Cerebral Oxygen Extraction Fraction (OEF) has been shown to be an independent predictor of stroke risk [1]. Furthermore, the NIH/NINDS Progress Review Group has recently named tissue oxygenation imaging as a primary research goal in its August 2013 review. We have developed a means of quantifying OEF in under 65 ms using a “snapshot” PARSE [2,3] pulse sequence. In this ongoing work we develop a method by which transit changes in tissue oxygenation measured throughout the cardiac cycle is quantified for the first time. We develop a physiologic model which calculates cerebrovascular reserve (CVR) from these transient fluctuations using a Windkessel model. Since CVR provides complimentary information on arterial collateralization, our model has the potential to distinguish between small vessel and large vessel cerebrovascular disease—providing additional much needed information to clinicians. Snapshot PARSE encodes the free induction decay in a 2D slice using a rosette trajectory over 65 ms [2]. This yields 2D images of δω, R₂* and M₀ which are used to calculated OEF in the static dephasing regime [4]. In this work, we use widely available independent component analysis (ICA) of the raw frequency signal to extract the physiologic transient effects associated with the cardiac cycle and parameterize these effects in humans with angiographically confirmed neurovascular disease. Cardiac-gated: Because of the speed of PARSE (65 ms) we are able to see the transient fluctuations in tissue oxygenation induced by the inflow and extraction of oxygenated blood throughout the cardiac cycle. Images were acquired in 25 ms intervals from the R-wave trigger. By acquiring 20 PARSE datasets we are able to observe frequency shifts (δω) resulting from increased de-oxyhemoglobin in the draining veins of the head, similar to BOLD contrast. These 4-10 Hz shifts are de-noised using ICA with spatial coordinates defined as the length along the PARSE readout and temporal domain being the 20 time points separated by Δt = 25 ms. Images were reconstructed using a novel iterative Progressive Length Conjugate Gradient (PLCG) method to prevent local minima solutions. ICA uses blind-source separation to extract time-courses, which correspond to bulk signal enhancement associated with the cardiac cycle. Time courses that showed an enhancement of greater than 20% during the physiologic stress state were used to reconstruct the de-noised free-induction decay signal; allowing us to create a signal containing only the dynamic components. Hemispheric differences were calculated in images containing only dynamic components. Mean regional values were calculated using a “battleship” approach. Ten symptomatic patients with angiographically confirmed high grade (> 70%) stenosis of the MCA, ACA or PCA arteries were tested (M/F 5/5, <age> = 58.2 ± 9.9 years). A single 2D slice (5.0 mm thick, 220 mm x 220 mm FOV, 96x96 matrix, resolution = 2.3 x 2.3 x 5.0 mm³) was acquired in the superior division of the brain to cover the MCA, PCA and/or ACA vascular territories. Measured mean OEF in non-affected normal brain parenchyma of 36.87 ± 6.6% with symptomatically affected regions reaching 84.05 ± 4.54% correlates well with literature. Though little can be deduced from the time-course created before de-noising, ICA’d images taken during the first 125 ms of the cardiac cycle in a symptomatic patient with a right ICA stenosis show clear asymmetric hemispheric OEF (right hemispheric 13.06% elevation, Figure 1a). We also see a non-uniform flush in of de-oxygenated hemoglobin with a subsequent uneven outflow, unseen in healthy volunteers, suggesting regions of compromised cerebral vascular reserve. This non-uniform draining of de-oxygenated blood is fit with a Windkessel model (Figure 1bc) to quantitate hemodynamic compromise. We see in the ten symptomatic patients statistically significant asymmetric hemispheric reactivity (p<.0179, Figure 2ab). We have found that MR-PARSE has detectable sensitivity to frequency shifts induced by transient alterations in de-oxyhemoglobin through the cardiac cycle. In our initial studies, we have shown, through the use of ICA, a statistically significant hemispheric effect. Our approach to quantify cerebrovascular reactivity represents a new and simple, non contrast approach to stratifying patients toward therapies to prevent stroke.