TY - JOUR
T1 - The Open-Access European Prevention of Alzheimer's Dementia (EPAD) MRI dataset and processing workflow
AU - EPAD consortium
AU - Lorenzini, Luigi
AU - Ingala, Silvia
AU - Wink, Alle Meije
AU - Kuijer, Joost P. A.
AU - Wottschel, Viktor
AU - Dijsselhof, Mathijs
AU - Sudre, Carole H.
AU - Haller, Sven
AU - Molinuevo, José Luis
AU - Gispert, Juan Domingo
AU - Cash, David M.
AU - Thomas, David L.
AU - Vos, Sjoerd B.
AU - Prados, Ferran
AU - Petr, Jan
AU - Wolz, Robin
AU - Palombit, Alessandro
AU - Schwarz, Adam J.
AU - Chételat, Gaël
AU - Payoux, Pierre
AU - di Perri, Carol
AU - Wardlaw, Joanna M.
AU - Frisoni, Giovanni B.
AU - Foley, Christopher
AU - Fox, Nick C.
AU - Ritchie, Craig
AU - Pernet, Cyril
AU - Waldman, Adam
AU - Barkhof, Frederik
AU - Mutsaerts, Henk J. M. M.
N1 - Funding Information: EPAD is supported by the EU/EFPIA Innovative Medicines Initiative Joint Undertaking EPAD grant agreement 115736. Funding Information: GBF is funded by: A.P.R.A. - Association Suisse pour la Recherche sur la Maladie d’Alzheimer, Genève; Fondation Segré, Genève; Ivan Pictet, Genève; Fondazione Agusta, Lugano; Fondation Chmielewski, Genève; Swiss National Science Foundation; and VELUX Foundation. Funding Information: DMC is supported by the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society, and Alzheimer’s Research UK, as well as Alzheimer's Research UK (ARUK‐PG2017‐1946) and the UCL/UCLH NIHR Biomedical Research Centre. Funding Information: DLT is supported by the UCLH NIHR Biomedical Research Centre, the Wellcome Trust (Centre award 539208), and Alzheimer’s Research UK (ARUK-NAS2016B-2) Funding Information: JMW is supported by the UK Dementia Research Institute Ltd (funded by the UK MRC, ARUK, and Alzheimer Society) and the Fondation Leducq (16 CVD 05). Funding Information: NCF is supported by the NIHR UCLH Biomedical Research Centre and the UK Dementia Research Institute at UCL Funding Information: This work is part of the EPAD LCS (European Prevention of Alzheimer's Dementia Longitudinal Cohort Study). The authors would like to express their gratitude to the EPAD-LCS participants, without whom this research would have not been possible. EPAD is supported by the EU/EFPIA Innovative Medicines Initiative Joint Undertaking EPAD grant agreement 115736. FB is supported by the NIHR UCLH Biomedical Research Centre, NCF is supported by the NIHR UCLH Biomedical Research Centre and the UK Dementia Research Institute at UCL, DLT is supported by the UCLH NIHR Biomedical Research Centre, the Wellcome Trust (Centre award 539208), and Alzheimer's Research UK (ARUK-NAS2016B-2), DMC is supported by the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer's Society, and Alzheimer's Research UK, as well as Alzheimer's Research UK (ARUK‐PG2017‐1946) and the UCL/UCLH NIHR Biomedical Research Centre. GBF is funded by: A.P.R.A. - Association Suisse pour la Recherche sur la Maladie d'Alzheimer, Genève; Fondation Segré, Genève; Ivan Pictet, Genève; Fondazione Agusta, Lugano; Fondation Chmielewski, Genève; Swiss National Science Foundation; and VELUX Foundation. HM is supported by the Dutch Heart Foundation (2020T049), by the Eurostars-2 joint program with co-funding from the European Union Horizon 2020 research and innovation program, provided by the Netherlands Enterprise Agency (RvO), and by the EU Joint Program for Neurodegenerative Disease Research, provided by the Netherlands Organisation for Health Research and Development and Alzheimer Nederland. JMW is supported by the UK Dementia Research Institute Ltd (funded by the UK MRC, ARUK, and Alzheimer Society) and the Fondation Leducq (16 CVD 05). JDG holds the “Ramón y Cajal” fellowship RYC-2013-13054. Funding Information: HM is supported by the Dutch Heart Foundation (2020T049), by the Eurostars-2 joint program with co-funding from the European Union Horizon 2020 research and innovation program, provided by the Netherlands Enterprise Agency (RvO), and by the EU Joint Program for Neurodegenerative Disease Research, provided by the Netherlands Organisation for Health Research and Development and Alzheimer Nederland. Publisher Copyright: © 2022 The Author(s)
PY - 2022/1/1
Y1 - 2022/1/1
N2 - 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.
AB - 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.
KW - EPAD
KW - Image analysis pipeline
KW - Magnetic resonance imaging
KW - Multi-modal data integration
KW - Quality control
UR - http://www.scopus.com/inward/record.url?scp=85134357838&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.nicl.2022.103106
DO - https://doi.org/10.1016/j.nicl.2022.103106
M3 - Article
C2 - 35839659
SN - 2213-1582
VL - 35
JO - NeuroImage: Clinical
JF - NeuroImage: Clinical
M1 - 103106
ER -