Lorenzano S, Rost NS, Khan M, Li H, Lima FO, Maas MB, Green RE, Thankachan TK, Dipietro AJ, Arai K, Som AT, Pham L-DD, Wu O, Harris GJ, Lo EH, Blumberg JB, Milbury PE, Feske SK, Furie KL. Oxidative Stress Biomarkers of Brain Damage: Hyperacute Plasma F2-Isoprostane Predicts Infarct Growth in Stroke. Stroke 2018;Abstract
    BACKGROUND AND PURPOSE: Oxidative stress is an early response to cerebral ischemia and is likely to play an important role in the pathogenesis of cerebral ischemic injury. We sought to evaluate whether hyperacute plasma concentrations of biomarkers of oxidative stress, inflammation, and tissue damage predict infarct growth (IG). METHODS: We prospectively measured plasma F2-isoprostane (F2-isoP), urinary 8-oxo-7,8-dihydro-2'-deoxyguoanosine, plasma oxygen radical absorbance capacity assay, high sensitivity C reactive protein, and matrix metalloproteinase 2 and 9 in consecutive patients with acute ischemic stroke presenting within 9 hours of symptom onset. Patients with baseline diffusion-weighted magnetic resonance imaging and follow-up diffusion-weighted imaging or computed tomographic scan were included to evaluate the final infarct volume. Baseline diffusion-weighted imaging volume and final infarct volume were analyzed using semiautomated volumetric method. IG volume was defined as the difference between final infarct volume and baseline diffusion-weighted imaging volume. RESULTS: A total of 220 acute ischemic stroke subjects were included in the final analysis. One hundred seventy of these had IG. Baseline F2-isoP significantly correlated with IG volume (Spearman ρ=0.20; P=0.005) and final infarct volume (Spearman ρ=0.19; P=0.009). In a multivariate binary logistic regression model, baseline F2-isoP emerged as an independent predictor of the occurrence of IG (odds ratio, 2.57; 95% confidence interval, 1.37-4.83; P=0.007). In a multivariate linear regression model, baseline F2-isoP was independently associated with IG volume (B, 0.38; 95% confidence interval, 0.04-0.72; P=0.03). CONCLUSIONS: Elevated hyperacute plasma F2-isoP concentrations independently predict the occurrence of IG and IG volume in patients with acute ischemic stroke. If validated in future studies, measuring plasma F2-isoP might be helpful in the acute setting to stratify patients with acute ischemic stroke for relative severity of ischemic injury and expected progression.
    Rost NS, Cougo P, Lorenzano S, Li H, Cloonan L, Bouts MJRJ, Lauer A, Etherton MR, Karadeli HH, Musolino PL, Copen WA, Arai K, Lo EH, Feske SK, Furie KL, Wu O. Diffuse microvascular dysfunction and loss of white matter integrity predict poor outcomes in patients with acute ischemic stroke. J Cereb Blood Flow Metab 2018;38(1):75-86.Abstract
    We sought to investigate the relationship between blood-brain barrier (BBB) permeability and microstructural white matter integrity, and their potential impact on long-term functional outcomes in patients with acute ischemic stroke (AIS). We studied 184 AIS subjects with perfusion-weighted MRI (PWI) performed <9 h from last known well time. White matter hyperintensity (WMH), acute infarct, and PWI-derived mean transit time lesion volumes were calculated. Mean BBB leakage rates (K2 coefficient) and mean diffusivity values were measured in contralesional normal-appearing white matter (NAWM). Plasma matrix metalloproteinase-2 (MMP-2) levels were studied at baseline and 48 h. Admission stroke severity was evaluated using the NIH Stroke Scale (NIHSS). Modified Rankin Scale (mRS) was obtained at 90-days post-stroke. We found that higher mean K2 and diffusivity values correlated with age, elevated baseline MMP-2 levels, greater NIHSS and worse 90-day mRS (all p < 0.05). In multivariable analysis, WMH volume was associated with mean K2 ( p = 0.0007) and diffusivity ( p = 0.006) values in contralesional NAWM. In summary, WMH severity measured on brain MRI of AIS patients is associated with metrics of increased BBB permeability and abnormal white matter microstructural integrity. In future studies, these MRI markers of diffuse cerebral microvascular dysfunction may improve prediction of cerebral tissue infarction and functional post-stroke outcomes.
    Wu O, Sumii T, Asahi M, Sasamata M, Ostergaard L, Rosen BR, Lo EH, Dijkhuizen RM. Infarct prediction and treatment assessment with MRI-based algorithms in experimental stroke models. J Cereb Blood Flow Metab 2007;27(1):196-204.Abstract
    There is increasing interest in using algorithms combining multiple magnetic resonance imaging (MRI) modalities to predict tissue infarction in acute human stroke. We developed and tested a voxel-based generalized linear model (GLM) algorithm to predict tissue infarction in an animal stroke model in order to directly compare predicted outcome with the tissue's histologic outcome, and to evaluate the potential for assessing therapeutic efficacy using these multiparametric algorithms. With acute MRI acquired after unilateral embolic stroke in rats (n=8), a GLM was developed and used to predict infarction on a voxel-wise basis for saline (n=6) and recombinant tissue plasminogen activator (rt-PA) treatment (n=7) arms of a trial of delayed thrombolytic therapy in rats. Pretreatment predicted outcome compared with post-treatment histology was highly accurate in saline-treated rats (0.92+/-0.05). Accuracy was significantly reduced (P=0.04) in rt-PA-treated animals (0.86+/-0.08), although no significant difference was detected when comparing histologic lesion volumes. Animals that reperfused had significantly lower (P<0.01) GLM-predicted infarction risk (0.73+/-0.03) than nonreperfused animals (0.81+/-0.05), possibly reflecting less severe initial ischemic injury and therefore tissue likely more amenable to therapy. Our results show that acute MRI-based algorithms can predict tissue infarction with high accuracy in animals not receiving thrombolytic therapy. Furthermore, alterations in disease progression due to treatment were more sensitively monitored with our voxel-based analysis techniques than with volumetric approaches. Our study shows that predictive algorithms are promising metrics for diagnosis, prognosis and therapeutic evaluation after acute stroke that can translate readily from preclinical to clinical settings.
    Wu O, Koroshetz WJ, Ostergaard L, Buonanno FS, Copen WA, Gonzalez RG, Rordorf G, Rosen BR, Schwamm LH, Weisskoff RM, Sorensen AG. Predicting tissue outcome in acute human cerebral ischemia using combined diffusion- and perfusion-weighted MR imaging. Stroke 2001;32(4):933-42.Abstract
    BACKGROUND AND PURPOSE: Tissue signatures from acute MR imaging of the brain may be able to categorize physiological status and thereby assist clinical decision making. We designed and analyzed statistical algorithms to evaluate the risk of infarction for each voxel of tissue using acute human functional MRI. METHODS: Diffusion-weighted MR images (DWI) and perfusion-weighted MR images (PWI) from acute stroke patients scanned within 12 hours of symptom onset were retrospectively studied and used to develop thresholding and generalized linear model (GLM) algorithms predicting tissue outcome as determined by follow-up MRI. The performances of the algorithms were evaluated for each patient by using receiver operating characteristic curves. RESULTS: At their optimal operating points, thresholding algorithms combining DWI and PWI provided 66% sensitivity and 83% specificity, and GLM algorithms combining DWI and PWI predicted with 66% sensitivity and 84% specificity voxels that proceeded to infarct. Thresholding algorithms that combined DWI and PWI provided significant improvement to algorithms that utilized DWI alone (P=0.02) but no significant improvement over algorithms utilizing PWI alone (P=0.21). GLM algorithms that combined DWI and PWI showed significant improvement over algorithms that used only DWI (P=0.02) or PWI (P=0.04). The performances of thresholding and GLM algorithms were comparable (P>0.2). CONCLUSIONS: Algorithms that combine acute DWI and PWI can assess the risk of infarction with higher specificity and sensitivity than algorithms that use DWI or PWI individually. Methods for quantitatively assessing the risk of infarction on a voxel-by-voxel basis show promise as techniques for investigating the natural spatial evolution of ischemic damage in humans.
    Yoshiura T, Wu O, Sorensen AG. Advanced MR techniques: diffusion MR imaging, perfusion MR imaging, and spectroscopy. Neuroimaging Clin N Am 1999;9(3):439-53.Abstract
    Recent technical advances in MR imaging have enabled the authors to investigate early physiological changes in acute ischemic stroke lesion. Diffusion and perfusion MR imaging can provide clinically useful information not only for early detection of ischemia, but also for prediction of tissue outcome. MR spectroscopy is a potentially powerful tool to study acute stroke, but its clinical value has been limited due to long examination time and low spatial resolution.