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On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke

Overview of attention for article published in Frontiers in Neuroscience, February 2018
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Title
On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke
Published in
Frontiers in Neuroscience, February 2018
DOI 10.3389/fnins.2018.00092
Pubmed ID
Authors

Ilaria Boscolo Galazzo, Lorenza Brusini, Silvia Obertino, Mauro Zucchelli, Cristina Granziera, Gloria Menegaz

Abstract

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 gray matter (GM). Although signal modeling 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.

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The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 26%
Other 3 9%
Student > Doctoral Student 3 9%
Student > Master 3 9%
Researcher 3 9%
Other 4 11%
Unknown 10 29%
Readers by discipline Count As %
Neuroscience 7 20%
Engineering 5 14%
Medicine and Dentistry 4 11%
Computer Science 3 9%
Physics and Astronomy 2 6%
Other 3 9%
Unknown 11 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 February 2018.
All research outputs
#22,767,715
of 25,382,440 outputs
Outputs from Frontiers in Neuroscience
#10,138
of 11,542 outputs
Outputs of similar age
#304,896
of 344,362 outputs
Outputs of similar age from Frontiers in Neuroscience
#224
of 232 outputs
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