Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network.

Anna Nigri, Stefania Ferraro, Claudia A M Gandini Wheeler-Kingshott, Michela Tosetti, Alberto Redolfi, Gianluigi Forloni, Egidio D'Angelo, Domenico Aquino, Laura Biagi, Paolo Bosco, Irene Carne, Silvia De Francesco, Greta Demichelis, Ruben Gianeri, Maria Marcella Lagana, Edoardo Micotti, Antonio Napolitano, Fulvia Palesi, Alice Pirastru, Giovanni Savini, Elisa Alberici, Carmelo Amato, Filippo Arrigoni, Francesca Baglio, Marco Bozzali, Antonella Castellano, Carlo Cavaliere, Valeria Elisa Contarino, Giulio Ferrazzi, Simona Gaudino, Silvia Marino, Vittorio Manzo, Luigi Pavone, Letterio S Politi, Luca Roccatagliata, Elisa Rognone, Andrea Rossi, Caterina Tonon, Raffaele Lodi, Fabrizio Tagliavini, Maria Grazia Bruzzone, RIN–Neuroimaging

Frontiers in neurology 2022

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Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures. Copyright © 2022 Nigri, Ferraro, Gandini Wheeler-Kingshott, Tosetti, Redolfi, Forloni, D'Angelo, Aquino, Biagi, Bosco, Carne, De Francesco, Demichelis, Gianeri, Lagana, Micotti, Napolitano, Palesi, Pirastru, Savini, Alberici, Amato, Arrigoni, Baglio, Bozzali, Castellano, Cavaliere, Contarino, Ferrazzi, Gaudino, Marino, Manzo, Pavone, Politi, Roccatagliata, Rognone, Rossi, Tonon, Lodi, Tagliavini, Bruzzone and The RIN–Neuroimaging.

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PMID: 35493836

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