Stratification of heterogeneous diffusion MRI ischemic lesion with kurtosis imaging: evaluation of mean diffusion and kurtosis MRI mismatch in an animal model of transient focal ischemia.
ABSTRACT Ischemic tissue damage is heterogeneous, resulting in complex patterns in the widely used diffusion-weighted MRI. Our study examined the spatiotemporal characteristics of diffusion kurtosis imaging in an animal model of transient middle cerebral artery occlusion.
Adult male Wistar rats (N=18) were subjected to 90 minutes middle cerebral artery occlusion. Multiparametric MR images were obtained during middle cerebral artery occlusion and 20 minutes after reperfusion with diffusion-weighted MRI obtained using 8 b-values from 250 to 3000 s/mm(2) in 6 diffusion gradient directions. Diffusion and kurtosis lesions were outlined in shuffled images by 2 investigators independently. T(2) MRI was obtained 24 hours after middle cerebral artery occlusion to evaluate stroke outcome.
Mean diffusion lesion (23.5%±8.1%, percentage of the brain slice) was significantly larger than mean kurtosis lesion (13.2%±2.0%) during middle cerebral artery occlusion. Mean diffusion lesion decreased significantly after reperfusion (13.8%±4.3%), whereas mean kurtosis lesion showed little change (13.0%±2.5%) with their lesion size difference being insignificant.
We demonstrated that mean diffusion/mean kurtosis mismatch recovered reasonably well on reperfusion, whereas regions with concurrent mean diffusion and mean kurtosis deficits showed poor recovery. Diffusion kurtosis imaging may help stratify heterogeneous diffusion-weighted MRI lesions for enhanced characterization of ischemic tissue injury.
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ABSTRACT: A computational framework is presented for relating the kurtosis tensor for water diffusion in brain to tissue models of brain microstructure. The tissue models are assumed to be comprised of non-exchanging compartments that may be associated with various microstructural spaces separated by cell membranes. Within each compartment the water diffusion is regarded as Gaussian, although the diffusion for the full system would typically be non-Gaussian. The model parameters are determined so as to minimize the Frobenius norm of the difference between the measured kurtosis tensor and the model kurtosis tensor. This framework, referred to as kurtosis analysis of neural diffusion organization (KANDO), may be used to help provide a biophysical interpretation to the information provided by the kurtosis tensor. In addition, KANDO combined with diffusional kurtosis imaging can furnish a practical approach for developing candidate biomarkers for neuropathologies that involve alterations in tissue microstructure. KANDO is illustrated for simple tissue models of white and gray matter using data obtained from healthy human subjects. Copyright © 2014 Elsevier Inc. All rights reserved.NeuroImage 11/2014; 106. DOI:10.1016/j.neuroimage.2014.11.015 · 6.13 Impact Factor
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ABSTRACT: Diffusion MRI is a promising, clinically feasible imaging technique commonly used to describe white matter changes after stroke. We investigated the sensitivity of diffusion MRI to detect microstructural alterations in gray matter after sensorimotor cortex stroke in adult male rats. The mean diffusivity (MD) and mean kurtosis of perilesional motor cortex were compared with measures in the contralesional forelimb area of sensorimotor cortex at 2 hours, 24 hours, 72 hours, or 25 days after surgery. MD and mean kurtosis were correlated to the surface densities of glia, dendrites, and axons. Perilesional mean kurtosis was increased at 72 hours and 25 days after stroke, whereas MD was no longer different from contralesional sensorimotor cortex at 24 hours after stroke. There was a significant increase in the density of glial processes at 72 hours after stroke in perilesional motor cortex, which correlated with perilesional MD. These data support that mean kurtosis and MD provide different but complimentary information on acute and chronic changes in perilesional cortex. Glia infiltration is associated with pseudonormalization of MD in the perilesional motor cortex at 72 hours after lesion; however, this association is absent 25 days after lesion. These data suggest that there are likely several different, time-specific microstructural changes underlying these 2 complimentary diffusion measures. © 2015 American Heart Association, Inc.Stroke 01/2015; 46(2). DOI:10.1161/STROKEAHA.114.006782 · 6.02 Impact Factor
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ABSTRACT: Diffusion kurtosis imaging (DKI) is an extension of diffusion tensor imaging (DTI), exhibiting improved sensitivity and specificity in detecting developmental and pathological changes in neural tissues. However, little attention was paid to the performances of DKI and DTI in detecting white matter abnormality in schizophrenia. In this study, DKI and DTI were performed in 94 schizophrenia patients and 91 sex- and age-matched healthy controls. White matter integrity was assessed by fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean kurtosis (MK), axial kurtosis (AK) and radial kurtosis (RK) of DKI and FA, MD, AD and RD of DTI. Group differences in these parameters were compared using tract-based spatial statistics (TBSS) (P < 0.01, corrected). The sensitivities in detecting white matter abnormality in schizophrenia were MK (34%) > AK (20%) > RK (3%) and RD (37%) > FA (24%) > MD (21%) for DKI, and RD (43%) > FA (30%) > MD (21%) for DTI. DKI-derived diffusion parameters (RD, FA and MD) were sensitive to detect abnormality in white matter regions (the corpus callosum and anterior limb of internal capsule) with coherent fiber arrangement; however, the kurtosis parameters (MK and AK) were sensitive to reveal abnormality in white matter regions (the juxtacortical white matter and corona radiata) with complex fiber arrangement. In schizophrenia, the decreased AK suggests axonal damage; however, the increased RD indicates myelin impairment. These findings suggest that diffusion and kurtosis parameters could provide complementary information and they should be jointly used to reveal pathological changes in schizophrenia.01/2015; 7:170-6. DOI:10.1016/j.nicl.2014.12.008