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Use of gadolinium-based contrast agents in multiple sclerosis: a review by the ESMRMB-GREC and ESNR Multiple Sclerosis Working Group

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A Commentary to this article was published on 02 October 2023

Abstract 

Magnetic resonance imaging (MRI) is the most sensitive technique for detecting inflammatory demyelinating lesions in multiple sclerosis (MS) and plays a crucial role in diagnosis and monitoring treatment effectiveness, and for predicting the disease course. In clinical practice, detection of MS lesions is mainly based on T2-weighted and contrast-enhanced T1-weighted sequences. Contrast-enhancing lesions (CEL) on T1-weighted sequences are related to (sub)acute inflammation, while new or enlarging T2 lesions reflect the permanent footprint from a previous acute inflammatory demyelinating event. These two types of MRI features provide redundant information, at least in regular monitoring of the disease. Due to the concern of gadolinium deposition after repetitive injections of gadolinium-based contrast agents (GBCAs), scientific organizations and regulatory agencies in Europe and North America have proposed that these contrast agents should be administered only if clinically necessary. In this article, we provide data on the mode of action of GBCAs in MS, the indications of the use of these agents in clinical practice, their value in MS for diagnostic, prognostic, and monitoring purposes, and their use in specific populations (children, pregnant women, and breast-feeders). We discuss imaging strategies that achieve the highest sensitivity for detecting CELs in compliance with the safety regulations established by different regulatory agencies. Finally, we will briefly discuss some alternatives to the use of GBCA for detecting blood–brain barrier disruption in MS lesions.

Clinical relevance statement

Although use of GBCA at diagnostic workup of suspected MS is highly valuable for diagnostic and prognostic purposes, their use in routine monitoring is not mandatory and must be reduced, as detection of disease activity can be based on the identification of new or enlarging lesions on T2-weighted images.

Key Points

• Both the EMA and the FDA state that the use of GBCA in medicine should be restricted to clinical scenarios in which the additional information offered by the contrast agent is required.

• The use of GBCA is generally recommended in the diagnostic workup in subjects with suspected MS and is generally not necessary for routine monitoring in clinical practice.

• Alternative MRI-based approaches for detecting acute focal inflammatory MS lesions are not yet ready to be used in clinical practice.

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Abbreviations

ADC:

Apparent diffusion coefficient

CEL:

Contrast-enhancing lesion

CMSC:

Consortium of Multiple Sclerosis Centers

DMT:

Disease-modifying treatment

DTI:

Diffusion tensor imaging

DWI:

Diffusion-weighted imaging

EMA:

European Medicines Agency

EPI:

Echo planar imaging

ESMRMB:

European Society for Magnetic Resonance in Medicine and Biology

ESNR:

European Society of Neuroradiology

FA:

Fractional anisotropy

FDA:

Food and Drug Administration

FLAIR:

Fluid-attenuated inversion recovery

GBCA:

Gadolinium-based contrast agent

GRE:

Gradient-recalled echo

GREC:

Gadolinium Research & Education Committee

MAGNIMS:

Magnetic resonance imaging in MS

MRI:

Magnetic resonance imaging

MS:

Multiple sclerosis

NAIMS:

North American Imaging in Multiple Sclerosis

PML:

Progressive multifocal leukoencephalopathy

SE:

Spin-echo

T1w:

T1-weighted

T2w:

T2-weighted

TSE/FSE:

Turbo/fast spin-echo

References

  1. Wattjes MP, Ciccarelli O, Reich DS et al (2021) 2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol 20:653–670

    PubMed  Google Scholar 

  2. Rovira A, Auger C, Alonso J (2013) Magnetic resonance monitoring of lesion evolution in multiple sclerosis. Ther Adv Neurol Disord 6:298–310

    PubMed  PubMed Central  Google Scholar 

  3. Gulani V, Calamante F, Shellock FG et al (2017) Gadolinium deposition in the brain: summary of evidence and recommendations. Lancet Neurol 16:564–570

    PubMed  Google Scholar 

  4. Ognard J, Barrat JA, Cotton F et al (2021) A roadmap towards pollution prevention and sustainable development of Gadolinium. J Neuroradiol 48:409–411

    PubMed  Google Scholar 

  5. Quattrocchi CC, Parillo M, Spani F et al (2023) Skin thickening of the scalp and high signal intensity of dentate nucleus in multiple sclerosis: association with linear versus macrocyclic gadolinium-based contrast agent administration. Invest Radiol 58:223–230. https://doi.org/10.1097/RLI.0000000000000929

    Article  CAS  PubMed  Google Scholar 

  6. Mallio CA, Rovira À, Parizel PM, Quattrocchi CC (2020) Exposure to gadolinium and neurotoxicity: current status of preclinical and clinical studies. Neuroradiology 62:925–934

    PubMed  Google Scholar 

  7. Quattrocchi CC, Ramalho J, van der Molen AJ et al (2019) Standardized assessment of the signal intensity increase on unenhanced T1-weighted images in the brain: the European Gadolinium Retention Evaluation Consortium (GREC) Task Force position statement. Eur Radiol 29:3959–3967

    PubMed  Google Scholar 

  8. Quattrocchi CC, van der Molen AJ (2017) Gadolinium retention in the body and brain: is it time for an international joint research effort? Radiology 282:12–16

    PubMed  Google Scholar 

  9. Kanda T, Ishii K, Kawaguchi H et al (2014) High signal intensity in the dentate nucleus and globus pallidus on unenhanced T1-weighted MR images: relationship with increasing cumulative dose of a gadolinium-based contrast material. Radiology 270:834–841

    PubMed  Google Scholar 

  10. Thompson AJ, Banwell BL, Barkhof F et al (2018) Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 17:162–173

    PubMed  Google Scholar 

  11. Saade C, Bou-Fakhredin R, Yousem DM et al (2018) Gadolinium and multiple sclerosis: vessels, barriers of the brain, and glymphatics. AJNR Am J Neuroradiol 39:2168–2176

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Minagar A, Alexander JS (2003) Blood-brain barrier disruption in multiple sclerosis. Mult Scler 9:540–549

    CAS  PubMed  Google Scholar 

  13. Lassmann H (2019) Pathogenic mechanisms associated with different clinical courses of multiple sclerosis. https://doi.org/10.3389/FIMMU.2018.03116

  14. Barkhof F, Scheltens P, Frequin STFM et al (1992) Relapsing-remitting multiple sclerosis: sequential enhanced MR imaging vs clinical findings in determining disease activity. AJR Am J Roentgenol 159:1041–1047

    CAS  PubMed  Google Scholar 

  15. Lassmann H (2008) The pathologic substrate of magnetic resonance alterations in multiple sclerosis. Neuroimaging Clin N Am 18:563–576

    PubMed  Google Scholar 

  16. Koudriavtseva T, Thompson AJ, Fiorelli M et al (1997) Gadolinium enhanced MRI predicts clinical and MRI disease activity in relapsing-remitting multiple sclerosis. J Neurol Neurosurg Psychiatry 62:285–287

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Cotton F, Weiner HL, Jolesz FA, Guttmann CRG (2003) MRI contrast uptake in new lesions in relapsing-remitting MS followed at weekly intervals. Neurology 60:640–646

    PubMed  Google Scholar 

  18. Burnham JA, Wright RR, Dreisbach J, Murray RS (1991) The effect of high-dose steroids on MRI gadolinium enhancement in acute demyelinating lesions. Neurology 41:1349–1349

    CAS  PubMed  Google Scholar 

  19. Thompson AJ, Kermode AG, Wicks D et al (1991) Major differences in the dynamics of primary and secondary progressive multiple sclerosis. Ann Neurol 29:53–62

    CAS  PubMed  Google Scholar 

  20. Tremlett H, Zhao Y, Joseph J et al (2008) Relapses in multiple sclerosis are age- and time-dependent. J Neurol Neurosurg Psychiatry 79:1368–1374

    CAS  PubMed  Google Scholar 

  21. Koch MW, Mostert J, Greenfield J et al (2020) Gadolinium enhancement on cranial MRI in multiple sclerosis is age dependent. J Neurol 267:2619–2624

    CAS  PubMed  Google Scholar 

  22. Brownlee WJ, Altmann DR, Prados F et al (2019) Early imaging predictors of long-term outcomes in relapse-onset multiple sclerosis. Brain 142:2276–2287

    PubMed  Google Scholar 

  23. Filippi M, Preziosa P, Banwell BL et al (2019) Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines. Brain 142:1858–1875

    PubMed  PubMed Central  Google Scholar 

  24. European Medicines Agency. EMA’s final opinion confirms restrictions on use of linear gadolinium agents in body scans (21 July 2017). https://www.ema.europa.eu/en/documents/referral/gadolinium-article-31-referral-emas-final-opinion-confirms-restrictions-use-linear-gadolinium-agents_en-0.pdf. Accessed 20 Feb 2023

  25. FDA Drug Safety Podcast: FDA warns that gadolinium-based contrast agents (GBCAs) are retained in the body; requires new class warnings | FDA. https://www.fda.gov/drugs/fda-drug-safety-podcasts/fda-drug-safety-podcast-fda-warns-gadolinium-based-contrast-agents-gbcas-are-retained-body-requires. Accessed 20 Feb 2023

  26. Wijburg MT, Warnke C, McGuigan C et al (2021) Pharmacovigilance during treatment of multiple sclerosis: early recognition of CNS complications. J Neurol Neurosurg Psychiatry 92:177–188

    PubMed  Google Scholar 

  27. Mallio CA, Quattrocchi CC, Rovira À, Parizel PM (2020) Gadolinium deposition safety: seeking the patient’s perspective. AJNR Am J Neuroradiol 41:944–946

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Mallio CA, Piervincenzi C, Gianolio E et al (2019) Absence of dentate nucleus resting-state functional connectivity changes in nonneurological patients with gadolinium-related hyperintensity on T1 -weighted images. J Magn Reson Imaging 50:445–455

    PubMed  Google Scholar 

  29. Mallio CA, Piervincenzi C, Carducci F et al (2020) Within-network brain connectivity in Crohn’s disease patients with gadolinium deposition in the cerebellum. Neuroradiology 62:833–841

    PubMed  Google Scholar 

  30. Wiendl H, Gold R, Berger T et al (2021) Multiple Sclerosis Therapy Consensus Group (MSTCG): position statement on disease-modifying therapies for multiple sclerosis (white paper). Ther Adv Neurol Disord 14:17562864211039648

    PubMed  PubMed Central  Google Scholar 

  31. Fernandes L, Allen CM, Williams T et al (2021) The contemporary role of MRI in the monitoring and management of people with multiple sclerosis in the UK. Mult Scler Relat Disord 55:103190

    CAS  PubMed  Google Scholar 

  32. Blumfield E, Swenson DW, Iyer RS, Stanescu AL (2019) Gadolinium-based contrast agents - review of recent literature on magnetic resonance imaging signal intensity changes and tissue deposits, with emphasis on pediatric patients. Pediatr Radiol 49:448–457

    PubMed  Google Scholar 

  33. Towbin AJ, Zhang B, Dillman JR (2021) Evaluation of the effect of multiple administrations of gadopentetate dimeglumine or gadoterate meglumine on brain T1-weighted hyperintensity in pediatric patients. Pediatr Radiol 51:2568–2580

    PubMed  Google Scholar 

  34. Noda SM, Oztek MA, Stanescu AL et al (2022) Gadolinium retention: should pediatric radiologists be concerned, and how to frame conversations with families. Pediatr Radiol 52:345–353

    PubMed  Google Scholar 

  35. Oh KY, Roberts VHJ, Schabel MC et al (2015) Gadolinium chelate contrast material in pregnancy: fetal biodistribution in the nonhuman primate. Radiology 276:110–118

    PubMed  Google Scholar 

  36. Puac P, Rodríguez A, Vallejo C et al (2017) Safety of contrast material use during pregnancy and lactation. Magn Reson Imaging Clin N Am 25:787–797

    PubMed  Google Scholar 

  37. Winterstein AG, Thai TN, Nduaguba S et al (2022) Risk of fetal or neonatal death or neonatal intensive care unit admission associated with gadolinium magnetic resonance imaging exposure during pregnancy. Am J Obstet Gynecol 228:465.e1–465.e11

    PubMed  Google Scholar 

  38. Ray JG, Vermeulen MJ, Bharatha A et al (2016) Association between MRI Exposure during pregnancy and fetal and childhood outcomes. JAMA 316:952–961

    PubMed  Google Scholar 

  39. Chen MM, Coakley FV, Kaimal A, Laros RK (2008) Guidelines for computed tomography and magnetic resonance imaging use during pregnancy and lactation. Obstet Gynecol 112:333–340

    PubMed  Google Scholar 

  40. Mervak BM, Altun E, McGinty KA et al (2019) MRI in pregnancy: indications and practical considerations. J Magn Reson Imaging 49:621–631

    PubMed  Google Scholar 

  41. Gatta G, Di Grezia G, Cuccurullo V et al (2021) MRI in pregnancy and precision medicine: a review from literature. https://doi.org/10.3390/JPM12010009

  42. ACR (2023) Manual on contrast media, v2023. American College of Radiology, USA. https://www.acr.org/-/media/%20ACR/Files/Clinical-Resources/Contrast_Media.pdf. Accessed 19 Jun 2023

  43. ESUR (2018). ESUR guidelines on contrast agents, v10. https://www.esur.org/wp-content/uploads/2022/03/ESUR-Guidelines-10_0-Final-Version.pdf. Accessed 20 Feb 2023

  44. ACOG (2017) Committee Opinion No. 723: Guidelines for Diagnostic Imaging During Pregnancy and Lactation. Obstet Gynecol 130:e210–e216

    Google Scholar 

  45. Webb JA, Thomsen HS (2013) Gadolinium contrast media during pregnancy and lactation. Acta Radiol 54:599–600

    PubMed  Google Scholar 

  46. Wang PI, Chong ST, Kielar AZ et al (2012) Imaging of pregnant and lactating patients: part 1, evidence-based review and recommendations. AJR Am J Roentgenol 198:778–784

    PubMed  Google Scholar 

  47. Kubik-Huch RA, Gottstein-Aalame NM, Frenzel T et al (2000) Gadopentetate dimeglumine excretion into human breast milk during lactation. Radiology 216:555–558

    CAS  PubMed  Google Scholar 

  48. Sundgren PC, Leander P (2011) Is administration of gadolinium-based contrast media to pregnant women and small children justified? J Magn Reson Imaging 34:750–757

    PubMed  Google Scholar 

  49. Proença F, Guerreiro C, Sá G, Reimão S (2021) Neuroimaging safety during pregnancy and lactation: a review. Neuroradiology 63:837–845

    PubMed  Google Scholar 

  50. Little JT, Bookwalter CA (2020) Magnetic resonance safety: pregnancy and lactation. Magn Reson Imaging Clin N Am 28:509–516

    PubMed  Google Scholar 

  51. van der Molen AJ, Geenen RWF, Dekkers AI (2023) Guideline safe use of contrast media part 3, Radiological Society of The Netherlands (NVvR). https://radiologen.nl/sites/default/files/Kwaliteit/guideline_safe_use_of_contrast_media_part_3_final_8nov2022_eng.pdf. Accessed 26 Mar 2023

  52. van Waesberghe JH, Castelijns JA, Roser W et al (1997) Single-dose gadolinium with magnetization transfer versus triple-dose gadolinium in the MR detection of multiple sclerosis lesions. AJNR Am J Neuroradiol 18:1279–1285

    PubMed  PubMed Central  Google Scholar 

  53. Rovira A, Auger C, Huerga E et al (2017) Cumulative dose of macrocyclic gadolinium-based contrast agent improves detection of enhancing lesions in patients with multiple sclerosis. AJNR Am J Neuroradiol 38:1486–1493

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Giesel FL, Runge V, Kirchin M et al (2010) Three-dimensional multiphase time-resolved low-dose contrast-enhanced magnetic resonance angiography using TWIST on a 32-channel coil at 3 T. J Comput Assist Tomogr 34:678–683

    PubMed  Google Scholar 

  55. Loevner LA, Kolumban B, Hutóczki G et al (2023) Efficacy and safety of gadopiclenol for contrast-enhanced MRI of the central nervous system: the PICTURE randomized clinical trial. Invest Radiol 58:307–313

    CAS  PubMed  Google Scholar 

  56. Gong E, Pauly JM, Wintermark M, Zaharchuk G (2018) Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI. J Magn Reson Imaging 48:330–340

    PubMed  Google Scholar 

  57. Filippi M, Yousry T, Rocca MA et al (1997) Sensitivity of delayed gadolinium-enhanced MRI in multiple sclerosis. Acta Neurol Scand 95:331–334

    CAS  PubMed  Google Scholar 

  58. Absinta M, Vuolo L, Rao A et al (2015) Gadolinium-based MRI characterization of leptomeningeal inflammation in multiple sclerosis. Neurology 85:18–28

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Okar SV, Reich DS (2022) Routine gadolinium use for MRI follow-up of multiple sclerosis: point-the role of leptomeningeal enhancement. AJR Am J Roentgenol 219:24–25

    PubMed  Google Scholar 

  60. Aymerich FX, Auger C, Alcaide-Leon P et al (2017) Comparison between gadolinium-enhanced 2D T1-weighted gradient-echo and spin-echo sequences in the detection of active multiple sclerosis lesions on 3.0T MRI. Eur Radiol 27:1361–1368

    CAS  PubMed  Google Scholar 

  61. Bapst B, Amegnizin JL, Vignaud A et al (2020) Post-contrast 3D T1-weighted TSE MR sequences (SPACE, CUBE, VISTA/BRAINVIEW, isoFSE, 3D MVOX): technical aspects and clinical applications. J Neuroradiol 47:358–368

    PubMed  Google Scholar 

  62. Hodel J, Outteryck O, Ryo E et al (2014) Accuracy of postcontrast 3D turbo spin-echo MR sequence for the detection of enhanced inflammatory lesions in patients with multiple sclerosis. AJNR Am J Neuroradiol 35:519–523. https://doi.org/10.3174/AJNR.A3795

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Mugler JP, Bao S, Mulkern RV et al (2000) Optimized single-slab three-dimensional spin-echo MR imaging of the brain. Radiology 216:891–899

    PubMed  Google Scholar 

  64. de Panafieu A, Lecler A, Goujon A et al (2023) Contrast-enhanced 3D spin echo T1-weighted sequence outperforms 3D gradient echo T1-weighted sequence for the detection of multiple sclerosis lesions on 3.0 T brain MRI. Invest Radiol 58:314–319

    PubMed  Google Scholar 

  65. Di Perri C, Dwyer MG, Wack DS et al (2009) Signal abnormalities on 1.5 and 3 Tesla brain MRI in multiple sclerosis patients and healthy controls. A morphological and spatial quantitative comparison study. Neuroimage 47:1352–1362

    PubMed  Google Scholar 

  66. Do Amaral LLF, Fragoso DC, da Rocha AJ (2019) Improving acute demyelinating lesion detection: which T1-weighted magnetic resonance acquisition is more sensitive to gadolinium enhancement? Arq Neuropsiquiatr 77:485–492

    Google Scholar 

  67. Bastianello S, Gasperini C, Paolillo A et al (1998) Sensitivity of enhanced MR in multiple sclerosis: effects of contrast dose and magnetization transfer contrast. AJNR Am J Neuroradiol 19:1863–1867

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Algin O, Hakyemez B, Taşkapilioǧlu Ö et al (2010) Imaging of active multiple sclerosis plaques: efficiency of contrast-enhanced magnetization transfer subtraction technique. Diagn Interv Radiol 16:106–111

    PubMed  Google Scholar 

  69. Al-Saeed O, Ismail M, Athyal R, Sheikh M (2011) Fat-saturated post gadolinium T1 imaging of the brain in multiple sclerosis. Acta Radiol 52:570–574

    PubMed  Google Scholar 

  70. Balashov KE, Aung LL, Dhib-Jalbut S, Keller IA (2011) Acute multiple sclerosis lesion: conversion of restricted diffusion due to vasogenic edema. J Neuroimaging 21:202–204

    PubMed  PubMed Central  Google Scholar 

  71. Bugnicourt J-M, Garcia P-Y, Monet P et al (2010) Teaching NeuroImages: marked reduced apparent diffusion coefficient in acute multiple sclerosis lesion. Neurology 74:e87

    PubMed  Google Scholar 

  72. Rosso C, Remy P, Creange A et al (2006) Diffusion-weighted MR imaging characteristics of an acute strokelike form of multiple sclerosis. AJNR Am J Neuroradiol 27:1006–1008

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Rovira A, Pericot I, Alonso J et al (2002) Serial diffusion-weighted MR imaging and proton MR spectroscopy of acute large demyelinating brain lesions: case report. AJNR Am J Neuroradiol 23:989–994

    PubMed  PubMed Central  Google Scholar 

  74. Eisele P, Szabo K, Griebe M et al (2012) Reduced diffusion in a subset of acute MS lesions: a serial multiparametric MRI study. AJNR Am J Neuroradiol 33:1369–1373

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Lucchinetti C, Brück W, Parisi J et al (2000) Heterogeneity of multiple sclerosis lesions: implications for the pathogenesis of demyelination. Ann Neurol 47:707–717

    CAS  PubMed  Google Scholar 

  76. Rigby H, Maloney W, Bhan V (2012) Diagnostic considerations in acute MS lesions with restricted diffusion on MRI. Can J Neurol Sci 39:525–526

    PubMed  Google Scholar 

  77. Tievsky AL, Ptak T, Farkas J (1999) Investigation of apparent diffusion coefficient and diffusion tensor anisotrophy in acute and chronic multiple sclerosis lesions. AJNR Am J Neuroradiol 20:1491–1499

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Balashov KE, Lindzen E (2012) Acute demyelinating lesions with restricted diffusion in multiple sclerosis. Mult Scler 18:1745–1753

    PubMed  PubMed Central  Google Scholar 

  79. Gupta A, Al-Dasuqi K, Xia F et al (2017) The use of noncontrast quantitative MRI to detect gadolinium-enhancing multiple sclerosis brain lesions: a systematic review and meta-analysis. AJNR Am J Neuroradiol 38:1317–1322

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Abdoli M, Chakraborty S, MacLean HJ, Freedman MS (2016) The evaluation of MRI diffusion values of active demyelinating lesions in multiple sclerosis. Mult Scler Relat Disord 10:97–102

    PubMed  Google Scholar 

  81. Sacco S, Caverzasi E, Papinutto N et al (2020) Neurite orientation dispersion and density imaging for assessing acute inflammation and lesion evolution in MS. AJNR Am J Neuroradiol 41:2219–2226

    CAS  PubMed  PubMed Central  Google Scholar 

  82. Caruana G, Pessini LM, Cannella R et al (2020) Texture analysis in susceptibility-weighted imaging may be useful to differentiate acute from chronic multiple sclerosis lesions. Eur Radiol 30:6348–6356

    CAS  PubMed  Google Scholar 

  83. Yu O, Mauss Y, Zollner G et al (1999) Distinct patterns of active and non-active plaques using texture analysis on brain NMR images in multiple sclerosis patients: preliminary results. Magn Reson Imaging 17:1261–1267

    CAS  PubMed  Google Scholar 

  84. Michoux N, Guillet A, Rommel D et al (2015) Texture analysis of T2-weighted MR images to assess acute inflammation in brain MS lesions. PLoS One 10

  85. Zhang Y, Gauthier SA, Gupta A et al (2016) Magnetic susceptibility from quantitative susceptibility mapping can differentiate new enhancing from nonenhancing multiple sclerosis lesions without gadolinium injection. AJNR Am J Neuroradiol 37:1794–1799

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Caruana G, Auger C, Pessini LM et al (2022) SWI as an alternative to contrast-enhanced imaging to detect acute MS lesions. AJNR Am J Neuroradiol 43:534–539

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Vinayagamani S, Sabarish S, Nair SS et al (2021) Quantitative susceptibility-weighted imaging in predicting disease activity in multiple sclerosis. Neuroradiology 63:1061–1069

    PubMed  Google Scholar 

  88. Narayana PA, Coronado I, Sujit SJ et al (2020) Deep learning for predicting enhancing lesions in multiple sclerosis from noncontrast MRI. Radiology 294:398–404

    PubMed  Google Scholar 

  89. Vargas WS, Monohan E, Pandya S et al (2015) Measuring longitudinal myelin water fraction in new multiple sclerosis lesions. NeuroImage Clin 9:369–375

    PubMed  PubMed Central  Google Scholar 

  90. Filippi M, Rocca MA, Martino G et al (1998) Magnetization transfer changes in the normal appearing white matter precede the appearance of enhancing lesions in patients with multiple sclerosis. Ann Neurol 43:809–814

    CAS  PubMed  Google Scholar 

  91. de la Peña MJ, Peña IC, García PG-P et al (2019) Early perfusion changes in multiple sclerosis patients as assessed by MRI using arterial spin labeling. Acta Radiol Open 8:2058460119894214

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The ESMRMB-GREC (Gadolinium Research & Education Committee) is a group of multidisciplinary ESMRMB members, including clinicians, scientists, chemists, physicists, pathologists, and clinical epidemiologists who all share a common interest in the study of gadolinium-based contrast agents in a wide variety of clinical and preclinical conditions. The list of authors includes ESMRMB-GREC members (A. R., F. M. D.; A. J. M., C. A. M., C. A., C. Q.) and members of the Multiple Sclerosis Working Group of the European Society of Neuroradiology (ESNR) (A. R., L. H., J. H., M. S., M. P. W., B. J., T. Y.), who have written, revised and approved the final version of the manuscript

Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

  1. Section of Neuroradiology, Department of Radiology, University Hospital Vall d’Hebron, Autonomous University of Barcelona, Barcelona, Spain

    Àlex Rovira & Cristina Auger

  2. Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy

    Fabio M. Doniselli

  3. Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Vienna, Austria

    Lukas Haider

  4. Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, UK

    Lukas Haider

  5. Department of Radiology, Groupe Hospitalier Paris-Saint Joseph, Paris, France

    Jerome Hodel

  6. Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy

    Mariasavina Severino

  7. Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany

    Mike P. Wattjes

  8. Department of Radiology, Leiden University Medical Center, Leiden, Netherlands

    Aart J. van der Molen

  9. Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam University Medical Center, Amsterdam, Netherlands

    Bas Jasperse

  10. Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy

    Carlo A. Mallio

  11. Research Unit of Radiology, Department of Medicine and Surgery, Università Campus Bio-Medico Di Roma, Rome, Italy

    Carlo A. Mallio

  12. Lysholm Department of Neuroradiology, UCLH National Hospital for Neurology and Neurosurgery, Neuroradiological Academic Unit, UCL Institute of Neurology, London, UK

    Tarek Yousry

  13. Centre for Medical Sciences CISMed, University of Trento, Trento, Italy

    Carlo C. Quattrocchi

  14. Radiology, Multizonal Unit of Rovereto and Arco, APSS Provincia Autonoma Di Trento, Trento, Italy

    Carlo C. Quattrocchi

Authors
  1. Àlex Rovira
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  2. Fabio M. Doniselli
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  3. Cristina Auger
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  4. Lukas Haider
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  5. Jerome Hodel
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  6. Mariasavina Severino
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  7. Mike P. Wattjes
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  8. Aart J. van der Molen
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  9. Bas Jasperse
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  10. Carlo A. Mallio
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  11. Tarek Yousry
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  12. Carlo C. Quattrocchi
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Consortia

on behalf of the ESMRMB-GREC Working Group and of the ESNR Multiple Sclerosis Working Group

Corresponding author

Correspondence to Àlex Rovira.

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Guarantor

The scientific guarantor of this publication is Dr. Rovira.

Conflict of interest

(a) Àlex Rovira serves/ed on scientific advisory boards for Novartis, Sanofi-Genzyme, Icometrix, SyntheticMR, Bayer Healthcare, Biogen, and OLEA Medical, and has received speaker honoraria from Bayer Healthcare, Sanofi-Genzyme, Bracco Imaging, Merck-Serono, Teva Pharmaceutical Industries Ltd, Novartis, Roche, and Biogen.

(b) Fabio Doniselli, Cristina Auger, Jérôme Hodel, Mariasavina Severino, Bas Jasperse, Tarek Yousry, and Carlo Augusto Mallio do not have any conflict of interest to disclosure.

(c) Lukas Haider was supported by an ESNR (European Society of Neuro-Radiology) Research Fellowship and the ECTRIMS-MAGNIMS Research Fellowship and received funding from the Austrian MS Society.

(d) M. P. Wattjes received speaker or consultancy honoraria from Alexion, Bayer Healthcare, Biogen, Biologix, Celgene, Genilac, Imcyse, IXICO, Icometrix, Medison, Merck-Serono, Novartis, Roche, and Sanofi-Genzyme; publication royalties from Springer and Elsevier.

(e) A. J. van der Molen receives consultancy fees from Guerbet as a member of the Expert Group for Gadopiclenol in The Netherlands. He is a member of the ESUR-CMSC whose 2-yearly meetings have received support from Bayer Healthcare, Bracco Imaging, GE HealthCare, and Guerbet.

(f) Carlo Cosimo Quattrocchi has signed speaker contracts with Bayer Healthcare, Bracco Imaging, and Guerbet. He is co-chair of the ESMRMB-GREC Working Group whose yearly meetings have received unconditional support from Bayer Healthcare, Bracco Imaging, GE HealthCare, and Guerbet. He is a member of the ESUR-CMSC whose 2-yearly meetings have received support from Bayer Healthcare, Bracco Imaging, GE HealthCare, and Guerbet.

Statistics and biometry

The authors have significant statistical expertise. No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was not required for this study because this is a review article.

Ethical approval

Institutional Review Board approval was not required because this is a review article.

Study subjects or cohort overlap

No study subject or cohort overlap reported.

Methodology

• Multicentre study

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Rovira, À., Doniselli, F.M., Auger, C. et al. Use of gadolinium-based contrast agents in multiple sclerosis: a review by the ESMRMB-GREC and ESNR Multiple Sclerosis Working Group. Eur Radiol 34, 1726–1735 (2024). https://doi.org/10.1007/s00330-023-10151-y

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