DTI & rsFMR Imaging Acquisition Strategies for Connectivity Analysis
An Vu1

1San Francisco VA Health Care System

Synopsis

The Human Connectome Project (HCP) relies primarily on resting state functional MR imaging (rfMRI) and diffusion MR imaging (dMRI) to generate detailed maps of brain connectivity. Technical improvements and optimization of these methods have enabled significant increases in the spatial and temporal resolutions of fMRI and dMRI at both 3T and 7T. Ongoing technical developments for acquisition will be presented, targeting higher spatial resolution while maintaining adequate SNR and sensitivity to functional signals.

Abstract

The Human Connectome Project (HCP) uses resting state functional MR imaging (rfMRI), which measures correlations in the temporal fluctuations in an fMRI time series to deduce functional connectivity, and diffusion MR imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture. Advancements in imaging technology have enabled significant increases in the spatial and temporal resolutions achievable (1,2,3). For example, through the use of Simultaneous Multi-Slice (SMS) or Multiband (MB) technology, the HCP has made high resolution, whole brain imaging readily available to the community (e.g. 1.25 mm iso with 5500 ms TR at 3T and 1.05 mm iso with 7000 ms TR at 7T for dMRI (2; Fig 1); and 2 mm iso with 700 ms TR at 3T and 1.6 mm iso with 1000 ms TR at 7T for rsfMRI (3; Figs 2-4)).

Ongoing technical developments and optimization for acquisition facilitate even higher spatial resolution by improving SNR efficiency and sensitivity to functional signals. Fusion of datasets acquired across multiple resolutions (4) provides a method for simultaneously taking advantage of the high SNR of lower spatial resolution data and the fine grain information of the higher spatial resolution data. Similarly, super resolution techniques, such as SLice-Dithered Enhanced Resolution (SLIDER; 5-6), extract sub-millimeter, fine grain spatial information with high SNR by aggregating across multiple acquisitions of low slice-resolution images. The results thus far demonstrate that these approaches represent a significant advance in MR imaging of the human brain to investigate functional and structural connectivity potentially at the level laminar and columnar organization. Future coupling these advancements with next generation scanner hardware (7; e.g. stronger/faster gradients, denser receiver arrays, parallel transmit, etc.) provide a path towards whole brain mesoscale functional and structural connectivity imaging.

Acknowledgements

P30 NS076408/NS/NINDS NIH HHS/United States
P41 EB015894/EB/NIBIB NIH HHS/United States
U54 MH091657/MH/NIMH NIH HHS/United States
R01 MH111444/MH/NIMH NIH HHS/United States
R24 MH106096/MH/NIMH NIH HHS/United States
R44 NS073417/NS/NINDS NIH HHS/United States

References

1. Ugurbil K, Xu J, Auerbach E, Moeller S, Vu AT, Duarte-Carvajalino JM, Lenglet C, Wu X, Schmitter S, Van de Moortele PF, Strupp J, Sapiro G, De Martino F, Wang D, Harel N, Garwood M, Chen L, Feinberg DA, Smith SM, Miller KL, Sotiropoulos SN, Jbabdi Saad, Andersson JL, Behrens TEJ, Glasser MF, Van Essen D, Yacoub E. Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project. Neuroimage, 2013.

2. Vu AT, Auerbach E, Lenglet C, Moeller S, Sotiropoulos SN, Jbabdi S, Anderson J, Yacoub E, Ugurbil K. High resolution whole brain diffusion imaging at 7 T for the Human Connectome Project. NeuroImage, 2015.

3. Vu AT, Jamison K, Glasser MF, Smith SM, Coalson T, Moeller S, Auerbach EJ, Ugurbil K, Yacoub E. Tradeoffs in pushing spatial resolution for fMRI applications at high fields. Neuroimage 2016.

4. Sotiropoulos SN, Hernandez-Fernandez, Vu AT, Andersson JL, Moeller S, Yacoub E, Lenglet C, Ugurbil K, Behrens TEJ, Jbabdi S. Spherical Deconvolution by Data Fusion: Combining 3 and 7 Tesla Diffusion MRI for Improved Fibre Orientation Estimation. Neuroimage 2016.

5. Vu AT, Beckett A, Setsompop K, Feinberg DA. Evaluation of SLIce Dithered Enhanced Resolution Simultaneous MultiSlice (SLIDER-SMS) for human fMRI. Neuroimage 2017.

6. Setsompop K, Fan Q, Stockmann J, Bilgic B, Huang S, Cauley SF, Nummenmaa A, Wang F, Rathi Y, Witzel T, Wald LL. High-resolution in vivo diffusion imaging of the human brain with generalized slice dithered enhanced resolution: Simultaneous multislice (gSlider-SMS). Magn Reson Med 2017.

7. Feinberg D, Vu AT, Beckett A. Pushing the limits of ultra-high resolution human brain imaging with SMS-EPI demonstrated for columnar level fMRI. Neuroimage 2017.

Figures

Figure 1. Gray matter seeded probabilistic tractography examples for a seed in primary visual cortex. Due to the thin and tortuous nature of visual cortex, connectivity analysis is more challenging for the lower 1.25 mm, 3T data (left) than it is for the 1.05 mm, 7T data (right).

Figure 2. GE-EPI images acquired on the same subject using the HCP protocols at 3T and 7T at 2 mm and 1.6 mm isotropic respectively. Also shown are the corresponding subject’s seed based connectivity map for a seed voxel placed in the primary visual cortex. The 7T data supports similar if not stronger correlations than the 3T data. Furthermore, with reduced partial voluming, the 7T data reveals broader connectivity maps, extending into sulcal regions where the cortex is relatively thin.

Figure 3. The number of resting state signal components as a function of field strength and resolution across two subjects. With the same voxel resolution of 2mm, there is a significant increase in the number of signal components at 7T, likely as a result of the increased SNR and CNR of ultra high field. As the voxel size decreases, higher resolution and specificity is gained at a cost of reduced detectability due to decreases in temporal resolution and SNR, particularly when more inplane acceleration (IPAT) is used to mitigate image distortion and blurring.

Figure 4. Reductions in partial volume effects and increases in SNR, fCNR and connectivity measured in the 7T HCP protocol manifests in sharper, stronger, and more well defined dense Connectome connectivity gradients.

Proc. Intl. Soc. Mag. Reson. Med. 25 (2017)