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Front. Neurosci. | doi: 10.3389/fnins.2018.00092

On the viability of diffusion MRI-based microstructural biomarkers in ischemic stroke

 Ilaria Boscolo Galazzo1*, Lorenza Brusini1, Silvia Obertino1, Mauro Zucchelli1, Cristina Granziera2 and  Gloria Menegaz1
  • 1Department of Computer Science, University of Verona, Italy
  • 2Department of Neurology and Translational Imaging In Neurology group (ThINk), University Hospital of Basel, Switzerland

Recent tract-based analyses provided evidence for the exploitability of 3D-SHORE microstructural descriptors derived from diffusion MRI (dMRI) in revealing white matter (WM) plasticity. In this work, we focused on the main open issues left: 1) the comparative analysis with respect to classical tensor-derived indices, i.e. Fractional Anisotropy (FA) and Mean Diffusivity (MD); and 2) the ability to detect plasticity processes in grey matter (GM). Although signal modelling in GM is still largely unexplored, we investigated their sensibility to stroke-induced microstructural modifications occurring in the contralateral hemisphere. A more complete picture could provide hints for investigating the interplay of GM and WM modulations.
Ten stroke patients and ten age/gender-matched healthy controls were enrolled in the study and underwent diffusion spectrum imaging (DSI). Acquisitions at three and two time points (tp) were performed on patients and controls, respectively. For all subjects and acquisitions, FA and MD were computed along with 3D-SHORE-based indices [Generalized Fractional Anisotropy (GFA), Propagator Anisotropy (PA), Return To the Axis Probability (RTAP), Return To the Plane Probability (RTPP), and Mean Square Displacement (MSD)]. Tract-based analysis involving the cortical, subcortical and transcallosal motor networks and region-based analysis in GM were successively performed, focusing on the contralateral hemisphere to the stroke.
Reproducibility of all the indices on both WM and GM was quantitatively proved on controls. For tract-based, longitudinal group analyses revealed the highest significant differences across the subcortical and transcallosal networks for all the indices. The optimal regression model for predicting the clinical motor outcome at tp3 included GFA, PA, RTPP and MSD in the subcortical network in combination with the main clinical information at baseline. Region-based analysis in the contralateral GM highlighted the ability of anisotropy indices in discriminating between groups mainly at tp1, while diffusivity indices appeared to be altered at tp2.
3D-SHORE indices proved to be suitable in probing plasticity in both WM and GM, further confirming their viability as a novel family of biomarkers in ischemic stroke in WM and revealing their potential exploitability in GM. Their combination with tensor-derived indices can provide more detailed insights of the different tissue modulations related to stroke pathology.

Keywords: Diffusion propagator, Tensor model, 3D-SHORE model, reproducibility, tract-based, Grey Matter, ischemic stroke

Received: 30 Nov 2017; Accepted: 05 Feb 2018.

Edited by:

Julien Valette, Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), France

Reviewed by:

Matthew D. Budde, Medical College of Wisconsin, United States
Alexandru V. Avram, National Institutes of Health (NIH), United States  

Copyright: © 2018 Boscolo Galazzo, Brusini, Obertino, Zucchelli, Granziera and Menegaz. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Ilaria Boscolo Galazzo, University of Verona, Department of Computer Science, Verona, Italy,