This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Diffusion-weighted imaging (DWI), in which contrast is based on changes in water apparent diffusion coefficient (ADC), is a powerful imaging modality for early detection of ischemic brain injury. During the acute phase of stroke, the anatomical region defined on the DWI is initially smaller than the area of cerebral-blood-flow (CBF) deficit, but this region expands and eventually coincides with the area defined on perfusion-weighted imaging (PWI). The difference in the anatomic area defined by the PWI and DWI, often referred to as the ?perfusion-diffusion? mismatch, may represent salvageable tissues. ?Perfusion-diffusion mismatch? has been widely observed in humans and is presumed to approximate the ischemic penumbra. However, similar observations in animal models are limited and the spatiotemporal dynamics of the perfusion-diffusion mismatch has yet to be systematically investigated. The general aims of this proposal are to characterize tissue fate in focal ischemic brain injury using quantitative perfusion and diffusion imaging, and to relate tissue functional status and histology. These studies will focus on the acute phase (every 30 mins up to 4 hrs) of ischemic brain injury in rats subjected to permanent and temporary (30, 60 and 90 mins) occlusion. Different occlusion times will test the predictability of tissue fate across time. Quantitative perfusion and diffusion imaging at high spatial (180x180x1500 ?m3) and temporal (every 30 mins) resolution will be performed on a 4.7 Tesla scanner. The overall hypothesis is that the spatiotemporal dynamics of quantitative perfusion, diffusion and functional changes during the critical acute phase of the ischemic brain injury could be used to characterize and potentially predict ischemic tissue fate.
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