MGH-USC Human Connectome Project datasets with ultra-high b-value diffusion MRI.

Autor:	Fan Q; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Witzel T; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Nummenmaa A; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Van Dijk KRA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA; Harvard University Department of Psychology, Center for Brain Science, Cambridge, MA, USA., Van Horn JD; Laboratory of Neuro Imaging, Institute for Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA., Drews MK; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA; Harvard University Department of Psychology, Center for Brain Science, Cambridge, MA, USA., Somerville LH; Harvard University Department of Psychology, Center for Brain Science, Cambridge, MA, USA., Sheridan MA; Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Santillana RM; Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Snyder J; Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA., Hedden T; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Shaw EE; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Hollinshead MO; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA; Harvard University Department of Psychology, Center for Brain Science, Cambridge, MA, USA., Renvall V; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland., Zanzonico R; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Keil B; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Cauley S; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Polimeni JR; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Tisdall D; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Buckner RL; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA; Harvard University Department of Psychology, Center for Brain Science, Cambridge, MA, USA., Wedeen VJ; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA., Wald LL; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA., Toga AW; Laboratory of Neuro Imaging, Institute for Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA., Rosen BR; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, 149 13th Street, Charlestown 02129, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA. Electronic address: bruce@nmr.mgh.harvard.edu.
Jazyk:	angličtina
Zdroj:	NeuroImage [Neuroimage] 2016 Jan 01; Vol. 124 (Pt B), pp. 1108-1114. Date of Electronic Publication: 2015 Sep 10.
DOI:	10.1016/j.neuroimage.2015.08.075
Abstrakt:	The MGH-USC CONNECTOM MRI scanner housed at the Massachusetts General Hospital (MGH) is a major hardware innovation of the Human Connectome Project (HCP). The 3T CONNECTOM scanner is capable of producing a magnetic field gradient of up to 300 mT/m strength for in vivo human brain imaging, which greatly shortens the time spent on diffusion encoding, and decreases the signal loss due to T2 decay. To demonstrate the capability of the novel gradient system, data of healthy adult participants were acquired for this MGH-USC Adult Diffusion Dataset (N=35), minimally preprocessed, and shared through the Laboratory of Neuro Imaging Image Data Archive (LONI IDA) and the WU-Minn Connectome Database (ConnectomeDB). Another purpose of sharing the data is to facilitate methodological studies of diffusion MRI (dMRI) analyses utilizing high diffusion contrast, which perhaps is not easily feasible with standard MR gradient system. In addition, acquisition of the MGH-Harvard-USC Lifespan Dataset is currently underway to include 120 healthy participants ranging from 8 to 90 years old, which will also be shared through LONI IDA and ConnectomeDB. Here we describe the efforts of the MGH-USC HCP consortium in acquiring and sharing the ultra-high b-value diffusion MRI data and provide a report on data preprocessing and access. We conclude with a demonstration of the example data, along with results of standard diffusion analyses, including q-ball Orientation Distribution Function (ODF) reconstruction and tractography. (Copyright © 2015 Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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