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MGH-USC Human Connectome Project Datasets with Ultra-High b-Value Diffusion MRI

By Qiuyun Fan, Thomas Witzel, Aapo Nummenmaa, Koene R.A. Van Dijk, John D. Van Horn, Michelle K. Drews, Leah H. SomervilleMargaret A. Sheridan, Rosario M. Santillana, Jenna Snyder, Trey Hedden, Emily E. Shaw, Marisa O. Hollinshead, Ville Renvall, Roberta Zanzonico, Boris Keil, Stephen Cauley, Jonathan R. Polimeni, Dylan Tisdall, Randy L. Buckner, Van J. Wedeen, Lawrence L. Wald, Arthur W. Toga, and Bruce R. Rosen | NeuroImage | September 10, 2015


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.

Read the full paper here.