and consensus diagnostic criteria for neurosarcoidosis: From the Neurosarcoidosis Consortium Consensus Group. JAMA Neurol2018; 75(12): 1546–1553.
23.
ShiboskiCHShiboskiSCSerorR, et al. 2016 American College of Rheumatology/European League Against Rheumatism Classification Criteria for Primary Sjögren’s Syndrome: A Consensus and Data-Driven Methodology Involving Three International Patient Cohorts: ACR/EULAR CLASSIFICATION CRITERIA FOR PRIMARY SS. Arthritis Rheumatol2017; 69: 35–45.
24.
DepienneCBriceADurrA.Chapter 14 SPG4, the most frequent hereditary spastic paraplegia: Clinical and genetic aspects. In: BriceAPulstS-M (eds) Spinocerebellar degenerations: The ataxias and spastic paraplegias (Blue Books of Neurology). Amsterdam: Elsevier, 2007, pp. 296–307.
25.
WingerchukDMBanwellBBennettJL, et al. International consensus diagnostic criteria for neuromyelitis optica spectrum disorders. Neurology2015; 85: 177–189.
26.
KleffnerIDörrJRingelsteinM, et al. Diagnostic criteria for Susac syndrome. J Neurol Neurosurg Psychiatry2016; 87: 1287–1295.
MistryNDixonJTallantyreE, et al. Central veins in brain lesions visualized with high-field magnetic resonance imaging: A pathologically specific diagnostic biomarker for inflammatory demyelination in the brain. JAMA Neurol2013; 70(5): 623.
29.
van der Vuurst de VriesRMMescheriakovaJYWongYYM, et al. Application of the 2017 revised McDonald criteria for multiple sclerosis to patients with a typical clinically isolated syndrome. JAMA Neurol2018; 75(11): 1392–1398.
30.
PolmanCHReingoldSCBanwellB, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol2011; 69(2): 292–302.
31.
The central vein sign on cerebral 3T MRI in multiple sclerosis—a multi-center investigation under the auspices of the MAGNIMS study group. In: Paper presented at the 34th congress of the European Committee for treatment and research in multiple sclerosis, Berlin, 10–12 October 2018, pp. 8–120. Basel: ECTRIMS.
32.
TyshkovCPawateSBradshawMJ, et al. Multiple sclerosis and sarcoidosis: A case for coexistence. Neurol Clin Pract2019; 9(3): 218–227.
33.
SchwartzDLTaggeIPowersK, et al. Multisite reliability and repeatability of an advanced brain MRI protocol: Reliability of an advanced brain MRI protocol. J Magn Reson Imaging2019; 50: 878–888.
