The long-range goal of this work is to develop and validate a novel, clinically useful, location-weighted CT perfusion (CTP) based tool to predict the maximal clinical recovery attributable to salvage of ischemic tissue with reperfusion. The first step is to ascertain how best to predict tissue fate depending on whether or not there is early reperfusion. Although this in itself would be a major advance, the goal of acute stroke treatment is to minimize neurological deficit and maximize functional outcome. Predicting only potential tissue salvage is inadequate to assess the risk versus benefit of intervention, except for extreme cases, i.e., large volume of tissue at risk, or no salvageable tissue. A method that predicts expected clinical improvement based on extent and location of tissue salvage is the ultimate goal of acute stroke imaging. Owing to the superior quantitative capability of CT, as opposed to MR, perfusion imaging, the application of specific CT cerebral blood flow (CT-CBF) and blood volume (CT-CBV) thresholds to predict tissue survival or infarction appears promising. Because smaller studies have suggested that the calculated volume salvaged by reperfusion is correlated with improvement in NIHSS, it is essential that these thresholds be validated in larger patient cohorts for which reperfusion status is known.
In Aims 1 and 2, we will therefore establish CTP thresholds for """"""""core"""""""" (tissue likely to die despite reperfusion) and """"""""benign oligemia"""""""" (tissue likely to survive despite persistent hypoperfusion). Ischemic tissue with CTP values between these extremes reflects """"""""unstable penumbra"""""""" (tissue with variable outcome, depending on the degree, extent, and timing of reperfusion).
In Aim 2. iii, we will confirm that CT angiographic source images (CTA-SI), which cover the entire brain, require no post processing, and are available immediately at scan completion, can also be used to sensitively determine infarct """"""""core"""""""".
In Aim 3, we will begin to develop a clinical prediction model to estimate """"""""maximal expected clinical improvement in NIHSS scoring associated with reperfusion"""""""".
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