• M Filippi, G Tedeschi, P Pantano, N De Stefano, P Zaratin, M A Rocca, and INNI Network.
• Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy. filippi.massimo@hsr.it.
• Neurol. Sci. 2017 Jun 1; 38 (6): 1029-1038.

AbstractMagnetic 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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