Research ReportSpatiotemporal dynamics of diffusional kurtosis, mean diffusivity and perfusion changes in experimental stroke
Highlights
► Mean kurtosis offers unique contrasts to probe biophysical changes associated with stroke. ► Mean kurtosis was sensitive to hyperacute and acute stroke changes. ► Mean kurtosis contrast had different temporal dynamics than mean diffusivity. ► Mean kurtosis MRI can potentially complement existing stroke imaging techniques.
Introduction
The anatomical mismatch between diffusion-weighted (DWI) and perfusion-weighted imaging (PWI) abnormality offers remarkable sensitivity to ischemic brain injury (Schlaug et al., 1999). However, some mismatch tissue are oligemic, some are salvageable and some are not, depending on the duration and nature of ischemic injury, and proximity of patent vessels, among other factors. Thus, the perfusion–diffusion mismatch only approximates the ischemic penumbra. Despite its shortcomings (Kidwell et al., 2003), the mismatch is commonly used to guide clinical decision making in acute stroke management. By contrast, conventional T2-weighted (T2W) images and computed tomography could not detect ischemic injury until at least 6 hours after stroke onset, coinciding with vasogenic edema at which point the tissue has already become infarct (Baird and Warach, 1998). Other methods are being explored to improve characterization of ischemic brain injury.
Diffusional kurtosis is a measure of the non-Gaussianity of water diffusion (Jensen et al., 2005). Free, unrestricted water diffusion has a Gaussian distribution, and thus a zero diffusional kurtosis. Restricted water diffusion has a distribution that is sharper than Gaussian, hence positive diffusional kurtosis. Tissue microstructures that restrict water diffusion include cell membranes, organelles and tissue compartments, among other factors. In other words, diffusional kurtosis characterizes the complexity or heterogeneity of the tissue microenvironment (Jensen et al., 2005). In diseases, such as ischemic brain injury, diffusional kurtosis could change due to: i) cytotoxic edema, ii) progressive alteration in cell packing geometry, iii) cell membrane permeability changes, and/or iv) change in cell size distribution as a result of cell necrosis (Baird and Warach, 1998, Fung et al., 2011). Diffusional kurtosis imaging (DKI) has some advantages over conventional DTI because of its sensitivity to tissue heterogeneity, especially isotropic grey matter (GM) (Jensen and Helpern, 2010, Jensen et al., 2005). DKI thus has the potential to provide additional insights of tissue microstructure (Jensen and Helpern, 2010).
DKI has recently been used to study human ischemic stroke. Diffusional kurtosis increased at 1 to 5 days after stroke onset (Helpern et al., 2009, Jensen et al., 2010, Latt et al., 2009b, Peeters et al., 2010, van Westen et al., 2010) and exhibited distinct abnormalities that were not apparent on conventional DWI/DTI or apparent diffusion coefficient (ADC) map (Helpern et al., 2009). Latt et al. investigated the presence of water exchange in ischemic lesion by varying the diffusion time in DKI acquisition in humans (Latt et al., 2009b). Diffusional kurtosis of both white matter (WM) and, to a lesser extent, GM lesions varied with diffusion time at 1 to 5 days after stroke onset, while mean diffusivity (MD) and normal tissue did not. DKI has also been used to study normal WM and GM microstructures (Cheung et al., 2009, Falangola et al., 2008, Fieremans et al., 2010, Hui et al., 2008), brain glioma (Raab et al., 2010), attention-deficit hyperactivity disorder (Helpern et al., 2011), and traumatic brain injury (Grossman et al., in press). DKI studies in animal stroke models, however, have not been reported, and the temporal evolution of DKI-derived metrics with respect to DWI and PWI changes in animal models has yet to be systematically investigated. Animal models where focal ischemia can be reproducibly studied under controlled conditions would be important for characterizing DKI contrast, which could ultimately lead to better characterization and staging of human stroke.
The goal of this study was to longitudinally examine the spatiotemporal dynamics of diffusional kurtosis in cerebral ischemia in an animal model of permanent and transient (45 min) middle cerebral artery occlusion (MCAO) during the hyperacute, acute and chronic phases (up to 7 days post-occlusion). Comparisons were longitudinally made with MD, fractional anisotropy (FA), T2W MRI, and perfusion changes in the same animals.
Section snippets
Permanent MCAO
Fig. 1 shows the spatiotemporal dynamics of the absolute CBF, MD, MK, FA maps and T2W images of an animal subjected to permanent MCAO. CBF of the ischemic lesion was markedly reduced and did not change over time. MD reduction and MK increase were apparent in hyperacute (0–2 hrs) and acute (24 hrs post-occlusion) phases. FA and T2W images did not change until 24 hrs post-occlusion.
The group-averaged temporal evolution of CBF, MD, MK and FA were analyzed for the cortex and striatum ROIs (Fig. 2).
Discussions
This study documented the spatiotemporal dynamics of diffusional kurtosis in a rat stroke model of permanent and transient MCAO. MK offers unique contrasts to probe biophysical changes associated with stroke. MK shows different spatiotemporal dynamics than MD and FA. MK is sensitive to hyperacute and acute stroke changes albeit difference in relative changes and CNR than MD, but higher contrast than FA and T2. MK contrast persists 1 to 7 days post-occlusion, whereas MD shows renormalization at
Animal preparations
Male Sprague–Dawley rats (250 to 300 g; Charles River Laboratories, Wilmington, MA, USA) were used. All experimental procedures were approved by the Institutional Animal Care and Use Committee, UT Health Science Centre at San Antonio. Animals were initially anesthetized with 5% isoflurane, and mechanically ventilated (Harvard Model 683 Small Animal Ventilator, Holliston, MA, USA). Stroke surgery was performed using the intraluminal MCAO method under 2% isoflurane as described previously (Shen et
Acknowledgments
This work was supported in part by the NIH (R01-NS45879) and the American Heart Association (EIA 0940104N and SDG-0830293N) to TQD.
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