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. 2014:2014:742-5.
doi: 10.1109/EMBC.2014.6943697.

Assessment of white matter microstructure in stroke patients using NODDI

Ganesh Adluru, Yaniv Gur, Jeffrey S Anderson, Lorie G Richards, Nagesh Adluru, Edward V R DiBella

Assessment of white matter microstructure in stroke patients using NODDI

Ganesh Adluru et al. Annu Int Conf IEEE Eng Med Biol Soc. 2014.

Abstract

Diffusion weighted imaging (DWI) is widely used to study changes in white matter following stroke. In various studies employing diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI) modalities, it has been shown that fractional anisotropy (FA), mean diffusivity (MD), and generalized FA (GFA) can be used as measures of white matter tract integrity in stroke patients. However, these measures may be non-specific, as they do not directly delineate changes in tissue microstructure. Multi-compartment models overcome this limitation by modeling DWI data using a set of indices that are directly related to white matter microstructure. One of these models which is gaining popularity, is neurite orientation dispersion and density imaging (NODDI). This model uses conventional single or multi-shell HARDI data to describe fiber orientation dispersion as well as densities of different tissue types in the imaging voxel. In this paper, we apply for the first time the NODDI model to 4-shell HARDI stroke data. By computing NODDI indices over the entire brain in two stroke patients, and comparing tissue regions in ipsilesional and contralesional hemispheres, we demonstrate that NODDI modeling provides specific information on tissue microstructural changes. We also introduce an information theoretic analysis framework to investigate the non-local effects of stroke in the white matter. Our initial results suggest that the NODDI indices might be more specific markers of white matter reorganization following stroke than other measures previously used in studies of stroke recovery.

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Figures

Fig. 1
Fig. 1
Manually drawn ROIs encompassing stroke region overlaid on a diffusion weighted image at b=2000 s·mm−2 in one axial slice. Corresponding contralesional ROIs are also shown. Red for ipsilesional hemisphere and green for contralesional hemisphere. Axial and coronal views are shown in two subjects.
Fig. 2
Fig. 2
Microstructural and diffusion measures in two subjects. The blue arrows point to stroke regions in both subjects.
Fig. 3
Fig. 3
JH-ICBM white matter labels warped into the individual subject spaces using ANTS are shown on their respective FA maps.
Fig. 4
Fig. 4
The density estimates of the microstructural measure distributions for ODI, ND, CSF as well as MD, FA and GFA obtained from stroke and contralesional ROIs in the two subjects. The symmetrized KLD (sKLD) values are shown in each facet. The range for all the measures is 0 to 1. MD values are in mm2·s−1 while the other indices are in arbitrary units (a.u.).
Fig. 5
Fig. 5
The non-local effects of stroke on the 21 tracts obtained from the JH-ICBM template. The tract names are ordered in reverse alphabetical order.
See this image and copyright information in PMC

References

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