High resolution whole brain diffusion imaging at 7T for the Human Connectome Project

• Published in: NeuroImage (Orlando, Fla.) Vol. 122; pp. 318 - 331
• Main Authors: Vu, A.T., Auerbach, E., Lenglet, C., Moeller, S., Sotiropoulos, S.N., Jbabdi, S., Andersson, J., Yacoub, E., Ugurbil, K.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.11.2015; Elsevier Limited
• Subjects: Brain - anatomy & histology; Brain research; Connectome - methods; Diffusion; Diffusion Magnetic Resonance Imaging - methods; Humans; Image Processing, Computer-Assisted; Signal Processing, Computer-Assisted; Signal-To-Noise Ratio; Studies
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2015.08.004

Mapping structural connectivity in healthy adults for the Human Connectome Project (HCP) benefits from high quality, high resolution, multiband (MB)-accelerated whole brain diffusion MRI (dMRI). Acquiring such data at ultrahigh fields (7T and above) can improve intrinsic signal-to-noise ratio (SNR), but suffers from shorter T2 and T2⁎ relaxation times, increased B1+ inhomogeneity (resulting in signal loss in cerebellar and temporal lobe regions), and increased power deposition (i.e. specific absorption rate (SAR)), thereby limiting our ability to reduce the repetition time (TR). Here, we present recent developments and optimizations in 7T image acquisitions for the HCP that allow us to efficiently obtain high quality, high resolution whole brain in-vivo dMRI data at 7T. These data show spatial details typically seen only in ex-vivo studies and complement already very high quality 3T HCP data in the same subjects. The advances are the result of intensive pilot studies aimed at mitigating the limitations of dMRI at 7T. The data quality and methods described here are representative of the datasets that will be made freely available to the community in 2015. •High quality, ~1mm resolution, whole brain dMRI is achieved at 7T.•B1+, SAR, and motion sensitivity issues are addressed.•High spatial resolution reduces gyral bias in tractography analysis.•Fusion of high angular and high spatial resolution datasets is proposed.