The Open-Access European Prevention of Alzheimer?s Dementia (EPAD) MRI dataset and processing workflow

被引:12
|
作者
Lorenzini, Luigi [1 ]
Ingala, Silvia [1 ]
Wink, Alle Meije [1 ]
Kuijer, Joost P. A. [1 ]
Wottschel, Viktor [1 ]
Dijsselhof, Mathijs [1 ]
Sudre, Carole H. [2 ,3 ,4 ,5 ]
Haller, Sven [6 ,7 ]
Gispert, Juan Domingo [8 ,9 ,10 ,11 ,12 ]
Cash, David M. [13 ]
Thomas, David L. [14 ,15 ]
Vos, Sjoerd B.
Prados, Ferran [16 ,17 ,18 ]
Petr, Jan [19 ]
Wolz, Robin [20 ,21 ]
Palombit, Alessandro [20 ]
Schwarz, Adam J. [22 ]
Chetelat, Gael [23 ]
Payoux, Pierre [24 ,25 ]
Di Perri, Carol [26 ]
Wardlaw, Joanna M. [27 ,28 ]
Frisoni, Giovanni B. [29 ,30 ,31 ]
Foley, Christopher [32 ]
Fox, Nick C. [5 ]
Ritchie, Craig [33 ]
Pernet, Cyril [27 ,34 ]
Waldman, Adam [27 ,35 ]
Barkhof, Frederik [1 ,36 ]
Mutsaerts, Henk J. M. M. [1 ,37 ]
机构
[1] Univ Amsterdam, Dept Radiol & Nucl Med, Amsterdam Neurosci, Med Ctr, Amsterdam, Netherlands
[2] UCL, MRC Unit Lifelong Hlth & Ageing, London, England
[3] UCL, Dementia Res Ctr, Dept Neurodegenerat Dis, Queen Sq Inst Neurol, London, England
[4] UCL, Ctr Med Image Comp, London, England
[5] Kings Coll London, Sch Biomed Engn & Imaging Sci, London, England
[6] CIMC Ctr Imagerie Med Cornavin, Pl Cornavin 18, CH-1201 Geneva, Switzerland
[7] Uppsala Univ, Dept Surg Sci, Radiol, Uppsala, Sweden
[8] Pasqual Maragall Fdn, BBRC, Barcelona, Spain
[9] CIBER Fragil & Envejecimiento Saludable CIBERFES, Madrid, Spain
[10] Hosp del Mar Med Res Inst, IMIM, Barcelona, Spain
[11] Univ Pompeu Fabra, Barcelona, Spain
[12] CIBER Bioingn Biomat & Nanomed CIBER BBN, Madrid, Spain
[13] UCL, UK Dementia Res Inst, London, England
[14] UCL, Neuroradiol Acad Unit, Queen Sq Inst Neurol London, London, England
[15] UCL, Wellcome Ctr Human Neuroimaging, Queen Sq Inst Neurol, London, England
[16] UCL, Queen Sq Multiple Sclerosis Ctr, Nucl Magnet Resonance Res Unit, Queen Sq Inst Neurol, London, England
[17] UCL, Ctr Med Image Comp, Dept Med Phys & Biomed Engn, London, England
[18] Univ Oberta Catalunya, Ehlth Ctr, Barcelona, Spain
[19] Helmholtz Zentrum Dresden Rossendorf, Inst Radiopharmaceut Canc Res, Dresden, Germany
[20] IXICO, London, England
[21] Imperial Coll London, London, England
[22] Takeda Pharmaceut Ltd, Cambridge, MA USA
[23] Univ Normandie, Inst Blood and Brain Caen Normandie, Unicaen, Inserm,U1237,PhIND Physiopathol & Imaging Neurol D, F-14000 Caen, France
[24] Purpan Univ Hosp, Dept Nucl Med, Toulouse CHU, Toulouse, France
[25] Univ Toulouse, Toulouse NeuroImaging Ctr, INSERM, UPS, Toulouse, France
[26] Univ Edinburgh, Ctr Clin Brain Sci, Edinburgh, Scotland
[27] Univ Edinburgh, UK Dementia Res Inst Edinburgh, Edinburgh, Scotland
[28] IRCCS Inst Ctr San Giovanni Dio Fatebenefratelli, Lab Alzheimers Neuroimaging & Epidemiol, Brescia, Italy
[29] Univ Hosp, Geneva, Switzerland
[30] Univ Geneva, Geneva, Switzerland
[31] GE Healthcare Ltd, Little Chalfont, England
[32] Univ Edinburgh, Ctr Dementia Prevent, Edinburgh, Scotland
[33] Imperial Coll London, Dept Brain Sci, London, England
[34] UCL, Inst Neurol & Healthcare Engn, London, England
[35] Univ Ghent, Ghent Inst Funct & Metab Imaging GIfMI, Ghent, Belgium
[36] Copenhagen Univ Hosp, Neurobiol Res Unit, Rigshosp, Copenhagen, Denmark
[37] H Lundbeck & Co AS, DK-2500 Valby, Denmark
基金
英国医学研究理事会; 英国惠康基金; 瑞士国家科学基金会;
关键词
Magnetic resonance imaging; EPAD; Image analysis pipeline; Quality control; BRAIN; ACTIVATION;
D O I
10.1016/j.nicl.2022.103106
中图分类号
R445 [影像诊断学];
学科分类号
100207 ;
摘要
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 pre-processing 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
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页数:14
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