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Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients.

Scientific data | 2022

Strong gradient systems can improve the signal-to-noise ratio of diffusion MRI measurements and enable a wider range of acquisition parameters that are beneficial for microstructural imaging. We present a comprehensive diffusion MRI dataset of 26 healthy participants acquired on the MGH-USC 3 T Connectome scanner equipped with 300 mT/m maximum gradient strength and a custom-built 64-channel head coil. For each participant, the one-hour long acquisition systematically sampled the accessible diffusion measurement space, including two diffusion times (19 and 49 ms), eight gradient strengths linearly spaced between 30 mT/m and 290 mT/m for each diffusion time, and 32 or 64 uniformly distributed directions. The diffusion MRI data were preprocessed to correct for gradient nonlinearity, eddy currents, and susceptibility induced distortions. In addition, scan/rescan data from a subset of seven individuals were also acquired and provided. The MGH Connectome Diffusion Microstructure Dataset (CDMD) may serve as a test bed for the development of new data analysis methods, such as fiber orientation estimation, tractography and microstructural modelling.

Pubmed ID: 35042861 RIS Download

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Associated grants

  • Agency: NIMH NIH HHS, United States
    Id: U01 MH093765
  • Agency: NIBIB NIH HHS, United States
    Id: P41 EB030006
  • Agency: NCRR NIH HHS, United States
    Id: S10 RR023043
  • Agency: NINDS NIH HHS, United States
    Id: K23 NS096056
  • Agency: NINDS NIH HHS, United States
    Id: K23 NS078044
  • Agency: NIBIB NIH HHS, United States
    Id: R00 EB015445
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS118187
  • Agency: NCRR NIH HHS, United States
    Id: S10 RR019307
  • Agency: NIBIB NIH HHS, United States
    Id: U01 EB026996
  • Agency: NIBIB NIH HHS, United States
    Id: R01 EB006847
  • Agency: NIBIB NIH HHS, United States
    Id: P41 EB015896
  • Agency: NCRR NIH HHS, United States
    Id: S10 RR023401
  • Agency: NIA NIH HHS, United States
    Id: K99 AG073506

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FreeSurfer (tool)

RRID:SCR_001847

Open source software suite for processing and analyzing human brain MRI images. Used for reconstruction of brain cortical surface from structural MRI data, and overlay of functional MRI data onto reconstructed surface. Contains automatic structural imaging stream for processing cross sectional and longitudinal data. Provides anatomical analysis tools, including: representation of cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from rest of brain, skull stripping, B1 bias field correction, nonlinear registration of cortical surface of individual with stereotaxic atlas, labeling of regions of cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures.Operating System: Linux, macOS.

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