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Abstract #4514

MRI quality data assessment in the Italian IRCCS advanced neuroimaging network using ACR phantoms

Fulvia Palesi1, Anna Nigri2, Domenico Aquino2, Ruben Gianeri2, Alice Pirastru3, Marcella Laganà3, Laura Biagi4, Michela Tosetti4, Maria Grazia Bruzzone2, Claudia A.M. Gandini Wheeler-Kingshott5,6,7, and The Italian IRCCS advanced neuroimaging network8

1Neuroradiology Unit, Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy, 2Neuroradiology, Fondazione I.R.C.C.S. Istituto Neurologico Carlo Besta, Milan, Italy, 3IRCCS Fondazione Don Carlo Gnocchi, Milano, Italy, 4IRCCS Fondazione Stella Maris, Pisa, Italy, 5Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom, 6Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy, 7Brain MRI 3T Research Center, IRCCS Mondino Foundation, Pavia, Italy, 8The Italian IRCCS advanced neuroimaging network, Milan, Italy

Generating big-data is becoming imperative with the advent of machine learning. Neuroimaging networks respond to this need. Italian Research Neurological Institutes have formed an advanced neuroimaging network to develop protocols for multisite studies. The present work reports on ACR phantom data across sites and evaluates accuracy and longitudinal reproducibility of: uniformity and ghosting, geometric accuracy, slice thickness, high-contrast and low-contrast object detectability. Our findings show that uniformity, geometric accuracy, low-contrast object detectability are measures that failed at some sites. We intervened to correct these issues improving protocol quality and scanner stability, establishing levels of precision relevant for future multicentre studies in quantitative imaging.

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