Abstract
Background and Purpose: Changes in vascular indices such as blood-to-brain forward volume transfer constant (Ktrans) and plasma distribution volume (vp) are considered as potential predictors of impending hemorrhage in acute stroke. However, few studies have reported their spatial distributions and variability within a given stroke lesion. This study examined the voxel-by-voxel distributions of vp and Ktrans within a region of interest (ROI) and the overall mean for the entire ROI to investigate their possible inherent variability. Methods: Male Wistar rats (~300 g; N=6) were subjected to embolic occlusion of the middle cerebral artery for 2 h followed by treatment with recombinant tissue plasminogen activator (rTPA) treatment for thrombolysis. Measurements of vp and Ktrans were made in the ischemic lesion after rTPA infusion using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Data were generated using two approaches. In the first, voxel-by-voxel values of moments about the mean viz., median and skewness. In the second, values were summed across the ROI producing a mean and standard deviation. Differences between the two means were assessed by t-tests and significance inferred at p≤0.05. Results: The voxel-by-voxel estimates of vp were larger (0.025+0.008) than the summed mean (0.016+0.005), the difference being marginally significant (p=0.05). A positive skew value of 1.88 was obtained for the data and accordingly the median value (0.019) was lower than the mean. In contrast, voxel -based estimate of Ktrans (0.002+0.001) was not different from the summed mean (0.002+0.001; p>0.05). The median value for Ktrans (0.002) was not significantly different from the mean (p>0.05) suggesting a more uniform distribution of the data across the voxels with a very low skewness (0.05). Conclusions: These observations suggest that the voxel-by-voxel distributions can be dissimilar for the different indices of vascular injury within a given ischemic lesion. Such variations may be representative of varying degrees of damage and, consequently, may also represent the effects of a putative treatment. Understanding the tissue pathology determining these variations can assist in employing them as biomarkers of injury and response to treatment.
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