title: Towards higher sensitivity and stability of axon diameter estimation with diffusion-weighted MRI.
abstract: Diffusion-weighted MRI is an important tool for in vivo and non-invasive axon morphometry. The ActiveAx technique utilises an optimised acquisition protocol to infer orientationally invariant indices of axon diameter and density by fitting a model of white matter to the acquired data. In this study, we investigated the factors that influence the sensitivity to small-diameter axons, namely the gradient strength of the acquisition protocol and the model fitting routine. Diffusion-weighted ex. vivo images of the mouse brain were acquired using 16.4-T MRI with high (Gmax of 300 mT/m) and ultra-high (Gmax of 1350 mT/m) gradient strength acquisitions. The estimated axon diameter indices of the mid-sagittal corpus callosum were validated using electron microscopy. In addition, a dictionary-based fitting routine was employed and evaluated. Axon diameter indices were closer to electron microscopy measures when higher gradient strengths were employed. Despite the improvement, estimated axon diameter indices (a lower bound of ~ 1.8 μm) remained higher than the measurements obtained using electron microscopy (~1.2 μm). We further observed that limitations of pulsed gradient spin echo (PGSE) acquisition sequences and axonal dispersion could also influence the sensitivity with which axon diameter indices could be estimated. Our results highlight the influence of acquisition protocol, tissue model and model fitting, in addition to gradient strength, on advanced microstructural diffusion-weighted imaging techniques. © 2016 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.
authors.affiliation: Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia.|Queensland Brain Institute, The University of Queensland, Brisbane, Australia.
authors.forename: Farshid
authors.initials: F
authors.lastname: Sepehrband
authors.affiliation: Department of Computer Science & Centre for Medical Image Computing, University College London, London, UK.
authors.forename: Daniel C
authors.initials: DC
authors.lastname: Alexander
authors.affiliation: Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia.
authors.forename: Nyoman D
authors.initials: ND
authors.lastname: Kurniawan
authors.affiliation: Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia.
authors.forename: David C
authors.initials: DC
authors.lastname: Reutens
authors.affiliation: Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia.|School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia.|Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.|Faculty of Information Engineering, Southwest University of Science and Technology, Mianyang, China.
authors.forename: Zhengyi
authors.initials: Z
authors.lastname: Yang
mesh_terms: D000818:Animals; D001369:Axons / Q000378:metabolism* / Q000648:ultrastructure; D003198:Computer Simulation; D003337:Corpus Callosum / Q000648:ultrastructure; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008810:Mice, Inbred C57BL; D008962:Models, Theoretical; D009457:Neuroglia / Q000378:metabolism / Q000648:ultrastructure; D013113:Spin Labels
chemical_list: D013113:Spin Labels
keywords: ActiveAx; axon diameter index; diffusion-weighted MRI; electron microscopy; histological validation; mouse corpus callosum; ultra-high gradient strength