title: Can diffusion kurtosis imaging improve the sensitivity and specificity of detecting microstructural alterations in brain tissue chronically after experimental stroke? Comparisons with diffusion tensor imaging and histology.
abstract: Imaging techniques that provide detailed insights into structural tissue changes after stroke can vitalize development of treatment strategies and diagnosis of disease. Diffusion-weighted MRI has been playing an important role in this regard. Diffusion kurtosis imaging (DKI), a recent addition to this repertoire, has opened up further possibilities in extending our knowledge about structural tissue changes related to injury as well as plasticity. In this study we sought to discern the microstructural alterations characterized by changes in diffusion tensor imaging (DTI) and DKI parameters at a chronic time point after experimental stroke. Of particular interest was the question of whether DKI parameters provide additional information in comparison to DTI parameters in understanding structural tissue changes, and if so, what their histological origins could be. Region-of-interest analysis and a data-driven approach to identify tissue abnormality were adopted to compare DTI- and DKI-based parameters in post mortem rat brain tissue, which were compared against immunohistochemistry of various cellular characteristics. The unilateral infarcted area encompassed the ventrolateral cortex and the lateral striatum. Results from region-of-interest analysis in the lesion borderzone and contralateral tissue revealed significant differences in DTI and DKI parameters between ipsi- and contralateral sensorimotor cortex, corpus callosum, internal capsule and striatum. This was reflected by a significant reduction in ipsilateral mean diffusivity (MD) and fractional anisotropy (FA) values, accompanied by significant increases in kurtosis parameters in these regions. Data-driven analysis to identify tissue abnormality revealed that the use of kurtosis-based parameters improved the detection of tissue changes in comparison with FA and MD, both in terms of dynamic range and in being able to detect changes to which DTI parameters were insensitive. This was observed in gray as well as white matter. Comparison against immunohistochemical stainings divulged no straightforward correlation between diffusion-based parameters and individual neuronal, glial or inflammatory tissue features. Our study demonstrates that DKI allows sensitive detection of structural tissue changes that reflect post-stroke tissue remodeling. However, our data also highlights the generic difficulty in unambiguously asserting specific causal relationships between tissue status and MR diffusion parameters.
authors.affiliation: Biomedical MR Imaging and Spectroscopy Group, Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands. Electronic address: umesh@invivonmr.uu.nl.
authors.forename: S
authors.initials: S
authors.lastname: Umesh Rudrapatna
authors.affiliation: Laboratory for Experimental Brain Research, Department of Clinical Sciences, Division of Neurosurgery, Lund University, BMC A13, S-22184 Lund, Sweden.
authors.forename: Tadeusz
authors.initials: T
authors.lastname: Wieloch
authors.affiliation: Laboratory for Experimental Brain Research, Department of Clinical Sciences, Division of Neurosurgery, Lund University, BMC A13, S-22184 Lund, Sweden.
authors.forename: Kerstin
authors.initials: K
authors.lastname: Beirup
authors.affiliation: Laboratory for Experimental Brain Research, Department of Clinical Sciences, Division of Neurosurgery, Lund University, BMC A13, S-22184 Lund, Sweden.
authors.forename: Karsten
authors.initials: K
authors.lastname: Ruscher
authors.affiliation: Biomedical MR Imaging and Spectroscopy Group, Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.
authors.forename: Wouter
authors.initials: W
authors.lastname: Mol
authors.affiliation: Biomedical MR Imaging and Spectroscopy Group, Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.
authors.forename: Pavel
authors.initials: P
authors.lastname: Yanev
authors.affiliation: PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.
authors.forename: Alexander
authors.initials: A
authors.lastname: Leemans
authors.affiliation: Biomedical MR Imaging and Spectroscopy Group, Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.
authors.forename: Annette
authors.initials: A
authors.lastname: van der Toorn
authors.affiliation: Biomedical MR Imaging and Spectroscopy Group, Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands. Electronic address: r.m.dijkhuizen@umcutrecht.nl.
authors.forename: Rick M
authors.initials: RM
authors.lastname: Dijkhuizen
mesh_terms: D000818:Animals; D001921:Brain / Q000473:pathology* / Q000648:ultrastructure*; D001931:Brain Mapping; D003627:Data Interpretation, Statistical; D056324:Diffusion Tensor Imaging / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry; D020244:Infarction, Middle Cerebral Artery / Q000473:pathology; D008297:Male; D051381:Rats; D020521:Stroke / Q000473:pathology*
keywords: Chronic stroke; DKI; DTI; Diffusion; Diffusion kurtosis imaging; Microstructure