Ensemble average propagator-based detection of microstructural alterations after stroke.

Details

Serval ID
serval:BIB_7473330D38CF
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Ensemble average propagator-based detection of microstructural alterations after stroke.
Journal
International journal of computer assisted radiology and surgery
Author(s)
Brusini L., Obertino S., Galazzo I.B., Zucchelli M., Krueger G., Granziera C., Menegaz G.
ISSN
1861-6429 (Electronic)
ISSN-L
1861-6410
Publication state
Published
Issued date
09/2016
Peer-reviewed
Oui
Volume
11
Number
9
Pages
1585-1597
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
New analytical reconstruction techniques of diffusion weighted signal have been proposed. A previous work evidenced the exploitability of some indices derived from the simple harmonic oscillator-based reconstruction and estimation (3D-SHORE) model as numerical biomarkers of neural plasticity after stroke. Here, the analysis is extended to two additional indices: return to the plane/origin (RTPP/RTOP) probabilities. Moreover, several motor networks were introduced and the results were analyzed at different time scales.
Ten patients underwent three diffusion spectrum imaging (DSI) scans [1 week (tp1), 1 month (tp2) and 6 months (tp3) after stroke]. Ten matched controls underwent two DSI scans 1 month apart. 3D-SHORE was used for reconstructing the signal and the microstructural indices were derived. Tract-based analysis was performed along motor cortical, subcortical and transcallosal networks in the contralesional area.
The optimal intra-class correlation coefficient (ICC) was obtained in the subcortical loop for propagator anisotropy (ICC [Formula: see text] 0.96), followed by generalized fractional anisotropy (ICC [Formula: see text] 0.94). The new indices reached the highest stability in the transcallosal network and performed well in the cortical and subcortical networks with the exception of RTOP in the cortical loop (ICC [Formula: see text] 0.59). They allowed discriminating patients from controls at the majority of the timescales. Finally, the regression model using indices calculated along the subcortical loop at tp1 resulted in the best prediction of clinical outcome.
The whole set of microstructural indices provide measurements featuring high precision. The new indices allow discriminating patients from controls in all networks, except for RTPP in the cortical loop. Moreover, the 3D-SHORE indices in subcortical connections constitute a good regression model for predicting the clinical outcome at 6 months, supporting their suitability as numerical biomarkers for neuronal plasticity after stroke.

Keywords
Anisotropy, Brain/pathology, Diffusion Magnetic Resonance Imaging/methods, Female, Humans, Male, Middle Aged, Stroke/diagnosis
Pubmed
Create date
07/07/2016 14:31
Last modification date
20/08/2019 15:32
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