Literature DB >> 23711537

The Human Connectome Project and beyond: initial applications of 300 mT/m gradients.

Jennifer A McNab1, Brian L Edlow, Thomas Witzel, Susie Y Huang, Himanshu Bhat, Keith Heberlein, Thorsten Feiweier, Kecheng Liu, Boris Keil, Julien Cohen-Adad, M Dylan Tisdall, Rebecca D Folkerth, Hannah C Kinney, Lawrence L Wald.   

Abstract

The engineering of a 3 T human MRI scanner equipped with 300 mT/m gradients - the strongest gradients ever built for an in vivo human MRI scanner - was a major component of the NIH Blueprint Human Connectome Project (HCP). This effort was motivated by the HCP's goal of mapping, as completely as possible, the macroscopic structural connections of the in vivo healthy, adult human brain using diffusion tractography. Yet, the 300 mT/m gradient system is well suited to many additional types of diffusion measurements. Here, we present three initial applications of the 300 mT/m gradients that fall outside the immediate scope of the HCP. These include: 1) diffusion tractography to study the anatomy of consciousness and the mechanisms of brain recovery following traumatic coma; 2) q-space measurements of axon diameter distributions in the in vivo human brain and 3) postmortem diffusion tractography as an adjunct to standard histopathological analysis. We show that the improved sensitivity and diffusion-resolution provided by the gradients are rapidly enabling human applications of techniques that were previously possible only for in vitro and animal models on small-bore scanners, thereby creating novel opportunities to map the microstructure of the human brain in health and disease.
Copyright © 2013 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Axon diameter; Consciousness; Corpus callosum; Diffusion MRI; Human connectome; In vivo; Postmortem; Tractography; Traumatic coma

Mesh:

Year:  2013        PMID: 23711537      PMCID: PMC3812060          DOI: 10.1016/j.neuroimage.2013.05.074

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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