The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke

• Type of Material: Article
• Authors: Sook‐Lei Liew, University of Southern California; Artemis Zavaliangos-Petropulu, University of Southern California; Neda Jahanshad, University of Southern California; Catherine E Lang, Washington Univ; Kathryn S Hayward, University of Melbourne; Keith R Lohse, University of Utah; Julia M Juliano, University of Southern California; Francesca Assogna, IRCCS Santa Lucia Foundation; Lee A Baugh, University of South Dakota; Anup K Bhattacharya, Washington University; Bavrina Bigjahan, University of Southern California; Michael Borich, Emory University; Lara A Boyd, University of British Columbia; Amy Brodtmann, University of Melbourne; Cathrin Buetefisch, Emory University; Winston D Byblow, University of Auckland; Jessica M Cassidy, University of North Carolina; Adriana B Conforto, São Paulo University, São Paulo; Cameron R Craddock, University of Texas Austin; Michael A Dimyan, University of Maryland, Baltimore; Adrienne N Dula, University of Texas Austin; Elsa Ermer, University of Maryland, Baltimore; Mark R Etherton, Massachusetts General Hospital; Kelene A Fercho, University of South Dakota; Chris M Gregory, Medical University of South Carolina; Shahram Hadidchi, Wayne State University; Jess A Holguin, University of Southern California; Darryl H Hwang, University of Southern California; Simon Jung, University of Bern; Steven A Kautz, Medical University of South Carolina; Mohamed Salah Khlif, University of Melbourne; Nima Khoshab, University of California Irvine; Bokkyu Kim, State University of New York Upstate Medical University; Hosung Kim, University of Southern California; Amy Kuceyeski, Weill Cornell Medicine; Martin Lotze, University of Greifswald; Bradley J MacIntosh, University of Toronto; John L Margetis, University of Southern California; Feroze B Mohamed, Thomas Jefferson University; Fabrizio Piras, IRCCS Santa Lucia Foundation; Ander Ramos-Murguialday, Basque Research and Technology Alliance (BRTA); Geneviève Richard, University of Oslo; Pamela Roberts, Cedars Sinai; Andrew D Robertson, University of Waterloo; Jane M Rondina, University College London; Natalia S Rost, Harvard Medical School; Nerses Sanossian, University of Southern California; Nicolas Schweighofer, University of Southern California; Na Jin Seo, Medical University of South Carolina; Mark S Shiroishi, University of Southern California; Surjo R Soekadar, Charité ‐ University Medicine Berlin; Gianfranco Spalletta, IRCCS Santa Lucia Foundation; Cathy M Stinear, University of Auckland; Anisha Suri, University of Pittsburgh; Wai Kwong W Tang, Chinese University of Hong Kong; Gregory T Thielman, University of the Sciences, Philadelphia; Daniela Vecchio, IRCCS Santa Lucia Foundation, Rome; Arno Villringer, Max Planck Inst Human Cognit & Brain Sci; Nick S Ward, University College London; Emilio Werden, University of Melbourne; Lars T Westlye, University of Oslo; Carolee Winstein, University of Southern California; George F Wittenberg, University of Pittsburgh; Kristin A Wong, University of Texas Austin; Chunshui Yu, Tianjin Medical University; Steven C Cramer, University of California Los Angeles; Paul M Thompson, University of Southern California
• Language: English
• Date: 2020-04-20
• Publisher: WILEY
• Publication Version: Final Published Version
• Copyright Statement: © 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1002/hbm.25015
• Title of Journal or Parent Work: HUMAN BRAIN MAPPING
• Volume: 43
• Issue: 1
• Start Page: 129
• End Page: 148
• Grant/Funding Information: American Heart Association; AMORSA, Grant/Award Number: FKZ 16SV7754; Brain and Behavior Research Foundation, Grant/Award Numbers: NARSAD Young Investigator Grant, P&S Fund Investigator; BrightFocus Foundation, Grant/Award Number: A2019052S; Canadian Institutes of Health Research, Grant/Award Number: PJT-153330; Canadian Partnership for Stroke Recovery; Center for Integrated Healthcare, U.S. Department of Veterans Affairs, Grant/Award Numbers: IO1RX001667, N-1667; Deutsche Forschungsgemeinschaft, Grant/Award Numbers: LO795/22-1, LO795/5-1; Einstein Stiftung Berlin; Fortüne-Program of the University of Tübingen, Grant/Award Number: 2422-0-1; H2020 European Research Council, Grant/Award Numbers: ERC-2017-STG-759370, ERC-STG-802998; Health Research Council of New Zealand, Grant/Award Numbers: 09/164R, 11/270, 14/136; Italian Ministry of Health, Grant/Award Number: RC 15-16-17-18-19/A; Leon Levy Foundation Fellowship; Lone Star Stroke Research Consortium; Max-Planck-Gesellschaft; National Health and Medical Research Council, Grant/Award Numbers: 1020526, 1088449, 1094974; National Institutes of Health, Grant/Award Numbers: 5P2CHD086851, HD065438, HD086844, K01HD091283, K23NS088107, P20 GM109040, P2CHD06570, R00HD091375, R01AG059874, R01HD065438, R01HD095137, R01MH117601, R01NR015591, R01NS076348, R01NS082285, R01NS086905, R01NS090677, R01NS115845, R21HD067906, R56-NS100528, U19NS115388, U54EB020403; National Key Research and Development Program of China, Grant/Award Number: 2018YFC1314300; Norges Forskningsråd, Grant/Award Number: 249795; Norwegian ExtraFoundation for Health and Rehabilitation, Grant/Award Number: 2015/FO5146; South-Eastern Norway Regional Health Authority, Grant/Award Number: 2018076; Stroke Association, Grant/Award Number: TSA 2017/04; the Bundesministerium für Bildung und Forschung BMBF MOTORBIC, Grant/Award Number: FKZ 13GW0053
• Keywords: LESION IDENTIFICATION; CORE RECOMMENDATIONS; MRI; SEGMENTATION; Neuroimaging; CORTICAL THICKNESS; RELIABILITY; stroke; REHABILITATION; lesions; ISCHEMIC-STROKE; FUNCTIONAL OUTCOMES; neuroinformatics; Neurosciences & Neurology; UPPER-LIMB FUNCTION; Radiology, Nuclear Medicine & Medical Imaging; Neurosciences; Science & Technology; Life Sciences & Biomedicine; big data; HUMAN CEREBRAL-CORTEX
• Research Categories: Biology, Neuroscience; Health Sciences, Radiology; Health Sciences, Rehabilitation and Therapy

Abstract

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.