To evaluate prospectively whether an intravenous gadolinium injection could improve the detection of the central vein sign on susceptibility-weighted imaging sequences obtained with a 1.5 T magnetic resonance scanner in patients with multiple sclerosis compared to unenhanced susceptibility-weighted images.
Materials and methods
This prospective, institution review board-approved study included 19 patients affected by multiple sclerosis (six men; 13 women; mean age 40.8 years, range 20–74 years). Patients had the relapsing–remitting clinical subtype in 95% of cases, and only one (5%) patient had the primary progressive clinical subtype of multiple sclerosis. T2-weighted images, fluid-attenuated inversion recovery images, unenhanced and contrast-enhanced susceptibility-weighted images were evaluated in consensus by two neuroradiologists for the presence of the central vein sign. The readers were blinded to magnetic resonance imaging reports, clinical information, the presence and the localisation of focal hyperintense white matter lesions. Any discordance between readers was resolved through a joint review of the recorded images with an additional neuroradiologist.
Results
A total of 317 multiple sclerosis lesions were analysed. The central vein sign had a higher prevalence detection rate on gadolinium-enhanced susceptibility-weighted images (272 of 317 lesions, 86%) compared to unenhanced susceptibility-weighted images (172 of 317 lesions, 54%).
Conclusion
Gadolinium-enhanced susceptibility-weighted imaging improves the detection rate of the central vein sign in multiple sclerosis lesions.
MittalSWuZNeelavalliJ, et al.
Susceptibility-weighted imaging: technical aspects and clinical applications, part 2. Am J Neuroradiol2009;
30: 232–252.
3.
OgawaSLeeTMKayAR, et al.
Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc Natl Acad Sci USA1990;
87: 9868–9872.
4.
ReichenbachJRVenkatesanRSchillingerDJ, et al.
Small vessels in the human brain: MR venography with deoxyhemoglobin as an intrinsic contrast agent. Radiology1997;
204: 272–277.
5.
ScharfJBrauherrEForstingM, et al.
Significance of haemorrhagic lacunes on MRI in patients with hypertensive cerebrovascular disease and intracerebral haemorrhage. Neuroradiology1994;
36: 504–508.
6.
SparaciaGAgnelloFGambinoA, et al.
Multiple sclerosis: high prevalence of the ‘central vein’ sign in white matter lesions on susceptibility-weighted images. Neuroradiol J2018;
31: 356–361.
7.
ÖztoprakBÖztoprakIYıldızÖK.The effect of venous anatomy on the morphology of multiple sclerosis lesions: a susceptibility-weighted imaging study. Clin Radiol2016;
71: 418–426.
8.
LamotUAvsenikJŠegaS, et al.
Presence of central veins and susceptibility weighted imaging for evaluating lesions in multiple sclerosis and leukoaraiosis. Mult Scler Relat Disord2017;
13: 67–72.
9.
LummelNBoeckh-BehrensTSchoepfV, et al.
Presence of a central vein within white matter lesions on susceptibility weighted imaging: a specific finding for multiple sclerosis?Neuroradiology2011;
53: 311–317.
10.
MaggiPMazzoniLNMorettiM, et al.
SWI enhances vein detection using gadolinium in multiple sclerosis. Acta Radiol Open2015;
4: 1–4.
11.
TallantyreECDixonJEDonaldsonI, et al.
Ultra-high-field imaging distinguishes MS lesions from asymptomatic white matter lesions. Neurology2011;
76534–539.
12.
KilsdonkIDWattjesMPLopez-SorianoA, et al.
Improved differentiation between MS and vascular brain lesions using FLAIR* at 7 Tesla. Eur Radiol2014;
24: 841–849.
13.
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: 1289–1296.
14.
SolomonAJSchindlerMKHowardDB, et al. “
Central vessel sign” on 3T FLAIR* MRI for the differentiation of multiple sclerosis from migraine. Ann Clin Transl Neurol2015;
3: 82–87.
15.
LaneJIBolsterBCampeauNG, et al.
Characterization of multiple sclerosis plaques using susceptibility-weighted imaging at 1.5 T: can perivenular localization improve specificity of imaging criteria?J Comput Assist Tomogr2015;
39: 317–320.
16.
LamotUAvsenikJŠegaS, et al.
Presence of central veins and susceptibility weighted imaging for evaluating lesions in multiple sclerosis and leukoaraiosis. Mult Scler Relat Disord2017;
13: 67–72.
17.
SatiPOhJConstableRT, et al.; NAIMS Cooperative.
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: 714–722.
18.
AdamsCWPostonRNBukSJ.Pathology, histochemistry and immunocytochemistry of lesions in acute multiple sclerosis. J Neurol Sci1989;
92: 291–306.
19.
GeYZohrabianVMOsaEO, et al.
Diminished visibility of cerebral venous vasculature in multiple sclerosis by susceptibility-weighted imaging at 3.0 Tesla. J Magn Reson Imaging2009;
29: 1190–1194.
20.
BakshiRMiletichRSKinkelPR, et al.
High-resolution fluorodeoxyglucose positron emission tomography shows both global and regional cerebral hypometabolism in multiple sclerosis. J Neuroimaging1998;
8: 228–234.
21.
PolmanCHReingoldSCBanwellB, et al.
Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol2011;
69: 292–302.
22.
KurtzkeJF.Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS).Neurology1983;
33: 1444–1452.
23.
OtakeSTaokaTMaedaM, et al.
A guide to identification and selection of axial planes in magnetic resonance imaging of the brain. Neuroradiol J2018;
31: 336–344.
24.
SparaciaGSpecialeCBancoA, et al.
Accuracy of SWI sequences compared to T2*-weighted gradient echo sequences in the detection of cerebral cavernous malformations in the familial form. Neuroradiol J2016;
29: 326–335.
25.
SatiPThomassonDMLiN, et al.
Rapid, high-resolution, whole-brain, susceptibility-based MRI of multiple sclerosis. Mult Scler2014;
20: 1464–1470.
26.
DixonJESimpsonAMistryN, et al.
Optimisation of T2*-weighted MRI for the detection of small veins in multiple sclerosis at 3 T and 7 T. Eur J Radiol2013;
82: 719–727.
27.
GaitánMIYañezPPaday FormentiME, et al.
SWAN-Venule: an optimized MRI technique to detect the central vein sign in MS plaques. AJNR Am J Neuroradiol2020;
81(2): 272–276.
28.
do AmaralLLFFragosoDCNunesRH, et al.
Gadolinium-enhanced susceptibility-weighted imaging in multiple sclerosis: optimizing the recognition of active plaques for different MR imaging sequences. AJNR Am J Neuroradiol2019;
40(4): 614–619.
29.
International Society for Magnetic Resonance in Medicine.Gadolinium deposition in the brain: summary of evidence and recommendations. Lancet Neurol2017;
16: 564–570.
30.
SaindaneAM.Is gadolinium-based contrast material needed for MRI follow-up of multiple sclerosis?Radiology2019;
291(2): 190319.
31.
EichingerPSchönSPongratzV, et al.
Accuracy of unenhanced MRI in the detection of new brain lesions in multiple sclerosis. Radiology2019;
291(2): 181568.
32.
ThompsonAJBanwellBLBarkhofF, et al.
Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol2018;
17: 162–173.
33.
CottonFWeinerHLJoleszFA, et al.
MRI contrast uptake in new lesions in relapsing–remitting MS followed at weekly intervals. Neurology2003;
60: 640–646.
34.
BankierAALevineDHalpernEF, et al.
Consensus interpretation in imaging research: is there a better way?Radiology2010;
257: 14–17.
35.
Abolhasani ForoughiASalahiRNiksereshtAet al.
Comparison of diffusion-weighted imaging and enhanced T1-weighted sequencing in patients with multiple sclerosis. Neuroradiol J2017;
30: 347–351.
36.
SinneckerTClarkeMAMeierD, et al.
Evaluation of the central vein sign as a diagnostic imaging biomarker in multiple sclerosis. JAMA Neurol2019;
76: 1446–1456.
37.
El-KoussyMSchenkPKieferC, et al.
Susceptibility-weighted imaging of the brain: does gadolinium administration matter?Eur J Radiol2012;
81: 272–276.
