Diffusion kurtosis as an in vivo imaging marker for reactive astrogliosis in traumatic brain injury

Abstract

Diffusion Kurtosis Imaging (DKI) provides quantifiable information on the non-Gaussian behavior of water diffusion in biological tissue. Changes in water diffusion tensor imaging (DTI) parameters and DKI parameters in several white and gray matter regions were investigated in a mild controlled cortical impact (CCI) injury rat model at both the acute (2 h) and the sub-acute (7 days) stages following injury. Mixed model ANOVA analysis revealed significant changes in temporal patterns of both DTI and DKI parameters in the cortex, hippocampus, external capsule and corpus callosum. Post-hoc tests indicated acute changes in mean diffusivity (MD) in the bilateral cortex and hippocampus (p<0.0005) and fractional anisotropy (FA) in ipsilateral cortex (p<0.0005), hippocampus (p=0.014), corpus callosum (p=0.031) and contralateral external capsule (p=0.011). These changes returned to baseline by the sub-acute stage. However, mean kurtosis (MK) was significantly elevated at the sub-acute stages in all ipsilateral regions and scaled inversely with the distance from the impacted site (cortex and corpus callosum: p<0.0005; external capsule: p=0.003; hippocampus: p=0.011). Further, at the sub-acute stage increased MK was also observed in the contralateral regions compared to baseline (cortex: p=0.032; hippocampus: p=0.039) while no change was observed with MD and FA. An increase in mean kurtosis was associated with increased reactive astrogliosis from immunohistochemistry analysis. Our results suggest that DKI is sensitive to microstructural changes associated with reactive astrogliosis which may be missed by standard DTI parameters alone. Monitoring changes in MK allows the investigation of molecular and morphological changes in vivo due to reactive astrogliosis and may complement information available from standard DTI parameters. To date the use of diffusion tensor imaging has been limited to study changes in white matter integrity following traumatic insults. Given the sensitivity of DKI to detect microstructural changes even in the gray matter in vivo, allows the extension of the technique to understand patho-morphological changes in the whole brain following a traumatic insult.

Figure 1

The graph illustrates the errors associated with the assumption of Gaussian distribution of water diffusion as in the case of DTI reconstruction versus a non-Gaussian distribution assumption from DKI. Data was obtained from the corpus callosum using various b-values that were fit to both a linear equation as in the case of DTI and also fit to Eq. 1 for DKI. Note that when the b-values exceed 1000 s/mm², the data fits the DKI model significantly better than the DTI model.

Figure 2

Illustration of ROIs on FA maps for a representative injured rat on three consecutive coronal slices. Regions shown are: ipsi- (1) and contra- (2) lateral cortex, ipsi- (3) and contra- (4) lateral hippocampus, corpus callosum (5), ipsi- (6) and contra- (7) lateral external capsule.

Figure 3

FA, MD, and MK maps of a representative rat in the coronal view at baseline (pre-injury), 2 hour and 7 days post injury. Circles indicate the site of injury.

Figure 4

Changes in MD, FA and MK values for ipsilateral and contralateral hippocampus (HC-ips, HC-con), cortex (CTX-ips, CTX-con), external capsule (EC-ips, EC-con), and corpus callosum (CC) from baseline to 7 days post-injury. Statistical significance was based on comparison with baseline values. Error bars indicate standard deviation.

Figure 5

Changes in radial and axial diffusivity (λ_a, λ_r), and kurtosis (K_a, K_r) for white matter regions of corpus callosum (CC) and bi-lateral external capsule (EC_ips, EC_con) from baseline to 7 days post-injury. Statistical significance was based on comparison with baseline values. Error bars indicate standard deviation.

Figure 6

Comparison of immunohistochemical stains using glial fibrillary acidic protein (GFAP) two representative CCI exposed rats (Rat A and B) at 7 day post-injury and a sham rat. Both Rats A & B expressed significantly increased GFAP immunoreactivity at the site of the injury. However, Rat A also expressed significantly elevated GFAP immunoreactivity compared to Rat B in the contralateral cortex. Also shown are the MK vs. MD scattered plots from the contralateral cortex of both rats. The GFAP stains (40× magnification) are shown from the ipsilateral cortex, hippocampus and contralateral hippocampus, cortex of each rat. Increased MK was associated with increased GFAP staining as in the case of Rat A while it remained the same among rats that did not show elevated GFAP staining as in the case of Rat B. It should be noted that no changes are seen in MD for Rat A between the baseline and seven days post-injury despite an increase in MK. .

Figure 7

Pair-wise scattered plots of diffusion-related (MD, FA) and kurtosis-related (MK) parameters for voxels from an ROI on the contralateral cortex (see Fig. 2) from groups of (a) severely and (b) mildly stained rats showing changes in these parameters at 7 days post injury (red dots) in comparison to the baseline (blue dots). The corresponding histograms for each of the parameters with the effect size d_eff are also shown.

Figure 7

Pair-wise scattered plots of diffusion-related (MD, FA) and kurtosis-related (MK) parameters for voxels from an ROI on the contralateral cortex (see Fig. 2) from groups of (a) severely and (b) mildly stained rats showing changes in these parameters at 7 days post injury (red dots) in comparison to the baseline (blue dots). The corresponding histograms for each of the parameters with the effect size d_eff are also shown.