Elsevier

NeuroImage

Volume 124, Part B, 1 January 2016, Pages 1108-1114
NeuroImage

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

https://doi.org/10.1016/j.neuroimage.2015.08.075Get rights and content

Highlights

  • Ultra high b-value diffusion MRI data were acquired on the MGH–USC CONNECTOM scanner.

  • We provided information about data access and the data sharing repositories.

  • We described the imaging protocols and data pre-processing steps in details.

  • We demonstrated diffusion data quality using q-ball ODF and streamline tractography.

Abstract

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.

Introduction

The NIH Blueprint for Neuroscience Research has funded the MGH–USC consortium of the Human Connectome Project (HCP) to build a one of a kind CONNECTOM scanner. It is based on a Siemens Skyra 3T platform (Siemens Healthcare, Erlangen Germany) and is equipped with a novel gradient system that is capable of a maximum strength of 300 mT/m (Fan et al., 2014, Setsompop et al., 2013). This is the major hardware component of HCP-driven MR technology innovation. The strong gradient system greatly shortens the time spent on diffusion encoding and decreases signal loss due to T2 decay. We have collected one dataset of 35 healthy adults and are in the process of acquiring a second dataset to include 120 healthy participants spanning a wide age range (8 to 90 years old).

The first dataset, referred to as the MGH–USC Adult Diffusion Dataset, demonstrates the capability of the innovative CONNECTOM gradient system for in vivo human diffusion MRI (dMRI). In each of the 35 participants, dMRI data with a broad range of b-values (1000, 3000, 5000 and 10,000 s/mm2) were collected. The data were minimally preprocessed, and are publically available through open access data repositories. It is a unique, openly available source of high angular and high spatial resolution dMRI data with high diffusion weighting. One purpose of acquiring and sharing the data is to facilitate studies of new advanced diffusion analysis methods that may rely on contrasts from ultra-high diffusion weighting (i.e. high b-values) to resolve fine details of white matter microstructure perhaps not appreciable with standard gradient MR systems. For this purpose, the data acquisition scheme of the MGH–USC Adult Diffusion Dataset was not tailored specifically for any particular analysis method; rather, it was designed with the intent to allow for as much flexibility for future analyses as possible.

Collection of a second sample with ultra-high diffusion weighting MRI data, referred to as the MGH–Harvard–USC Lifespan Dataset, is currently underway and will be shared in the near future. For this second dataset a total of 120 healthy participants ranging from 8 to 90 years old will be scanned to demonstrate the feasibility of ultra-high b-value dMRI across a wide age range and to prepare a reference sample for future studies in patient populations that include children, adolescents, and older adults. In addition to exploring an age range that includes differences in brain development and atrophy, the groups included also vary in their tendency to move during the acquisition, allowing methodological and feasibility explorations of motion effects on measures of white matter microstructure that may be common in studies comparing age groups and patient groups.

All data from the MGH–USC HCP described in this report are publically available through the Laboratory of Neuro Imaging Image Data Archive (LONI IDA) and the WU–Minn Connectome Database (ConnectomeDB). The LONI IDA (https://ida.loni.usc.edu) is an integrated environment for safely archiving, querying and visualizing imaging data utilizing a web-browser interface. Specifically, the LONI IDA is a large-scale archive for neuroimaging, genetics, and phenomic datasets which serves a variety of multi-site imaging programs including the Alzheimer's Disease Neuroimaging Initiative (Toga et al., 2010) and the Michael J. Fox Foundation sponsored Parkinson's Progressive Markers Initiative (http://www.ppmi-info.org), and other major neuroimaging programs. All of the data from the MGH–USC HCP CONNECTOM scanner, described below, are freely available for access, download, or direct workflow submission using LONI Pipeline (Dinov et al., 2010) by any user after a permission request procedure (http://www.humanconnectomeproject.org/data). The WU–Minn HCP consortium maintains the ConnectomeDB (https://db.humanconnectome.org) to exclusively manage HCP data (Marcus et al., 2013) (see Hodge et al., 2015 for more detailed information about the ConnectomeDB in the same issue).

The MGH–USC Adult Diffusion Dataset (N = 35) collection is complete and minimally preprocessed. Both the unprocessed and minimally preprocessed data are available for download through LONI-IDA and ConnectomeDB. Acquisition of the MGH–Harvard–USC Lifespan Dataset is currently underway and, upon the completion of data collection, data processing and quality assessment, unprocessed and minimally preprocessed data will be added to both the LONI IDA and ConnectomeDB repositories for public access. The purpose of the present article is to describe the MGH–USC Adult Diffusion Dataset in detail and to give a flavor of what is to come in terms of the MGH–Harvard–USC Lifespan Dataset.

Section snippets

Participants

All participants provided in the MGH–USC Adult Diffusion Dataset were scanned on the 3T CONNECTOM MRI scanner (see (Setsompop et al., 2013) for an overview) housed at the Athinoula A. Martinos Center for Biomedical Imaging at MGH. A custom-made 64-channel phased array head coil was used for signal reception (Keil et al., 2013). No data were collected on other imaging modalities.

Thirty-five healthy adults participated in this study (16 Females, 20–59 years old; mean age = 31.1 years old). All

MGH–Harvard–USC Lifespan Dataset (target N = 120)

Data collection for the MGH–Harvard–USC Lifespan Dataset is underway. T1w, T2w, resting-state fMRI, and dMRI data of 120 healthy study participants ranging from children to older adults will be shared. The specific age ranges for each group and target sample sizes are listed in Table 4. Extensive cognitive or neuropsychological data will not be available for this feasibility study; however, basic demographic variables will be publically available, including age, gender, years of education,

Data access

The MGH–USC Adult Diffusion Dataset is openly available. Users must register with either LONI IDA (https://ida.loni.usc.edu/services/NewUser.jsp) or ConnectomeDB (https://db.humanconnectome.org/app/template/Login.vm) to get access to the data. All imaging and demographic data are directly available for download from either of the two repositories. Data Usage Agreements are required (for more details on the Data Usage Agreement with LONI IDA, see //ida.loni.usc.edu/collaboration/access/appLicense.jsp

MGH–USC Adult Diffusion Datasets

Here we briefly illustrate the data type and quality of the MGH–USC Adult Diffusion Datasets, using one example dataset.

Fig. 3 shows an axial plane of the T1w and T2w scans, along with the mask used for ear and face stripping. Data shown were corrected for gradient nonlinearity distortions.

Fig. 4 shows an axial plane of the preprocessed dMRI data with diffusion weighting applied along the same direction but with different gradient strengths.

Fig. 5 shows the q-ball Orientation Distribution

Conclusion

Based on the 3T Siemens CONNECTOM system, the MGH–USC HCP datasets serve as a unique openly available source of high angular and spatial resolution dMRI data with b-values up to 10,000 s/mm2. The ongoing MGH–Harvard–USC Lifespan study will further add to the database by providing data across the age span from children to older adults.

Acknowledgments

The authors thank Dr. Emmanuel Caruyer for providing help with b-vector calculations. The work is supported by funding from the National Institutes of Health Blueprint Initiative for Neuroscience Research Grant U01MH093765, NIH NIBIB Grant K99EB015445, NIH NIA Grant P50AG005134, NIH NIA Grant K01AG040197, and the Instrumentation Grants 1S10RR023401, 1S10RR019307, and 1S10RR023043. This work was also supported by NIH Grants 5P41 EB015922-16 and 1U54EB020406-01 to AWT.

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