1. Power estimation for non-standardized multisite studies
- Author
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Till Sprenger, Massimo Filippi, David A. Hafler, Sara Llufriu, Gina Kirkish, Mona K. Beyer, Pablo Villoslada, Xavier Montalban, Sandra D'Alfonso, Anisha Keshavan, Philippe Demaerel, Claus Zimmer, Pradip M. Pattany, Mike P. Wattjes, Christiane Graetz, Ludwig Kappos, Alessandro Carriero, Jorge R. Oksenberg, Jacob L. McCauley, Roland G. Henry, Alyssa H. Zhu, Adriane Gröger, Michael Amann, An Goris, Laura Gaetano, Antje Bischof, Filippo Martinelli-Boneschi, Hanne F. Harbo, Sergiu Groppa, Alessandro Stecco, Stefano Magon, Margaret A. Pericak-Vance, Daniel Pelletier, Frauke Zipp, Regina Schlaeger, Alex Rovira, Nico Papinutto, Friedemann Paul, Albert Saiz, Maria A. Rocca, Isabelle Cournu-Rebeix, William A. Stern, Howard L. Weiner, Bernhard Hemmer, Russell T. Shinohara, Manuel Comabella, Bénédicte Dubois, Rohit Bakshi, Jason C. Crane, Vinzenz Fleischer, Bernard M. J. Uitdehaag, Jens Wuerfel, Stephen L. Hauser, Mark Mühlau, Kesshi M. Jordan, Bertrand Fontaine, Keshavan, A, Paul, F, Beyer, Mk, Zhu, Ah, Papinutto, N, Shinohara, Rt, Stern, W, Amann, M, Bakshi, R, Bischof, A, Carriero, A, Comabella, M, Crane, Jc, D'Alfonso, S, Demaerel, P, Dubois, B, Filippi, M, Fleischer, V, Fontaine, B, Gaetano, L, Goris, A, Graetz, C, Gröger, A, Groppa, S, Hafler, Da, Harbo, Hf, Hemmer, B, Jordan, K, Kappos, L, Kirkish, G, Llufriu, S, Magon, S, Martinelli-Boneschi, F, Mccauley, J, Montalban, X, Muhlau, M, Pelletier, D, Pattany, Pm, Pericak-Vance, M, Rebeix, I, Rocca, M, Rovira, A, Schlaeger, R, Saiz, A, Sprenger, T, Stecco, A, Uitdehaag, Bm, Villoslada, P, Wattjes, Mp, Weiner, H, Wuerfel, J, Zimmer, C, Zipp, F, International Multiple Sclerosis Genetics, Consortium, Hauser, S, Oksenberg, Jr, Henry, Rg, Bioengineering Graduate Program (joint degree with UCSF), Department of Bioengineering [Berkeley], University of California [Berkeley], University of California-University of California-University of California [Berkeley], University of California-University of California-University of California [San Francisco] (UCSF), University of California, Department of Neurology [San Francisco], University of California [San Francisco] (UCSF), University of California-University of California, Max Delbrueck Centre for Molecular Medicine, NeuroCure Clinical Research Center and Clinical and Experimental Multiple Sclerosis Research Center, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Department of Radiology and Nuclear Medicine, Oslo University Hospital [Oslo], Department of Biostatistics and Epidemiology [Philadelphia], Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia], Department of Neurology [Suisse], University Hospital Basel [Basel], Medical Image Analysis Center (MIAC AG), Brigham and Women's Hospital [Boston], Clinical Immunology, Department of Translational Medicine, UPO University, Vall d'Hebron University Hospital [Barcelona], Department of Radiology and Biomedical Imaging [San Francisco], Department of Health Sciences, UPO University, Department of Radiology[Leuven], University Hospitals Leuven [Leuven], Department of Neurosciences Leuven, University of Leuven K.U.Leuven, Institute of Experimental Neurology, Milan, University Medical Centre of the Johannes Gutenberg University Mainz, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), University Medical Centre of the Johannes Gutenberg-University Mainz, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Departments of Neurology and Immunobiology [Yale], Yale University School of Medicine, Department of Neurology [Oslo], Akershus University Hospital [Lørenskog], Department Neurology of the Klinikum rechts der Isar, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Munich Cluster of Systems Neurology (SyNery), Center for Neuroimmunology, Service of Neurology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Neuroimaging Research Unit, Scientific Institute and University Hospital San Raffaele, Milan, John P. Hussman Institute for Human Genomics, University of Miami Leonard M. Miller School of Medicine (UMMSM), TUM–Neuroimaging Center, Department of Radiology [Miami], DKD Helios Klinik Wiesbaden, Section of Neuroradiology [Novara], Maggiore Hospital, VU University Medical Center [Amsterdam], Dept Neuroradiology [Munich], Klinikums rechts der Isar, University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC)-University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC)-University of California [San Francisco] (UC San Francisco), University of California (UC), University of California [San Francisco] (UC San Francisco), University of California (UC)-University of California (UC), University of Pennsylvania-University of Pennsylvania, Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU), Yale School of Medicine [New Haven, Connecticut] (YSM), Neurology, Amsterdam Neuroscience - Neuroinfection & -inflammation, and Radiology and nuclear medicine
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Computer science ,Cognitive Neuroscience ,computer.software_genre ,Sensitivity and Specificity ,050105 experimental psychology ,Imaging phantom ,Article ,Set (abstract data type) ,03 medical and health sciences ,0302 clinical medicine ,Distortion ,Image Interpretation, Computer-Assisted ,Calibration ,medicine ,[INFO.INFO-IM]Computer Science [cs]/Medical Imaging ,Humans ,0501 psychology and cognitive sciences ,Segmentation ,Computer Simulation ,10. No inequality ,Scaling ,Models, Statistical ,medicine.diagnostic_test ,05 social sciences ,Contrast (statistics) ,Brain ,Reproducibility of Results ,Magnetic resonance imaging ,Equipment Design ,Scale factor ,Image Enhancement ,Magnetic Resonance Imaging ,United States ,Equipment Failure Analysis ,Europe ,Neurology ,Ordinary least squares ,Data mining ,Function and Dysfunction of the Nervous System ,Artifacts ,computer ,030217 neurology & neurosurgery ,Algorithms - Abstract
A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions. publisher: Elsevier articletitle: Power estimation for non-standardized multisite studies journaltitle: NeuroImage articlelink: http://dx.doi.org/10.1016/j.neuroimage.2016.03.051 content_type: article copyright: © 2016 The Authors. Published by Elsevier Inc. ispartof: NeuroImage vol:134 pages:281-294 ispartof: location:United States status: published
- Published
- 2016