Available online 26 November 2017
Kiran Thapaliya, Viktor Vegh, Steffen Bollmann, Markus Barth
We thank Kieran O’Brien and Surabhi Sood for acquiring the data and the participants involved in this study. KT acknowledges UQI for Ph.D. scholarship. MB acknowledges funding from Australian Research Council Future Fellowship grant FT140100865, and VV from Discovery grant DP140103593. SB acknowledges funding from UQ Postdoctoral Research Fellowship grant. The authors acknowledge the facilities of the National Imaging Facility (NIF) at the Centre for Advanced Imaging, The University of Queensland.
Quantitative assessment of tissue microstructure is important in studying human brain diseases and disorders in which white matter is implicated, as it has been linked to demyelination, re-myelination, and axonal damage in clinical conditions. Ultra-high field magnetic resonance imaging data obtained using a multi-echo gradient echo sequence has been shown to contain information on myelin, axonal and extracellular compartments in white matter. In this study, we aimed to assess the sensitivity of a three-compartment model to estimate the variation of corresponding compartment parameters (water fraction, relaxation time and frequency shift) of the corpus callosum sub-regions, which are known to have different tissue structure. Additionally, we computed the g-ratio using myelin and axonal water fractions and performed a voxel-by-voxel analysis in the corpus callosum. Based on data acquired for ten participants, we show that the myelin compartment water fraction and T2∗ is consistent across the corpus callosum sub-regions, whilst myelin frequency shift varies. The results show that the variation in water fraction, T2∗ and frequency shift for the myelin signal compartment across the corpus callosum is smaller than for the axonal and extracellular signal compartments. The computed g-ratio was comparable to previously published studies in the corpus callosum. Our study suggests that a multi-echo GRE approach in vivo combined with a complex three-compartment model is sensitive to microstructural parameter variations across the human corpus callosum.
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