Abstract
Magnetic resonance imaging (MRI) is an important paraclinical tool to diagnose and monitor multiple sclerosis (MS). Conventional MRI measures lack of pathological specificity and are weakly correlated with MS clinical manifestations. Advanced MRI techniques are improving the understanding of the mechanisms underlying tissue injury, repair, and functional adaptation in MS; however, they require careful standardization. The definition of standardized methods for the collection and analysis of advanced MRI techniques is central not only to improve the understanding of disease pathophysiology and evolution, but also to generate research hypotheses, monitor treatment, increase cost-effectiveness and power of clinical trials. We promoted the Italian Neuroimaging Network Initiative (INNI), involving centers and investigators with an International recognized expertise, with the major goal to determine and validate novel MRI biomarkers to be utilized as predictors and/or outcomes in future MS studies. The INNI initiative supported the creation of a centralized repository, where advanced structural and functional MRI scans available at the participating sites, with the related clinical and neuropsychological data, are collected. These data will be used to perform research studies to identify clinical, neuropsychological and imaging biomarkers characteristics of the entire spectrum of MS. INNI will be instrumental to help to define standardized MRI and clinical protocols towards an increasing uptake of personalized interventions for people with MS at a national and international level. Upon approval of the INNI Steering Committee, the data collected in the online database will be shared with any research center detailing specific research proposals on disease pathophysiology or treatment effects.
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References
McDonald WI et al (2001) Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol 50(1):121–127
Polman CH et al (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69(2):292–302
Filippi M et al (2016) MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines. Lancet Neurol 15(3):292–303
Simon JH et al (2006) Standardized MR imaging protocol for multiple sclerosis: consortium of MS Centers consensus guidelines. AJNR Am J Neuroradiol 27(2):455–461
Lovblad KO et al (2010) MR imaging in multiple sclerosis: review and recommendations for current practice. AJNR Am J Neuroradiol 31(6):983–989
Enzinger C et al (2015) Nonconventional MRI and microstructural cerebral changes in multiple sclerosis. Nat Rev Neurol 11(12):676–686
Miller DH et al (2002) Measurement of atrophy in multiple sclerosis: pathological basis, methodological aspects and clinical relevance. Brain 125(Pt 8):1676–1695
Fisher E et al (2008) Gray matter atrophy in multiple sclerosis: a longitudinal study. Ann Neurol 64(3):255–265
Giorgio A et al (2008) Brain atrophy assessment in multiple sclerosis: importance and limitations. Neuroimaging Clin N Am 18(4):675–686 (xi)
Amato MP et al (2007) Association of neocortical volume changes with cognitive deterioration in relapsing-remitting multiple sclerosis. Arch Neurol 64(8):1157–1161
Filippi M, Rocca MA (2009) Functional MR imaging in multiple sclerosis. Neuroimaging Clin N Am 19(1):59–70
Filippi M et al (2013) Imaging resting state brain function in multiple sclerosis. J Neurol 260(7):1709–1713
Zaratin P, Battaglia MA, Abbracchio MP (2014) Nonprofit foundations spur translational research. Trends Pharmacol Sci 35(11):552–555
Rao SM (1991) A manual for the brief, repeatable battery of neuropsychological tests in multiple sclerosis. National Multiple Sclerosis Society, New York
Langdon DW et al (2012) Recommendations for a Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS). Mult Scler 18(6):891–898
Heaton RK, Chelune GJ, Talley JL, Kay GG, Curtis G (1993) Wisconsin card sorting test (WCST) manual revised and expanded. Psychological Assessment Resources Inc, Odessa, FL, USA
Stroop JR (1935) Studies of interference in serial verbal reactions. J Exp Psychol 28:643–662
Vickrey BG et al (1995) A health-related quality of life measure for multiple sclerosis. Qual Life Res 4(3):187–206
Fisk JD et al (1994) Measuring the functional impact of fatigue: initial validation of the fatigue impact scale. Clin Infect Dis 18(Suppl 1):S79–S83
Krupp LB et al (1989) The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol 46(10):1121–1123
Montgomery SA, Asberg M (1979) A new depression scale designed to be sensitive to change. Br J Psychiatry 134:382–389
Solari A et al (2004) Italian version of the Chicago multiscale depression inventory: translation, adaptation and testing in people with multiple sclerosis. Neurol Sci 24(6):375–383
Beck AT, Steer RA, Brown GK (1996) BDI-II: beck depression inventory manual, 2nd edn. Psychological Corporation, San Antonio
Jack CR Jr et al (2008) The Alzheimer’s Disease Neuroimaging Initiative (ADNI): MRI methods. J Magn Reson Imaging 27(4):685–691
Alexander DC, Barker GJ (2005) Optimal imaging parameters for fiber-orientation estimation in diffusion MRI. Neuroimage 27(2):357–367
Cole DM, Smith SM, Beckmann CF (2010) Advances and pitfalls in the analysis and interpretation of resting-state FMRI data. Front Syst Neurosci 4:8
Acknowledgements
This project has been supported by a research Grant from the Fondazione Italiana Sclerosi Multipla (FISM 2013/S/1).
INNI network: Milan: Paola Valsasina, Mauro Sibilia, Paolo Preziosa; Naples: Antonio Gallo, Alvino Bisecco, Renato Docimo; Rome: Nikolaos Petsas, Serena Ruggieri, Costanza Giannì; Siena: Maria Laura Stromillo, Riccardo Tappa Brocci.
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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments.
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Informed consent was obtained from all individual participants included in the study.
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M Filippi is Editor-in-Chief of the Journal of Neurology; serves on a scientific advisory board for Teva Pharmaceutical Industries; has received compensation for consulting services and/or speaking activities from Biogen Idec, Merk-Serono, Novartis, and Teva Pharmaceutical Industries; and receives research support from Biogen Idec, Teva Pharmaceutical Industries, Novartis, Italian Ministry of Health, Fondazione Italiana Sclerosi Multipla, Cure PSP, Alzheimer’s Drug Discovery Foundation (ADDF), the Jacques and Gloria Gossweiler Foundation (Switzerland), and ARiSLA (Fondazione Italiana di Ricerca per la SLA). G. Tedeschi has received compensation for consulting services and/or speaking activities from Bayer Schering Pharma, Biogen Idec, Merck Serono, and Teva Pharmaceutical Industries; and receives research support from Biogen Idec, Merck Serono, and Fondazione Italiana Sclerosi Multipla. Antonio Gallo received honoraria for speaking and travel Grants from Biogen, Sanofi-Aventis, Merck Serono, Genzyme, Teva, Bayer-Schering and Novartis. P. Pantano has received funding for travel from Novartis, Genzyme and Bracco and speaker honoraria from Biogen. N. De Stefano has received honoraria from Schering, Biogen Idec, Teva Pharmaceutical Industries Ltd, Novartis, Genzyme Corporation, Roche, and Merck for consulting services, speaking, and travel support. He serves on advisory boards for Biogen Idec, Merck, Novartis, Genzyme Corporation, and Roche. He has received research Grant support from the Italian MS Society. P. Zaratin works for Fondazione Italiana Sclerosi Multipla. M.A. Rocca received speakers honoraria from Biogen Idec, Novartis, Genzyme, Sanofi-Aventis, Teva and Merk Serono and receives research support from the Italian Ministry of Health and Fondazione Italiana Sclerosi Multipla.
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Members of INNI Network is listed in the acknowledgements.
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Filippi, M., Tedeschi, G., Pantano, P. et al. The Italian Neuroimaging Network Initiative (INNI): enabling the use of advanced MRI techniques in patients with MS. Neurol Sci 38, 1029–1038 (2017). https://doi.org/10.1007/s10072-017-2903-z
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DOI: https://doi.org/10.1007/s10072-017-2903-z