Winzeck S, Mocking SJT, Bezerra R, Bouts MJRJ, McIntosh EC, Diwan I, Garg P, Chutinet A, Kimberly WT, Copen WA, Schaefer PW, Ay H, Singhal AB, Kamnitsas K, Glocker B, Sorensen AG, Wu O. Ensemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRI. AJNR Am J Neuroradiol 2019;40(6):938-945.Abstract
BACKGROUND AND PURPOSE: Accurate automated infarct segmentation is needed for acute ischemic stroke studies relying on infarct volumes as an imaging phenotype or biomarker that require large numbers of subjects. This study investigated whether an ensemble of convolutional neural networks trained on multiparametric DWI maps outperforms single networks trained on solo DWI parametric maps. MATERIALS AND METHODS: Convolutional neural networks were trained on combinations of DWI, ADC, and low b-value-weighted images from 116 subjects. The performances of the networks (measured by the Dice score, sensitivity, and precision) were compared with one another and with ensembles of 5 networks. To assess the generalizability of the approach, we applied the best-performing model to an independent Evaluation Cohort of 151 subjects. Agreement between manual and automated segmentations for identifying patients with large lesion volumes was calculated across multiple thresholds (21, 31, 51, and 70 cm). RESULTS: An ensemble of convolutional neural networks trained on DWI, ADC, and low b-value-weighted images produced the most accurate acute infarct segmentation over individual networks ( < .001). Automated volumes correlated with manually measured volumes (Spearman ρ = 0.91, < .001) for the independent cohort. For the task of identifying patients with large lesion volumes, agreement between manual outlines and automated outlines was high (Cohen κ, 0.86-0.90; < .001). CONCLUSIONS: Acute infarcts are more accurately segmented using ensembles of convolutional neural networks trained with multiparametric maps than by using a single model trained with a solo map. Automated lesion segmentation has high agreement with manual techniques for identifying patients with large lesion volumes.
Schirmer MD, Ktena SI, Nardin MJ, Donahue KL, Giese A-K, Etherton MR, Wu O, Rost NS. Rich-Club Organization: An Important Determinant of Functional Outcome After Acute Ischemic Stroke. Front Neurol 2019;10:956.Abstract
To determine whether the rich-club organization, essential for information transport in the human connectome, is an important biomarker of functional outcome after acute ischemic stroke (AIS). Consecutive AIS patients ( = 344) with acute brain magnetic resonance imaging (MRI) (<48 h) were eligible for this study. Each patient underwent a clinical MRI protocol, which included diffusion weighted imaging (DWI). All DWIs were registered to a template on which rich-club regions have been defined. Using manual outlines of stroke lesions, we automatically counted the number of affected rich-club regions and assessed its effect on the National Institute of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS; obtained at 90 days post-stroke) scores through ordinal regression. Of 344 patients (median age 65, inter-quartile range 54-76 years) with a median DWI lesion volume (DWIv) of 3cc, 64% were male. We established that an increase in number of rich-club regions affected by a stroke increases the odds of poor stroke outcome, measured by NIHSS (OR: 1.77, 95%CI 1.41-2.21) and mRS (OR: 1.38, 95%CI 1.11-1.73). Additionally, we demonstrated that the OR exceeds traditional markers, such as DWIv (OR 1.08, 95%CI 1.06-1.11; OR 1.05, 95%CI 1.03-1.07) and age (OR 1.03, 95%CI 1.01-1.05; OR 1.05, 95%CI 1.03-1.07). In this proof-of-concept study, the number of rich-club nodes affected by a stroke lesion presents a translational biomarker of stroke outcome, which can be readily assessed using standard clinical AIS imaging protocols and considered in functional outcome prediction models beyond traditional factors.
Schirmer MD, Etherton Md PhD MR, Dalca PhD AV, Giese Md A-K, Cloonan MSc L, Wu PhD O, Golland PhD P, Rost Md Mph Faan NS. Effective Reserve: A Latent Variable to Improve Outcome Prediction in Stroke. J Stroke Cerebrovasc Dis 2019;28(1):63-69.Abstract
Prediction of functional outcome after stroke based on initial presentation remains an open challenge, suggesting that an important aspect is missing from these prediction models. There exists the notion of a protective mechanism called brain reserve, which may be utilized to understand variations in disease outcome. In this work, we expand the concept of brain reserve (effective reserve) to improve prediction models of functional outcome after acute ischemic stroke (AIS). Consecutive AIS patients with acute brain magnetic resonance imaging (<48 hours) were eligible for this study. White matter hyperintensity and acute infarct volume were determined on T2 fluid attenuated inversion recovery and diffusion weighted images, respectively. Modified Rankin Scale scores were obtained at 90days poststroke. Effective reserve was defined as a latent variable using structural equation modeling by including age, systolic blood pressure, and intracranial volume measurements. Of 453 AIS patients (mean age 66.6 ± 14.7 years), 36% were male and 311 hypertensive. There was inverse association between effective reserve and 90-day modified Rankin Scale scores (path coefficient -0.18 ± 0.01, P < .01). Compared to a model without effective reserve, correlation between predicted and observed modified Rankin Scale scores improved in the effective-reserve-based model (Spearman's ρ 0.29 ± 0.18 versus 0.15 ± 0.17, P < .001). Furthermore, hypertensive patients exhibited lower effective reserve (P < 10). Using effective reserve in prediction models of stroke outcome is feasible and leads to better model performance. Furthermore, higher effective reserve is associated with more favorable functional poststoke outcome and might correspond to an overall better vascular health.
Ktena SI, Schirmer MD, Etherton MR, Giese A-K, Tuozzo C, Mills BB, Rueckert D, Wu O, Rost NS. Brain Connectivity Measures Improve Modeling of Functional Outcome After Acute Ischemic Stroke. Stroke 2019;50(10):2761-2767.Abstract
Background and Purpose- The ability to model long-term functional outcomes after acute ischemic stroke represents a major clinical challenge. One approach to potentially improve prediction modeling involves the analysis of connectomics. The field of connectomics represents the brain's connectivity as a graph, whose topological properties have helped uncover underlying mechanisms of brain function in health and disease. Specifically, we assessed the impact of stroke lesions on rich club organization, a high capacity backbone system of brain function. Methods- In a hospital-based cohort of 41 acute ischemic stroke patients, we investigated the effect of acute infarcts on the brain's prestroke rich club backbone and poststroke functional connectomes with respect to poststroke outcome. Functional connectomes were created using 3 anatomic atlases, and characteristic path-length () was calculated for each connectome. The number of rich club regions affected were manually determined using each patient's diffusion weighted image. We investigated differences in with respect to outcome (modified Rankin Scale score; 90 days) and the National Institutes of Health Stroke Scale (NIHSS; early: 2-5 days; late: 90-day follow-up). Furthermore, we assessed the effect of including number of rich club regions and in outcome models, using linear regression and assessing the explained variance (R). Results- Of 41 patients (mean age [range]: 70 [45-89] years), 61% were male. Lower was generally associated with better outcome. Including number of rich club regions in the backward selection models of outcome, R increased between 1.3- and 2.6-fold beyond that of traditional markers (age and acute lesion volume) for NIHSS and modified Rankin Scale score. Conclusions- In this proof-of-concept study, we showed that information on network topology can be leveraged to improve modeling of poststroke functional outcome. Future studies are warranted to validate this approach in larger prospective studies of outcome prediction in stroke.
Schirmer MD, Giese A-K, Fotiadis P, Etherton MR, Cloonan L, Viswanathan A, Greenberg SM, Wu O, Rost NS. Spatial Signature of White Matter Hyperintensities in Stroke Patients. Front Neurol 2019;10:208.Abstract
White matter hyperintensity (WMH) is a common phenotype across a variety of neurological diseases, particularly prevalent in stroke patients; however, vascular territory dependent variation in WMH burden has not yet been identified. Here, we sought to investigate the spatial specificity of WMH burden in patients with acute ischemic stroke (AIS). We created a novel age-appropriate high-resolution brain template and anatomically delineated the cerebral vascular territories. We used WMH masks derived from the clinical T2 Fluid Attenuated Inverse Recovery (FLAIR) MRI scans and spatial normalization of the template to discriminate between WMH volume within each subject's anterior cerebral artery (ACA), middle cerebral artery (MCA), and posterior cerebral artery (PCA) territories. Linear regression modeling including age, sex, common vascular risk factors, and TOAST stroke subtypes was used to assess for spatial specificity of WMH volume (WMHv) in a cohort of 882 AIS patients. Mean age of this cohort was 65.23 ± 14.79 years, 61.7% were male, 63.6% were hypertensive, 35.8% never smoked. Mean WMHv was 11.58c ± 13.49 cc. There were significant differences in territory-specific, relative to global, WMH burden. In contrast to PCA territory, age (0.018 ± 0.002, < 0.001) and small-vessel stroke subtype (0.212 ± 0.098, < 0.001) were associated with relative increase of WMH burden within the anterior (ACA and MCA) territories, whereas male sex (-0.275 ± 0.067, < 0.001) was associated with a relative decrease in WMHv. Our data establish the spatial specificity of WMH distribution in relation to vascular territory and risk factor exposure in AIS patients and offer new insights into the underlying pathology.
Gökçay F, Arsava EM, Baykaner T, Vangel M, Garg P, Wu O, Singhal AB, Furie KL, Sorensen AG, Ay H. Age-dependent susceptibility to infarct growth in women. Stroke 2011;42(4):947-51.Abstract

It is not known if there is a relationship between gender and tissue outcome in human ischemic stroke. We sought to identify whether the proportion of initially ischemic to eventually infarcted tissue was different between men and women with ischemic stroke.


We studied 141 consecutive patients with acute ischemic stroke who had a baseline MRI obtained within 12 hours of symptom onset, a follow-up imaging on Day 4 or later, and diffusion-weighted imaging/mean transmit time mismatch on initial MRI. Lesion growth was calculated as percentage of mismatch tissue that underwent infarction on follow-up (percentage mismatch lost). Multivariable analyses explored the effect of gender and other predictors of tissue outcome on percentage mismatch lost.


There was no difference in median percentage mismatch lost between men (19%) and women (11%; P=0.720). There was, however, an interaction between gender and age; median percentage mismatch lost was 7% (0% to 12%) in women and 18% (1% to 35%) in men younger than the population median (71 years, P=0.061). The percentage mismatch lost was not different between men and women ≥71 years old (25% in both groups). The linear regression model revealed gender (P=0.027) and the interaction between age and gender (P=0.023) as independent predictors of percentage mismatch lost.


There is an age-by-gender interaction in tissue outcome after ischemic stroke; brain infarcts in women <70 years grow approximately 50% less than infarcts in their male counterparts. These findings extend the well-known concept that there is a differential age-by-gender effect on stroke incidence, mortality, and functional outcome to the tissue level.

Schwamm LH, Wu O, Song SS, Latour LL, Ford AL, Hsia AW, Muzikansky A, Betensky RA, Yoo AJ, Lev MH, Boulouis G, Lauer A, Cougo P, Copen WA, Harris GJ, Warach S. Intravenous thrombolysis in unwitnessed stroke onset: MR WITNESS trial results. Ann Neurol 2018;83(5):980-993.Abstract
OBJECTIVE: Most acute ischemic stroke (AIS) patients with unwitnessed symptom onset are ineligible for intravenous thrombolysis due to timing alone. Lesion evolution on fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) correlates with stroke duration, and quantitative mismatch of diffusion-weighted MRI with FLAIR (qDFM) might indicate stroke duration within guideline-recommended thrombolysis. We tested whether intravenous thrombolysis ≤4.5 hours from the time of symptom discovery is safe in patients with qDFM in an open-label, phase 2a, prospective study (NCT01282242). METHODS: Patients aged 18 to 85 years with AIS of unwitnessed onset at 4.5 to 24 hours since they were last known to be well, treatable within 4.5 hours of symptom discovery with intravenous alteplase (0.9mg/kg), and presenting with qDFM were screened across 14 hospitals. The primary outcome was the risk of symptomatic intracranial hemorrhage (sICH) with preplanned stopping rules. Secondary outcomes included symptomatic brain edema risk, and functional outcomes of 90-day modified Rankin Scale (mRS). RESULTS: Eighty subjects were enrolled between January 31, 2011 and October 4, 2015 and treated with alteplase at median 11.2 hours (IQR = 9.5-13.3) from when they were last known to be well. There was 1 sICH (1.3%) and 3 cases of symptomatic edema (3.8%). At 90 days, 39% of subjects achieved mRS = 0-1, as did 48% of subjects who had vessel imaging and were without large vessel occlusions. INTERPRETATION: Intravenous thrombolysis within 4.5 hours of symptom discovery in patients with unwitnessed stroke selected by qDFM, who are beyond the recommended time windows, is safe. A randomized trial testing efficacy using qDFM appears feasible and is warranted in patients without large vessel occlusions. Ann Neurol 2018;83:980-993.
Threlkeld ZD, Bodien YG, Rosenthal ES, Giacino JT, Nieto-Castanon A, Wu O, Whitfield-Gabrieli S, Edlow BL. Functional networks reemerge during recovery of consciousness after acute severe traumatic brain injury. Cortex 2018;106:299-308.Abstract
Integrity of the default mode network (DMN) is believed to be essential for human consciousness. However, the effects of acute severe traumatic brain injury (TBI) on DMN functional connectivity are poorly understood. Furthermore, the temporal dynamics of DMN reemergence during recovery of consciousness have not been studied longitudinally in patients with acute severe TBI. We performed resting-state functional magnetic resonance imaging (rs-fMRI) to measure DMN connectivity in 17 patients admitted to the intensive care unit (ICU) with acute severe TBI and in 16 healthy control subjects. Eight patients returned for follow-up rs-fMRI and behavioral assessment six months post-injury. At each time point, we analyzed DMN connectivity by measuring intra-network correlations (i.e. positive correlations between DMN nodes) and inter-network anticorrelations (i.e. negative correlations between the DMN and other resting-state networks). All patients were comatose upon arrival to the ICU and had a disorder of consciousness (DoC) at the time of acute rs-fMRI (9.2 ± 4.6 days post-injury): 2 coma, 4 unresponsive wakefulness syndrome, 7 minimally conscious state, and 4 post-traumatic confusional state. We found that, while DMN anticorrelations were absent in patients with acute DoC, patients who recovered from coma to a minimally conscious or confusional state while in the ICU showed partially preserved DMN correlations. Patients who remained in coma or unresponsive wakefulness syndrome in the ICU showed no DMN correlations. All eight patients assessed longitudinally recovered beyond the confusional state by 6 months post-injury and showed normal DMN correlations and anticorrelations, indistinguishable from those of healthy subjects. Collectively, these findings suggest that recovery of consciousness after acute severe TBI is associated with partial preservation of DMN correlations in the ICU, followed by long-term normalization of DMN correlations and anticorrelations. Both intra-network DMN correlations and inter-network DMN anticorrelations may be necessary for full recovery of consciousness after acute severe TBI.
Schröder J, Cheng B, Malherbe C, Ebinger M, Köhrmann M, Wu O, Kang D-W, Liebeskind DS, Tourdias T, Singer OC, Campbell B, Luby M, Warach S, Fiehler J, Kemmling A, Fiebach JB, Gerloff C, Thomalla G. Impact of Lesion Load Thresholds on Alberta Stroke Program Early Computed Tomographic Score in Diffusion-Weighted Imaging. Front Neurol 2018;9:273.Abstract
Background and aims: Assessment of ischemic lesions on computed tomography or MRI diffusion-weighted imaging (DWI) using the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is widely used to guide acute stroke treatment. However, it has never been defined how many voxels need to be affected to label a DWI-ASPECTS region ischemic. We aimed to assess the effect of various lesion load thresholds on DWI-ASPECTS and compare this automated analysis with visual rating. Materials and methods: We analyzed overlap of individual DWI lesions of 315 patients from the previously published predictive value of fluid-attenuated inversion recovery study with a probabilistic ASPECTS template derived from 221 CT images. We applied multiple lesion load thresholds per DWI-ASPECTS region (>0, >1, >10, and >20% in each DWI-ASPECTS region) to compute DWI-ASPECTS for each patient and compared the results to visual reading by an experienced stroke neurologist. Results: By visual rating, median ASPECTS was 9, 84 patients had a DWI-ASPECTS score ≤7. Mean DWI lesion volume was 22.1 (±35) ml. In contrast, by use of >0, >1-, >10-, and >20%-thresholds, median DWI-ASPECTS was 1, 5, 8, and 10; 97.1% (306), 72.7% (229), 41% (129), and 25.7% (81) had DWI-ASPECTS ≤7, respectively. Overall agreement between automated assessment and visual rating was low for every threshold used (>0%: κ = 0.020 1%: κ = 0.151; 10%: κ = 0.386; 20% κ = 0.381). Agreement for dichotomized DWI-ASPECTS ranged from fair to substantial (≤7: >10% κ = 0.48; >20% κ = 0.45; ≤5: >10% κ = 0.528; and >20% κ = 0.695). Conclusion: Overall agreement between automated and the standard used visual scoring is low regardless of the lesion load threshold used. However, dichotomized scoring achieved more comparable results. Varying lesion load thresholds had a critical impact on patient selection by ASPECTS. Of note, the relatively low lesion volume and lack of patients with large artery occlusion in our cohort may limit generalizability of these findings.
Etherton MR, Barreto AD, Schwamm LH, Wu O. Neuroimaging Paradigms to Identify Patients for Reperfusion Therapy in Stroke of Unknown Onset. Front Neurol 2018;9:327.Abstract
Despite the proven efficacy of intravenous alteplase or endovascular thrombectomy for the treatment of patients with acute ischemic stroke, only a minority receive these treatments. This low treatment rate is due in large part to delay in hospital arrival or uncertainty as to the exact time of onset of ischemic stroke, which renders patients outside the current guideline-recommended window of eligibility for receiving these therapeutics. However, recent pivotal clinical trials of late-window thrombectomy now force us to rethink the value of a simplistic chronological formulation that "time is brain." We must recognize a more nuanced concept that the rate of tissue death as a function of time is not invariant, that still salvageable tissue at risk of infarction may be present up to 24 h after last-known well, and that those patients may strongly benefit from reperfusion. Multiple studies have sought to address this clinical dilemma using neuroimaging methods to identify a radiographic time-stamp of stroke onset or evidence of salvageable ischemic tissue and thereby increase the number of patients eligible for reperfusion therapies. In this review, we provide a critical analysis of the current state of neuroimaging techniques to select patients with unwitnessed stroke for revascularization therapies and speculate on the future direction of this clinically relevant area of stroke research.
Copen WA, Schwamm LH, González RG, Wu O, Harmath CB, Schaefer PW, Koroshetz WJ, Sorensen AG. Ischemic stroke: effects of etiology and patient age on the time course of the core apparent diffusion coefficient. Radiology 2001;221(1):27-34.Abstract
PURPOSE: To determine whether the evolution of the core apparent diffusion coefficient (ADC) of water in ischemic stroke varies with patient age or infarct etiology. MATERIALS AND METHODS: One hundred forty-seven patients with stroke underwent 236 diffusion-weighted magnetic resonance imaging examinations. Etiologies of lesions were classified according to predefined criteria; in 224 images, the diagnosis of lacune could be firmly established or excluded. ADC was measured in the center of each lesion and in contralateral normal-appearing brain. A model was used to describe the time course of relative ADC (rADC), which is calculated by dividing the lesion ADC by the contralateral ADC, and to test for age- or etiology-related differences in this time course. RESULTS: Transition from decreasing to increasing rADC was estimated at 18.5 hours after stroke onset. In subgroup analysis, transition was earlier in nonlacunes than in lacunes (P =.02). There was a trend toward earlier transition in patients older than the median age of 66.0 years, compared with younger patients (P =.06). Pseudonormalization was estimated at 216 hours. Among nonlacunes, the rate of subsequent rADC increase was more rapid in younger patients than in older patients (P =.001). Within the smaller sample of lacunes, however, no significant age-related difference in this rate was found. CONCLUSION: Differences in ADC depending on the patient's age and infarct etiology suggest differing rates of ADC progression.
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.
Sorensen AG, Wu O, Copen WA, Davis TL, Gonzalez RG, Koroshetz WJ, Reese TG, Rosen BR, Wedeen VJ, Weisskoff RM. Human acute cerebral ischemia: detection of changes in water diffusion anisotropy by using MR imaging. Radiology 1999;212(3):785-92.Abstract
PURPOSE: To (a) determine the optimal choice of a scalar metric of anisotropy and (b) determine by means of magnetic resonance imaging if changes in diffusion anisotropy occurred in acute human ischemic stroke. MATERIALS AND METHODS: The full diffusion tensor over the entire brain was measured. To optimize the choice of a scalar anisotropy metric, the performances of scalar indices in simulated models and in a healthy volunteer were analyzed. The anisotropy, trace apparent diffusion coefficient (ADC), and eigenvalues of the diffusion tensor in lesions and contralateral normal brain were compared in 50 patients with stroke. RESULTS: Changes in anisotropy in patients were quantified by using fractional anisotropy because it provided the best performance in terms of contrast-to-noise ratio as a function of signal-to-noise ratio in simulations. The anisotropy of ischemic white matter decreased (P = .01). Changes in anisotropy in ischemic gray matter were not significant (P = .63). The trace ADC decreased for ischemic gray matter and white matter (P < .001). The first and second eigenvalues decreased in both ischemic gray and ischemic white matter (P < .001). The third eigenvalue decreased in ischemic gray (P = .001) and white matter (P = .03). CONCLUSION: Gray matter is mildly anisotropic in normal and early ischemic states. However, early white matter ischemia is associated with not only changes in trace ADC values but also significant changes in the anisotropy, or shape, of the water self-diffusion tensor.
Dijkhuizen RM, Asahi M, Wu O, Rosen BR, Lo EH. Delayed rt-PA treatment in a rat embolic stroke model: diagnosis and prognosis of ischemic injury and hemorrhagic transformation with magnetic resonance imaging. J Cereb Blood Flow Metab 2001;21(8):964-71.Abstract
The authors characterized effects of late recombinant tissue plasminogen activator (rt-PA) administration in a rat embolic stroke model with magnetic resonance imaging (MRI), to assess potential MRI correlates, or predictors, or both, of rt-PA-induced hemorrhage. Diffusion-, perfusion-, and postcontrast T1-weighted MRI were performed between 4 and 9 hours and at 24 hours after embolic stroke in spontaneously hypertensive rats. Treatment with either rt-PA or saline was started 6 hours after stroke. A spectrophotometric hemoglobin assay quantified hemorrhage severity. Before treatment, relative cerebral blood flow index (rCBFi) and apparent diffusion coefficient (ADC) in the ischemic territory were 30% +/- 23% and 60% +/- 5% (of contralateral), respectively, which increased to 45% +/- 39% and 68% +/- 4% 2 hours after rt-PA. After 24 hours, rCBFi and ADC were 27% +/- 27% and 59 +/- 5%. Hemorrhage volume after 24 hours was significantly greater in rt-PA-treated animals than in controls (8.7 +/- 3.7 microL vs. 5.1 +/- 2.4 microL, P < 0.05). Before rt-PA administration, clear postcontrast T1-weighted signal intensity enhancement was evident in areas of subsequent bleeding. These areas had lower rCBFi levels than regions without hemorrhage (23% +/- 22% vs. 36% +/- 29%, P < 0.05). In conclusion, late thrombolytic therapy does not necessarily lead to successful reperfusion. Hemorrhage emerged in areas with relatively low perfusion levels and early blood-brain barrier damage. Magnetic resonance imaging may be useful for quantifying effects of thrombolytic therapy and predicting risks of hemorrhagic transformation.