NeuroImage: Clinical (Jan 2022)
The Open-Access European Prevention of Alzheimer’s Dementia (EPAD) MRI dataset and processing workflow
- Luigi Lorenzini,
- Silvia Ingala,
- Alle Meije Wink,
- Joost P.A. Kuijer,
- Viktor Wottschel,
- Mathijs Dijsselhof,
- Carole H. Sudre,
- Sven Haller,
- José Luis Molinuevo,
- Juan Domingo Gispert,
- David M. Cash,
- David L. Thomas,
- Sjoerd B. Vos,
- Ferran Prados,
- Jan Petr,
- Robin Wolz,
- Alessandro Palombit,
- Adam J. Schwarz,
- Gaël Chételat,
- Pierre Payoux,
- Carol Di Perri,
- Joanna M. Wardlaw,
- Giovanni B. Frisoni,
- Christopher Foley,
- Nick C. Fox,
- Craig Ritchie,
- Cyril Pernet,
- Adam Waldman,
- Frederik Barkhof,
- Henk J.M.M. Mutsaerts
Affiliations
- Luigi Lorenzini
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands; Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands; Corresponding author.
- Silvia Ingala
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands; Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Alle Meije Wink
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands; Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Joost P.A. Kuijer
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands; Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Viktor Wottschel
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Mathijs Dijsselhof
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands; Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Carole H. Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK; Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK; Centre for Medical Image Computing, University College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King’s College London, UK
- Sven Haller
- CIMC - Centre d’Imagerie Médicale de Cornavin, Place de Cornavin 18, 1201 Genève, Switzerland; Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
- José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; H. Lundbeck A/S, 2500 Valby, Denmark
- Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain; IMIM (Hospital del Mar Medical Research Institute), Barcelona Spain; Universitat Pompeu Fabra, Barcelona, Spain; CIBER Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
- David M. Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK; UK Dementia Research Institute, University College of London, London, UK
- David L. Thomas
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK; Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology London, UK; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
- Sjoerd B. Vos
- Centre for Medical Image Computing, University College London, London, UK; Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology London, UK
- Ferran Prados
- Nuclear Magnetic Resonance Research Unit, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, London, United Kingdom; Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing, University College London, London, United Kingdom; e-Health Centre, Universitat Oberta de Catalunya, Barcelona, Spain
- Jan Petr
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands; Helmholtz‐Zentrum Dresden‐Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
- Robin Wolz
- IXICO, London, UK; Imperial College London, London, UK
- Alessandro Palombit
- IXICO, London, UK
- Adam J. Schwarz
- Takeda Pharmaceuticals Ltd., Cambridge, MA, USA
- Gaël Chételat
- Université de Normandie, Unicaen, Inserm, U1237, PhIND “Physiopathology and Imaging of Neurological Disorders”, Institut Blood-and-Brain @ Caen-Normandie, Cyceron, 14000 Caen, France
- Pierre Payoux
- Department of Nuclear Medicine, Toulouse CHU, Purpan University Hospital, Toulouse, France; Toulouse NeuroImaging Center, University of Toulouse, INSERM, UPS, Toulouse, France
- Carol Di Perri
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK; UK Dementia Research Institute at Edinburgh, University of Edinburgh, UK
- Giovanni B. Frisoni
- Laboratory Alzheimer’s Neuroimaging & Epidemiology, IRCCS Instituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; University Hospitals and University of Geneva, Geneva, Switzerland
- Christopher Foley
- GE Healthcare Ltd., Little Chalfont, UK
- Nick C. Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Craig Ritchie
- Centre for Dementia Prevention, The University of Edinburgh, Scotland, UK
- Cyril Pernet
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK; Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Denmark
- Adam Waldman
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK; Department of Brain Sciences, Imperial College London, London, UK
- Frederik Barkhof
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands; Institute of Neurology and Healthcare Engineering, University College London, London, UK; Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Henk J.M.M. Mutsaerts
- Dept. of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands; Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium; Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Journal volume & issue
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Vol. 35
p. 103106
Abstract
The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer’s Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences.Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI preprocessing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features — i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia.The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features — Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER), and Image Quality Rate (IQR) — were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses.
