The Open Science Initiative for Perfusion Imaging (OSIPI): Results from the ASL MRI Challenge
Udunna Anazodo1,2, Joana Pinto3, Flora Kennedy McConnell4,5,6, Cassandra Gould van Praag7,8, Henk Mutsaerts9, Aaron Oliver Taylor10, Jan Petr11, Diego Pineda-Ordóñez12, Maria-Eleni Dounavi13, Irène Brumer14, Wei Siang Marcus Chan14, Jack Toner15, Jian Hu15, Logan X. Zhang3, Laura Bell16, Joseph G. Woods17, Moss Y Zhao18, Paula Croal4,5, and Andre Monteiro Paschoal19
1Lawson Health Research Institute,, London, ON, Canada, 2Western University, London, ON, Canada, 3Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom, 4Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, United Kingdom, 5Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom, 6Nottingham Biomedical Research Centre, Queens Medical Centre, Nottingham, United Kingdom, 7Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, 8Department of Psychiatry, University of Oxford, Oxford, United Kingdom, 9Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center,, Amsterdam, Netherlands, 10Gold Standard Phantoms Limited, London, United Kingdom, 11Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical cancer research, Dresden, Germany, 12Department of Radiology, Clinica Del Country, Bogotá, Colombia, 13Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom, 14Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany, 15Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom, 16Genentech, Inc., South San Francisco, CA, United States, 17Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, CA, United States, 18Department of Radiology, Stanford University, Stanford, CA, United States, 19Institute of Radiology and Department of Radiology and Oncology, University of Sao Paulo, Sao Paulo, Brazil
The OSIPI ASL MRI Challenge is an initiative of the ASL community aiming to characterize the variability of CBF quantification arising from different pipelines. The goal of this challenge is to establish best practice in ASL data processing, understand the sources of variability, make ASL analysis more reproducible, and enable fair comparison between studies. Here, we analyzed 3 submitted entries from 7 teams registered in the challenge. The preliminary results showed pipelines based in different programming languages and analysis tools, leading to important variability in the quantitative CBF maps compared to the ground-truth.
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