(Stroke. 2003;34:2729.)
© 2003 American Heart Association, Inc.
Comments, Opinions, and Reviews |
From the University of California at Los Angeles Stroke Center (C.S.K., J.R.A., J.L.S.) and Department of Neurology (C.S.K., J.L.S.), University of California at Los Angeles Medical Center, and Department of Radiology, Brain Research Institute and Ahmanson-Lovelace Brain Mapping Center, David Geffin School of Medicine at University of California at Los Angeles (J.R.A.).
Correspondence to Chelsea S. Kidwell, MD, UCLA Stroke Center, 710 Westwood Plaza, UCLA Medical Center, Los Angeles, CA 90095. E-mail ckidwell{at}ucla.edu
| Abstract |
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Summary of Comment Based on these studies, various models for imaging the penumbra with MRI have been proposed, including the pioneering diffusion-perfusion mismatch model and later multivariate approaches. Each model has its own unique advantages and disadvantages.
Conclusions There now are sufficient data to support paradigm shifts in a variety of central tenets regarding MRI and the ischemic penumbra. These include the insights that diffusion-perfusion mismatch does not optimally define the penumbra; that early diffusion lesions are in part reversible and often include both irreversibly infarcted tissue and penumbra; that the visible zone of perfusion abnormality overestimates the penumbra by including regions of benign oligemia; that MRI is a very practical method for acute stroke imaging; and that therapeutic salvage of the ischemic penumbra has been demonstrated in humans using diffusion-perfusion MRI.
Key Words: ischemia magnetic resonance imaging, diffusion-weighted magnetic resonance imaging, perfusion-weighted penumbra
| Introduction |
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We predict that the impact of [advanced echoplanar MR techniques in acute stroke] ... may come to be viewed as analogous to the introduction of electrocardiography for the diagnosis of myocardial infarction, i.e., a rapid, reliable, objective, accurate, and essential emergency diagnostic test that will guide the development and application of acute therapeutic intervention.
Warach, Annals of Neurology, 1995
The promise of acute stroke therapies is anchored in the assumption that an ischemic penumbra exists in humans for several hours or more after symptom onset and that this tissue may be salvaged with restoration of blood flow or effective neuroprotective treatments. While recent trials have demonstrated that thrombolytic therapies are successful in the early time windows,1 there remains a crucial need to identify patients with existing salvageable tissue over longer time periods since these patients may benefit from late recanalization therapies.
There are a variety of definitions of the ischemic penumbra.25 For the purposes of this discussion, the penumbra will be defined as tissue that is at risk of infarction but still salvageable and that is the target of acute stroke therapy. Penumbral tissue needs to be distinguished from the ischemic core (tissue that is already irreversibly injured even if blood flow is reestablished) and from tissue experiencing benign oligemia, in which the mild reductions in tissue perfusion do not actually place the tissue at risk.
Stroke is a heterogeneous disorder, and the duration of the penumbra in humans varies substantially from person to person depending on a variety of factors, including location of the vessel occlusion, degree of collateral blood flow supply, intrinsic susceptibility to ischemia of tissues hypoperfused (eg, gray versus white matter), and other patient-specific factors. Direct visualization of the location and extent of the penumbra could greatly improve our ability to determine which patients may benefit from therapy and allow treatment decisions to be based on individualized pathophysiology rather than arbitrary chronological time windows.
In the past decade, diffusion- and perfusion-weighted MRI techniques have revolutionized the role of MRI in the evaluation of patients with acute cerebrovascular disease.6 Diffusion-weighted imaging provides a measure of tissue bioenergetic compromise and perfusion-weighted imaging a measure of hemodynamic compromise. The combined data from these 2 modalities can delineate the pathophysiological state of ischemia and may provide a practical means to rapidly and precisely identify the ischemic penumbra in the acute stroke setting. This article will address the successes and failures of initial MRI models of the ischemic penumbra as well as the unique opportunities and challenges to expanding the clinical applications of multimodal MRI of the penumbra in the acute stroke setting.
| MRI Models of the Ischemic Penumbra: Diffusion-Perfusion Mismatch |
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The most compelling data supporting the mismatch model come from observations that the natural history of early diffusion abnormalities in untreated patients is to grow over time into the area of the initial perfusion abnormality as the penumbra gradually fails.8 An analysis of data from placebo-treated patients enrolled in 2 neuroprotective studies demonstrated that lesions grew on average by 144% to 180% from the baseline to the follow-up imaging studies.9,10
In contrast, several analyses of patients experiencing reperfusion (either spontaneously or therapeutically with thrombolytics) have shown inhibition of diffusion lesion growth, suggesting actual salvage of the mismatch region (Figure 2). For example, Jansen and colleagues11 demonstrated inhibition of lesion growth in patients experiencing reperfusion compared with patients with persistent perfusion deficits or vessel occlusions. More recently, Parsons and colleagues12 compared MRI signatures in patients treated with intravenous tissue plasminogen activator within 6 hours of onset compared with a group of matched controls. They found a significant decrease in the amount of mismatch tissue that proceeded to infarction in the thrombolysis-treated group. Of note, substantial regions of diffusion-perfusion mismatch have been clearly visualized in acute posterior as well as anterior circulation ischemia, with salvage of mismatch regions also demonstrated after thrombolytic therapy.13
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A second important observation has been that significant diffusion-perfusion mismatch may be present up to 24 hours or more from symptom onset. Darby and colleagues14 demonstrated that while the presence and volume of mismatch progressively decreases over time, approximately 60% to 70% of patients up to 24 hours will still have substantial regions of mismatch (Figure 3). This finding is supported by studies previously performed in stroke patients employing positron emission tomography demonstrating penumbral tissue present in up to 16 to 48 hours after symptom onset.15,16 These findings suggest that the time window available for salvage of the penumbra in select patients may be much longer than the traditional, presumed 3- to 6-hour window and that diffusion-perfusion MRI has the ability to identify these patients.
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Challenges to the Mismatch Model
Despite these initial successes, recent studies have demonstrated that the simple diffusion-perfusion mismatch model is only a rough approximation of the ischemic penumbra. The standard mismatch model is based on 2 assumptions: (1) the border of visualizable perfusion-weighted imaging abnormality demarcates penumbral tissue from tissue not at risk, and (2) the border of the diffusion-weighted imaging abnormality demarcates core, irreversibly infarcted tissue from penumbral tissue (Figure 4). It is now known that both of these claims are flawed.
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Challenge 1 to the Mismatch Model: Penumbra Versus Benign Oligemia
The first major challenge to the mismatch model is differentiation of true penumbra from tissue experiencing benign oligemia. Initial studies performed in the 1970s by Astrup and colleagues17 identified 3 types of tissue with abnormal blood flow: (1) irreversibly damaged tissue (cerebral blood flow <6 to 10 mL/100 g per minute); (2) ischemic penumbral tissue: functionally silent tissue that could be salvaged if blood flow was restored (cerebral blood flow 10 to 20 mL/100 g per minute); and (3) oligemic tissue (cerebral blood flow below normal range but not at risk of infarction).
When the standard mismatch model was first promulgated, it was not widely appreciated that the border between abnormal- and normal-appearing tissue evident to the human interpreter on most perfusion maps includes some regions of benign oligemia. Careful subsequent studies have demonstrated that although the natural history of the diffusion abnormality is to grow into the mismatch zone, this growth generally encompasses a substantial proportion, but not all, of the region of visible perfusion abnormality.
How to best demarcate the outer limits of the perfusion abnormality to include only penumbra and not benign oligemia has been the focus of recent intensive research efforts. Several groups have attempted to address this issue by studying the evolution of diffusion and perfusion lesions in untreated patients. These natural history studies have the potential to differentiate penumbra from benign oligemia by assessing tissue fate in the worst-case scenario (recanalization does not occur). Tissue with an initial perfusion abnormality but no diffusion abnormality that proceeds to infarction is considered to have been within the penumbral region, while tissue with an initial perfusion abnormality that does not proceed to infarction is considered to have been within the benign oligemic region. A range of apparent diffusion coefficient (ADC) and perfusion thresholds have been identified that differentiate between penumbra and benign oligemia with modest degrees of accuracy.1824
However, several factors constrain the predictive value of the isolated ADC or perfusion thresholds determined in these studies. One limitation is that some patients likely experience spontaneous recanalization, even without interventional therapy, at undetermined time intervals after baseline imaging, contaminating the putative nonreperfusion population. Moreover, variations in methodology between centers limit the widespread utility of these findings. Furthermore, it is unlikely that isolated ADC or MR perfusion measures acquired at a single time point will be sufficient to make these differentiations because of interindividual variations in timing of scan acquisition, blood pressure, collateral flow, and other metabolic conditions.25,26
For these reasons, several groups have been developing multivariate models that incorporate information obtained from multiple MRI sequences to predict tissue outcome in untreated patients. Various models have been developed employing logistic regression analysis, generalized linear algorithms, multiparametric ISODATA techniques, and other automated strategies.7,27,28 All of these approaches have demonstrated good overall accuracy; however, they are limited in their generalizability since they have been based largely on patients imaged relatively late after onset. Additional studies with larger sample sizes and more uniform analytical methodologies are needed to confirm and extend these findings.
Challenge 2 to the Mismatch Model: Core Versus Penumbra
The second challenge to the mismatch model involves differentiation of the true penumbra from the ischemic core, ie, tissue that has already been irreversibly injured even if blood flow is reestablished. The mismatch model assumes that the initial diffusion lesion represents irreversibly infarcted core tissue. However, animal models have demonstrated that diffusion lesions may be partially or even fully reversible when reperfusion occurs within 2 to 3 hours.2933
Several groups have now replicated these findings in humans, demonstrating that the volume of tissue displaying diffusion abnormality may actually decrease (and in some cases diffusion lesions may be completely reversed) if blood flow is restored at an early time point (Figure 5).3438 MR studies in patients treated with intra-arterial thrombolysis have shown that, early after stroke onset, a very substantial volume of tissue showing diffusion abnormality is actually penumbra rather than core. In the University of California at Los Angeles (UCLA) series of patients undergoing vessel recanalization with intra-arterial thrombolytics, partial or complete reversal of initial diffusion abnormalities occurred in 44% of patients, with an average decrease in size of the initial diffusion-weighted imaging lesion volume of 52%.39 Although some of the tissue that shows therapeutically driven early reversal of diffusion lesions and abnormal ADC eventually redevelops diffusion abnormalities (late secondary injury),39 a substantial proportion of tissue, one third in the UCLA series, had evidence of sustained reversal of diffusion abnormalities and ultimate salvage at late imaging.
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On the basis of these findings, we have suggested a modified view of the ischemic penumbra as defined by MRI in which the penumbra includes not only diffusion-perfusion mismatch but also portions of the initial diffusion abnormality itself (Figure 6). An important implication of this modified view is that even select patients without diffusion-perfusion mismatch may still derive benefit from thrombolytic therapy.34
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The fact that diffusion abnormalities can be reversed and fully salvaged in some patients suggests that alternative approaches beyond the mismatch model may be able to more accurately distinguish core from penumbral tissue. Specifically, it is important to study patients undergoing vessel recanalization to develop models that can predict what will happen in the best-case scenario of early and sustained reperfusion. Our group has used an image coregistration technique to study the pretreatment MRI characteristics of tissue that either proceeded to infarction, developed hemorrhagic transformation, or was salvaged in patients who underwent recanalization therapies.
The fundamental paradigm for these studies is to obtain baseline multimodal MRI, perform an intervention that restores perfusion rapidly, and then obtain final outcome imaging. Only tissues that were already irreversibly infarcted before therapy will end as infarct regions, and mapping (coregistration) of final infarct lesions onto pretreatment scans will permit voxel-by-voxel analysis and identification of MR variables that distinguish core from penumbra (Figure 7). Intra-arterial thrombolysis is a particularly powerful technique for this type of study because not only does it permit rapid recanalization, but the final procedure angiogram affords full knowledge of the success and timing of recanalization in individual patients, allowing unambiguous identification of a population of patients experiencing early reperfusion.
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Figure 8 shows summary ADC histograms for tissue regions that evolved toward the 3 unique tissue fates (hemorrhagic transformation, infarction, or salvage). The histograms show that tissues that underwent hemorrhagic transformation had lower ADC values than tissues that became infarcted and that the salvaged (penumbral) tissue had the highest (most normal) ADC values. However, substantial overlap between the ADC ranges occurred within the 3 groups, indicating that the ADC value alone cannot fully predict tissue fate. This is further illustrated by calculations of the likelihood of infarction based on individual ADC thresholds. For example, this analysis suggests that a tissue region with ADC <550 µm2/s has a 50% likelihood of infarction even if reperfusion occurs. Use of newer ADC imaging techniques, such as fluid-attenuated inversion recovery (FLAIR) ADC imaging, may improve overall prediction ability of isolated ADC thresholds alone even further.40
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Multivariate models to predict irreversible infarction despite vessel recanalization, as well as risk of hemorrhagic transformation, have the potential to substantially improve predictive accuracy. In our series, models derived by logistic regression achieved overall accuracy rates of 80% to 81%. The most important predictive variables that entered into both these models were the ADC value (a measure of the intensity and the cumulative extent of ischemic tissue injury experienced up until the time of imaging) and the Tmax value (a time-to-peak measure of the severity of tissue hypoperfusion). By comparison, the mismatch model achieved an accuracy rate of only 53%.41 While this type of multivariate model has the potential to improve overall accuracy in identifying the ischemic penumbra, including some patients without mismatch who might benefit from therapy, it is important to recognize that diffusion-perfusion mismatch often provides a good, rapidly available estimation of the penumbra and a practical means for selecting candidates for therapy.
MRI as a Practical Stroke Tool
While the practicality of MRI as a neuroimaging method for hyperacute stroke has been questioned in the past, there is a growing body of data demonstrating both the feasibility and practicality of this approach. Current stroke MRI protocols take only 5 to 20 minutes to perform and are part of the routine hyperacute stroke workup in many academic stroke centers.34,4244 Modern high-speed computers can quantitatively predict the outcome of specific regions of brain tissue on the basis of statistical models developed from longitudinal studies in the best-case scenario of complete sustained reperfusion as well as in the worst-case scenario of no reperfusion. This type of postprocessing analysis can be performed within 5 to 15 minutes. Moreover, a growing number of community hospitals have 24-hour MRI capability.45 Finally, emerging data suggest that MRI may be able to accurately detect hyperacute intraparenchymal hemorrhage, obviating the need for CT studies and suggesting that MRI may be a suitable sole imaging modality for acute stroke.46,47
Future Directions
There are a number of important future directions for MR imaging of the penumbra. Further work is needed to validate quantitative perfusion imaging and demonstrate its ability to differentiate penumbra from benign oligemia. Of particular importance is the need for employment of standardized methodologies for postprocessing and analysis to allow comparison of data across studies and institutions.
Of note, any model developed in patients treated with thrombolytic therapy (either intra-arterial or intravenous) is constrained by a delay of 1 to 2 hours or more from the time of initial imaging to vessel recanalization. Moreover, some thrombolytic agents themselves, including tissue plasminogen activator, may have a toxic effect on cerebral tissue. The most accurate models with the greatest discriminatory power will likely be developed in patients undergoing endovascular procedures (eg, clot retrievers, lasers), which permit ultra-rapid recanalization. These procedures could theoretically be performed in the MRI suite with the appropriate catheters and devices, further minimizing delays.
In addition, rapidly advancing technology will allow validation and incorporation of new MR techniques, including MR spectroscopy, flow heterogeneity measures, and MRI oxygen extraction fraction techniques into acute stroke protocols.4850 These techniques have the potential to further augment existing multivariate models in delineating infarct core, penumbra, and benign oligemia.
Perhaps the most exciting potential application of MRI is its use as a selection tool for acute stroke treatments. The initial excitement surrounding the successful National Institute of Neurological Disorders and Stroke trials showing a benefit of intravenous tissue plasminogen activator when delivered within 3 hours of symptom onset has been tempered by 2 emerging facts: (1) few patients are currently being treated within the 3-hour window, and (2) identification of effective therapies beyond 3 hours from symptom onset remains elusive. While there is clearly a need to extend the time window for treatment, it is important to recognize that the number of patients who will benefit from treatment (those with an existing penumbra) progressively decreases over time. Therefore, a trial of an acute stroke therapy delivered later than 3 hours after onset has the greatest likelihood of showing efficacy if the trial incorporates a method to select appropriate patients for therapy, ie, those with existing salvageable penumbral tissue and decreased likelihood of developing complications from treatment. Multimodal MRI allows therapeutic decisions to be based on individual patient pathophysiological information, allowing the time window to be extended in appropriate patients. However, clinical studies of MRI-guided stroke therapies to date have largely consisted of small case series.12,51 To definitively prove the clinical utility of this technique, large-scale multicenter clinical trials must be performed to demonstrate not only decreased lesion volumes but also improved clinical outcome in MR-selected patients.
Currently, trials are under way that employ MRI for 3 separate purposes within clinical trial methodology (Table). The first involves studies that use MRI as an auxiliary or surrogate outcome measure, as was pioneered in neuroprotective treatment trials and now continues to be applied in both neuroprotective and reperfusion trials. The second type of trial is designed to confirm the clinical utility of the MRI mismatch hypothesis, as is being done in the DWI Evolution for Understanding Stroke Etiology (DEFUSE) and Echoplanar Imaging Thrombolysis Evaluation (EPITHET) trials. In these trials, all patients in a late time window are treated, irrespective of their pretreatment MR pattern, to test the hypothesis that patients with MRI penumbral patterns will respond to therapy while those with MRI nonpenumbral patterns will not. The third type of trial actually employs MRI to select for treatment only patients with appropriate MRI patterns. The Desmoteplase in Acute Stroke/Dose Escalation of Desmoteplase (DIAS/DEDAS) studies enroll patients with mismatch patterns, and the Stroke Evaluation for Late Endovascular Cerebral Thrombolysis With MR (SELECT MR) trial enrolls patients with penumbral patterns and low risk of hemorrhagic transformation on the basis of MR predictive models. These latter studies are designed to extend the time window for late treatments by selecting only patients with favorable MRI patterns.
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| Conclusions |
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| Acknowledgments |
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This work was supported in part by a grant from the American Heart Association (0170033N; Dr Kidwell), by a fellowship grant from the National Stroke Association (Dr Kidwell), and by grants K23 NS 02088 (Dr Kidwell), NS 39498 (Dr Alger), and K24 NS 02092 (Dr Saver) from the National Institute of Neurological Disorders and Stroke.
Received June 3, 2003; accepted July 17, 2003.
| References |
|---|
|
|
|---|
2. Hakim AM. The cerebral ischemic penumbra. Can J Neurol Sci. 1987; 14: 557559.[Medline] [Order article via Infotrieve]
3. Baron J. Mapping the ischaemic penumbra with PET: implications for acute stroke treatment. Cerebrovasc Dis. 1999; 9: 193201.[CrossRef][Medline] [Order article via Infotrieve]
4. Hossmann KA. Viability thresholds and the penumbra of focal ischemia. Ann Neurol. 1994; 36: 557565.[CrossRef][Medline] [Order article via Infotrieve]
5. Ginsberg MD, Pulsinelli WA. The ischemic penumbra, injury thresholds, and the therapeutic window for acute stroke. Ann Neurol. 1994; 36: 553554.[CrossRef][Medline] [Order article via Infotrieve]
6. Baird AE, Warach S. Magnetic resonance imaging of acute stroke. J Cereb Blood Flow Metab. 1998; 18: 583609.[CrossRef][Medline] [Order article via Infotrieve]
7. Schlaug G, Benfield A, Baird AE, et al. The ischemic penumbra: operationally defined by diffusion and perfusion MRI. Neurology. 1999; 53: 15281537.
8. Baird AE, Benfield A, Schlaug G, et al. Enlargement of human cerebral ischemic lesion volumes measured by diffusion-weighted magnetic resonance imaging. Ann Neurol. 1997; 41: 581589.[CrossRef][Medline] [Order article via Infotrieve]
9. Warach S, Pettigrew LC, Dashe JF, et al, for the Citicoline 010 Investigators. Effect of citicoline on ischemic lesions as measured by diffusion-weighted magnetic resonance imaging. Ann Neurol. 2000; 48: 713722.[CrossRef][Medline] [Order article via Infotrieve]
10. Warach S, Hacke W, Hsu C, et al. Effect of MaxiPOST on ischemic lesions in patients with acute stroke: the POST-010 MRI substudy. Stroke. 2002; 33: 383. Abstract.
11. Jansen O, Schellinger P, Fiebach J, et al. Early recanalisation in acute ischaemic stroke saves tissue at risk defined by MRI. Lancet. 1999; 353: 20362037.[CrossRef][Medline] [Order article via Infotrieve]
12. Parsons MW, Barber PA, Chalk J, et al. Diffusion- and perfusion-weighted MRI response to thrombolysis in stroke. Ann Neurol. 2002; 51: 2837.[CrossRef][Medline] [Order article via Infotrieve]
13. Ostrem JL, Kidwell CS, Saver JL, et al. Basilar artery occlusion: diffusion-perfusion MRI characterization of tissue salvage in patients receiving intra-arterial thrombolysis. Stroke. 2002; 33: 360.
14. Darby DG, Barber PA, Gerraty RP, et al. Pathophysiological topography of acute ischemia by combined diffusion-weighted and perfusion MRI. Stroke. 1999; 30: 20432052.
15. Marchal G, Beaudouin V, Rioux P, et al. Prolonged persistence of substantial volumes of potentially viable brain tissue after stroke: a correlative PET-CT study with voxel-based data analysis. Stroke. 1996; 27: 599606.
16. Heiss WD, Huber M, Fink GR, et al. Progressive derangement of periinfarct viable tissue in ischemic stroke. J Cereb Blood Flow Metab. 1992; 12: 193203.[Medline] [Order article via Infotrieve]
17. Astrup J, Symon L, Branston NM, Lassen N. Thresholds of cerebral ischemia. In: Schmiedek P, ed. Microsurgery for Stroke. Berlin, Germany: Springer; 1976: 1621.
18. Grandin CB, Duprez TP, Smith AM, et al. Which MR-derived perfusion parameters are the best predictors of infarct growth in hyperacute stroke? Comparative study between relative and quantitative measurements. Radiology. 2002; 223: 361370.
19. Neumann-Haefelin T, Wittsack HJ, Wenserski F, et al. Diffusion- and perfusion-weighted MRI: the DWI/PWI mismatch region in acute stroke. Stroke. 1999; 30: 15911597.
20. Thijs VN, Adami A, Neumann-Haefelin T, et al. Relationship between severity of MR perfusion deficit and DWI lesion evolution. Neurology. 2001; 57: 12051211.
21. Rohl L, Ostergaard L, Simonsen CZ, et al. Viability thresholds of ischemic penumbra of hyperacute stroke defined by perfusion-weighted MRI and apparent diffusion coefficient. Stroke. 2001; 32: 11401146.
22. Parsons MW, Yang Q, Barber PA, et al. Perfusion magnetic resonance imaging maps in hyperacute stroke: relative cerebral blood flow most accurately identifies tissue destined to infarct. Stroke. 2001; 32: 15811587.
23. Desmond PM, Lovell AC, Rawlinson AA, et al. The value of apparent diffusion coefficient maps in early cerebral ischemia. AJNR Am J Neuroradiol. 2001; 22: 12601267.
24. Oppenheim C, Grandin C, Samson Y, et al. Is there an apparent diffusion coefficient threshold in predicting tissue viability in hyperacute stroke? Stroke. 2001; 32: 24862491.
25. Fiehler J, Knab R, Reichenbach JR, et al. Apparent diffusion coefficient decreases and magnetic resonance imaging perfusion parameters are associated in ischemic tissue of acute stroke patients. J Cereb Blood Flow Metab. 2001; 21: 577584.[Medline] [Order article via Infotrieve]
26. Warach S. Tissue viability thresholds in acute stroke: the 4-factor model. Stroke. 2001; 32: 24602461.
27. Wu O, Koroshetz WJ, Ostergaard L, et al. Predicting tissue outcome in acute human cerebral ischemia using combined diffusion- and perfusion-weighted MR imaging. Stroke. 2001; 32: 933942.
28. Jacobs MA, Mitsias P, Soltanian-Zadeh H, et al. Multiparametric MRI tissue characterization in clinical stroke with correlation to clinical outcome: part 2. Stroke. 2001; 32: 950957.
29. Dijkhuizen RM, Berkelbach van der Sprenkel JW, Tulleken KA, Nicolay K. Regional assessment of tissue oxygenation and the temporal evolution of hemodynamic parameters and water diffusion during acute focal ischemia in rat brain. Brain Res. 1997; 750: 161170.[CrossRef][Medline] [Order article via Infotrieve]
30. Mintorovitch J, Moseley ME, Chileuitt L, et al. Comparison of diffusion- and T2-weighted MRI for the early detection of cerebral ischemia and reperfusion in rats. Magn Reson Med. 1991; 18: 3950.[Medline] [Order article via Infotrieve]
31. Hossmann KA, Fischer M, Bockhorst K, Hoehn-Berlage M. NMR imaging of the apparent diffusion coefficient (ADC) for the evaluation of metabolic suppression and recovery after prolonged cerebral ischemia. J Cereb Blood Flow Metab. 1994; 14: 723731.[Medline] [Order article via Infotrieve]
32. Hasegawa Y, Fisher M, Latour LL, et al. MRI diffusion mapping of reversible and irreversible ischemic injury in focal brain ischemia. Neurology. 1994; 44: 14841490.
33. Minematsu K, Li L, Sotak CH, et al. Reversible focal ischemic injury demonstrated by diffusion-weighted magnetic resonance imaging in rats. Stroke. 1992; 23: 13041310.
34. Kidwell CS, Saver JL, Mattiello J, et al. Thrombolytic reversal of acute human cerebral ischemic injury shown by diffusion/perfusion magnetic resonance imaging. Ann Neurol. 2000; 47: 462469.[CrossRef][Medline] [Order article via Infotrieve]
35. Lutsep HL, Nesbit GM, Berger RM, Coshow WR. Does reversal of ischemia on diffusion-weighted imaging reflect higher apparent diffusion coefficient values? J Neuroimaging. 2001; 11: 313316.[Medline] [Order article via Infotrieve]
36. Uno M, Harada M, Okada T, Nagahiro S. Diffusion-weighted and perfusion-weighted magnetic resonance imaging to monitor acute intra-arterial thrombolysis. J Stroke Cerebrovasc Dis. 2000; 9: 113120.[CrossRef][Medline] [Order article via Infotrieve]
37. Fiehler J, Foth M, Kucinski T, et al. Severe ADC decreases do not predict irreversible tissue damage in humans. Stroke. 2002; 33: 7986.
38. Chalela JA, Ezzeddine MA, Callabrese TM, et al. Diffusion and perfusion changes two hours after intravenous rt-PA therapy: a preliminary report. Stroke. 2002; 33: 356357.
39. Kidwell CS, Saver JL, Starkman S, et al. Late secondary ischemic injury in patients receiving intraarterial thrombolysis. Ann Neurol. 2002; 52: 698703.[CrossRef][Medline] [Order article via Infotrieve]
40. Latour LL, Warach S. Cerebral spinal fluid contamination of the measurement of the apparent diffusion coefficient of water in acute stroke. Magn Reson Med. 2002; 48: 478486.[CrossRef][Medline] [Order article via Infotrieve]
41. Kidwell CS, Alger JR, Saver JL, et al. MR signatures of infarction vs salvageable penumbra in acute human stroke: a preliminary model. Stroke. 2000; 31: 285.
42. Sunshine JL, Tarr RW, Lanzieri CF, et al. Hyperacute stroke: ultrafast MR imaging to triage patients prior to therapy. Radiology. 1999; 212: 325332.
43. Selim M, Fink JN, Kumar S, et al. Predictors of hemorrhagic transformation after intravenous recombinant tissue plasminogen activator: prognostic value of the initial apparent diffusion coefficient and diffusion-weighted lesion volume. Stroke. 2002; 33: 20472052.
44. Warach S, Rodriguez SU, Olan WJ. Routine screening for IV tPA therapy less than 3 hours with MRI: initial clinical experience. Stroke. 2001; 32: 371.
45. Liebeskind DS, Yang CK, Sayre J, Bakshi R. Neuroimaging of cerebral ischemia in clinical practice. Stroke. 2003; 34: 255. Abstract.
46. Kidwell CS, Chalela JA, Saver JL, et al. Hemorrhage Early MRI Evaluation (HEME) study: preliminary results of a multicenter trial of neuroimaging in patients with acute stroke symptoms within 6 hours of onset. Stroke. 2003; 34: 239. Abstract.
47. Schellinger PD, Fiebach JB, Gass A, et al. Accuracy of stroke MRI in hyperacute intracerebral hemorrhage <6 hours: a prospective standardized blinded multicenter study. Stroke. 2003; 34: 239.
48. Lee JM, Vo KD, An H, et al. Magnetic resonance cerebral metabolic rate of oxygen utilization in hyperacute stroke patients. Ann Neurol. 2003; 53: 227232.[CrossRef][Medline] [Order article via Infotrieve]
49. Parsons MW, Li T, Barber PA, et al. Combined (1)H MR spectroscopy and diffusion-weighted MRI improves the prediction of stroke outcome. Neurology. 2000; 55: 498505.
50. Ostergaard L, Sorensen AG, Chesler DA, et al. Combined diffusion-weighted and perfusion-weighted flow heterogeneity magnetic resonance imaging in acute stroke. Stroke. 2000; 31: 10971103.
51. Rother J, Schellinger PD, Gass A, et al. Effect of intravenous thrombolysis on MRI parameters and functional outcome in acute stroke <6 hours. Stroke. 2002; 33: 24382445.
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J.-M. Olivot, M. Mlynash, V. N. Thijs, S. Kemp, M. G. Lansberg, L. Wechsler, R. Bammer, M. P. Marks, and G. W. Albers Optimal Tmax Threshold for Predicting Penumbral Tissue in Acute Stroke Stroke, February 1, 2009; 40(2): 469 - 475. [Abstract] [Full Text] [PDF] |
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M. Castellanos, T. Sobrino, S. Pedraza, O. Moldes, J. M. Pumar, Y. Silva, J. Serena, M. Garcia-Gil, J. Castillo, and A. Davalos High plasma glutamate concentrations are associated with infarct growth in acute ischemic stroke Neurology, December 2, 2008; 71(23): 1862 - 1868. [Abstract] [Full Text] [PDF] |
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O. Y. Bang, J. L. Saver, J. R. Alger, S. Starkman, B. Ovbiagele, D. S. Liebeskind, and For the UCLA Collateral Investigators Determinants of the distribution and severity of hypoperfusion in patients with ischemic stroke Neurology, November 25, 2008; 71(22): 1804 - 1811. [Abstract] [Full Text] [PDF] |
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S. Siemonsen, T. Fitting, G. Thomalla, P. Horn, J. Finsterbusch, P. Summers, C. Saager, T. Kucinski, and J. Fiehler T2' Imaging Predicts Infarct Growth beyond the Acute Diffusion-weighted Imaging Lesion in Acute Stroke Radiology, September 1, 2008; 248(3): 979 - 986. [Abstract] [Full Text] [PDF] |
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A. E. Hillis, L. Gold, V. Kannan, L. Cloutman, J. T. Kleinman, M. Newhart, J. Heidler-Gary, C. Davis, E. Aldrich, R. Llinas, et al. Site of the ischemic penumbra as a predictor of potential for recovery of functions Neurology, July 15, 2008; 71(3): 184 - 189. [Abstract] [Full Text] [PDF] |
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K. Yamada, Y. Nagakane, H. Sasajima, M. Nakagawa, K. Mineura, T. Masunami, K. Akazawa, and T. Nishimura Incidental Acute Infarcts Identified on Diffusion-Weighted Images: A University Hospital-Based Study AJNR Am. J. Neuroradiol., May 1, 2008; 29(5): 937 - 940. [Abstract] [Full Text] [PDF] |
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H. Ay, E. M. Arsava, M. Vangel, B. Oner, M. Zhu, O. Wu, A. Singhal, W. J. Koroshetz, and A. G. Sorensen Interexaminer Difference in Infarct Volume Measurements on MRI: A Source of Variance in Stroke Research Stroke, April 1, 2008; 39(4): 1171 - 1176. [Abstract] [Full Text] [PDF] |
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F CHEN, Q LIU, H WANG, Y SUZUKI, N NAGAI, J YU, G MARCHAL, and Y NI Comparing two methods for assessment of perfusion-diffusion mismatch in a rodent model of ischaemic stroke: a pilot study Br. J. Radiol., March 1, 2008; 81(963): 192 - 198. [Abstract] [Full Text] [PDF] |
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B. H. Buck, D. S. Liebeskind, J. L. Saver, O. Y. Bang, S. W. Yun, S. Starkman, L. K. Ali, D. Kim, J. P. Villablanca, N. Salamon, et al. Early Neutrophilia Is Associated With Volume of Ischemic Tissue in Acute Stroke Stroke, February 1, 2008; 39(2): 355 - 360. [Abstract] [Full Text] [PDF] |
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M. S. Hussain and A. Shuaib Research Into Neuroprotection Must Continue ... but With a Different Approach Stroke, February 1, 2008; 39(2): 521 - 522. [Full Text] [PDF] |
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K. Butcher, M. Parsons, L. Allport, S. B. Lee, P. A. Barber, B. Tress, G. A. Donnan, S. M. Davis, and for the EPITHET Investigators Rapid Assessment of Perfusion-Diffusion Mismatch Stroke, January 1, 2008; 39(1): 75 - 81. [Abstract] [Full Text] [PDF] |
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T. Tourdias, V. Dousset, I. Sibon, E. Pele, P. Menegon, J. Asselineau, C. Pachai, F. Rouanet, P. Robinson, G. Chene, et al. Magnetization Transfer Imaging Shows Tissue Abnormalities in the Reversible Penumbra Stroke, December 1, 2007; 38(12): 3165 - 3171. [Abstract] [Full Text] [PDF] |
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L. B. Goldstein Acute Ischemic Stroke Treatment in 2007 Circulation, September 25, 2007; 116(13): 1504 - 1514. [Full Text] [PDF] |
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B. H. Buck, D. S. Liebeskind, J. L. Saver, O. Y. Bang, S. Starkman, L. K. Ali, D. Kim, J. P. Villablanca, N. Salamon, S. W. Yun, et al. Association of Higher Serum Calcium Levels With Smaller Infarct Volumes in Acute Ischemic Stroke Arch Neurol, September 1, 2007; 64(9): 1287 - 1291. [Abstract] [Full Text] [PDF] |
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H. B. van der Worp and J. van Gijn Acute Ischemic Stroke N. Engl. J. Med., August 9, 2007; 357(6): 572 - 579. [Full Text] [PDF] |
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F. Chen, Y. Suzuki, N. Nagai, X. Sun, H. Wang, J. Yu, G. Marchal, and Y. Ni Microplasmin and Tissue Plasminogen Activator: Comparison of Therapeutic Effects in Rat Stroke Model at Multiparametric MR Imaging Radiology, August 1, 2007; 244(2): 429 - 438. [Abstract] [Full Text] [PDF] |
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M. A. Jacobs, T. S. Ibrahim, and R. Ouwerkerk AAPM/RSNA Physics Tutorials AAPM/RSNA Physics Tutorials for Residents: MR Imaging: Brief Overview and Emerging Applications RadioGraphics, July 1, 2007; 27(4): 1213 - 1229. [Abstract] [Full Text] [PDF] |
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C. S. Kidwell and S. Warach Mismatch and Defuse: Harvesting the Riches of Multicenter Neuroimaging-Based Stroke Studies Stroke, June 1, 2007; 38(6): 1718 - 1719. [Full Text] [PDF] |
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H. P. Adams Jr, G. del Zoppo, M. J. Alberts, D. L. Bhatt, L. Brass, A. Furlan, R. L. Grubb, R. T. Higashida, E. C. Jauch, C. Kidwell, et al. Guidelines for the Early Management of Adults With Ischemic Stroke: A Guideline From the American Heart Association/American Stroke Association Stroke Council, Clinical Cardiology Council, Cardiovascular Radiology and Intervention Council, and the Atherosclerotic Peripheral Vascular Disease and Quality of Care Outcomes in Research Interdisciplinary Working Groups: The American Academy of Neurology affirms the value of this guideline as an educational tool for neurologists. Circulation, May 22, 2007; 115(20): e478 - e534. [Abstract] [Full Text] [PDF] |
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H. P. Adams Jr, G. del Zoppo, M. J. Alberts, D. L. Bhatt, L. Brass, A. Furlan, R. L. Grubb, R. T. Higashida, E. C. Jauch, C. Kidwell, et al. Guidelines for the Early Management of Adults With Ischemic Stroke: A Guideline From the American Heart Association/ American Stroke Association Stroke Council, Clinical Cardiology Council, Cardiovascular Radiology and Intervention Council, and the Atherosclerotic Peripheral Vascular Disease and Quality of Care Outcomes in Research Interdisciplinary Working Groups: The American Academy of Neurology affirms the value of this guideline as an educational tool for neurologists Stroke, May 1, 2007; 38(5): 1655 - 1711. [Abstract] [Full Text] [PDF] |
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R. Delgado-Mederos, A. Rovira, J. Alvarez-Sabin, M. Ribo, J. Munuera, M. Rubiera, E. Santamarina, O. Maisterra, P. Delgado, J. Montaner, et al. Speed of tPA-Induced Clot Lysis Predicts DWI Lesion Evolution in Acute Stroke Stroke, March 1, 2007; 38(3): 955 - 960. [Abstract] [Full Text] [PDF] |
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D. Kim, R. Jahan, S. Starkman, A. Abolian, C.S. Kidwell, F. Vinuela, G.R. Duckwiler, B. Ovbiagele, P.M. Vespa, S. Selco, et al. Endovascular Mechanical Clot Retrieval in a Broad Ischemic Stroke Cohort AJNR Am. J. Neuroradiol., November 1, 2006; 27(10): 2048 - 2052. [Abstract] [Full Text] [PDF] |
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O. Wu, S. Christensen, N. Hjort, R. M. Dijkhuizen, T. Kucinski, J. Fiehler, G. Thomalla, J. Rother, and L. Ostergaard Characterizing physiological heterogeneity of infarction risk in acute human ischaemic stroke using MRI Brain, September 1, 2006; 129(9): 2384 - 2393. [Abstract] [Full Text] [PDF] |
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B. S. Geisler, F. Brandhoff, J. Fiehler, C. Saager, O. Speck, J. Rother, H. Zeumer, and T. Kucinski Blood Oxygen Level-Dependent MRI Allows Metabolic Description of Tissue at Risk in Acute Stroke Patients Stroke, July 1, 2006; 37(7): 1778 - 1784. [Abstract] [Full Text] [PDF] |
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N. Henninger, K. M. Sicard, K. F. Schmidt, J. Bardutzky, and M. Fisher Comparison of Ischemic Lesion Evolution in Embolic Versus Mechanical Middle Cerebral Artery Occlusion in Sprague Dawley Rats Using Diffusion and Perfusion Imaging Stroke, May 1, 2006; 37(5): 1283 - 1287. [Abstract] [Full Text] [PDF] |
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G. Thomalla, C. Schwark, J. Sobesky, E. Bluhmki, J. B. Fiebach, J. Fiehler, O. Zaro Weber, T. Kucinski, E. Juettler, P. A. Ringleb, et al. Outcome and Symptomatic Bleeding Complications of Intravenous Thrombolysis Within 6 Hours in MRI-Selected Stroke Patients: Comparison of a German Multicenter Study With the Pooled Data of ATLANTIS, ECASS, and NINDS tPA Trials Stroke, March 1, 2006; 37(3): 852 - 858. [Abstract] [Full Text] [PDF] |
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J. L. Saver Time Is Brain--Quantified Stroke, January 1, 2006; 37(1): 263 - 266. [Abstract] [Full Text] [PDF] |
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A. L. Krol, S. B. Coutts, J. E. Simon, M. D. Hill, C.-H. Sohn, A. M. Demchuk, and for the VISION Study Group Perfusion MRI Abnormalities in Speech or Motor Transient Ischemic Attack Patients Stroke, November 1, 2005; 36(11): 2487 - 2489. [Abstract] [Full Text] [PDF] |
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C. A. Molina and J. L. Saver Extending Reperfusion Therapy for Acute Ischemic Stroke: Emerging Pharmacological, Mechanical, and Imaging Strategies Stroke, October 1, 2005; 36(10): 2311 - 2320. [Abstract] [Full Text] [PDF] |
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S. Suzuki, C. S. Kidwell, S. Starkman, J. L. Saver, G. Duckwiler, F. Vinuela, and B. Ovbiagele Use of Multimodal MRI and Novel Endovascular Therapies in a Patient Ineligible for Intravenous Tissue Plasminogen Activator Stroke, September 1, 2005; 36(9): e77 - e79. [Abstract] [Full Text] [PDF] |
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D. M. Kent, M. D. Hill, R. Ruthazer, S. B. Coutts, A. M. Demchuk, I. Dzialowski, O. Wunderlich, and R. von Kummer "Clinical-CT Mismatch" and the Response to Systemic Thrombolytic Therapy in Acute Ischemic Stroke Stroke, August 1, 2005; 36(8): 1695 - 1699. [Abstract] [Full Text] [PDF] |
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K.S. Butcher, M. Parsons, L. MacGregor, P.A. Barber, J. Chalk, C. Bladin, C. Levi, T. Kimber, D. Schultz, J. Fink, et al. Refining the Perfusion-Diffusion Mismatch Hypothesis Stroke, June 1, 2005; 36(6): 1153 - 1159. [Abstract] [Full Text] [PDF] |
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J. Sobesky, O. Z. Weber, F.-G. Lehnhardt, V. Hesselmann, M. Neveling, A. Jacobs, and W.-D. Heiss Does the Mismatch Match the Penumbra?: Magnetic Resonance Imaging and Positron Emission Tomography in Early Ischemic Stroke Stroke, May 1, 2005; 36(5): 980 - 985. [Abstract] [Full Text] [PDF] |
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S. M. Davis and G. A. Donnan Using Mismatch on MRI to Select Thrombolytic Responders: An Attractive Hypothesis Awaiting Confirmation Stroke, May 1, 2005; 36(5): 1100 - 1101. [Full Text] [PDF] |
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N. Hjort, K. Butcher, S.M. Davis, C.S. Kidwell, on behalf of the UCLA Thrombolysis Investigators, W.J. Koroshetz, J. Rother, P.D. Schellinger, S. Warach, and L. Ostergaard Magnetic Resonance Imaging Criteria for Thrombolysis in Acute Cerebral Infarct Stroke, February 1, 2005; 36(2): 388 - 397. [Abstract] [Full Text] [PDF] |
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L. Feng, C. L. Dumoulin, S. Dashnaw, R. D. Darrow, R. L. DeLaPaz, P. L. Bishop, and J. Pile-Spellman Feasibility of Stent Placement in Carotid Arteries with Real-time MR Imaging Guidance in Pigs Radiology, February 1, 2005; 234(2): 558 - 562. [Abstract] [Full Text] [PDF] |
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J. Sobesky, O. Z. Weber, F.-G. Lehnhardt, V. Hesselmann, A. Thiel, C. Dohmen, A. Jacobs, M. Neveling, and W.-D. Heiss Which Time-to-Peak Threshold Best Identifies Penumbral Flow?: A Comparison of Perfusion-Weighted Magnetic Resonance Imaging and Positron Emission Tomography in Acute Ischemic Stroke Stroke, December 1, 2004; 35(12): 2843 - 2847. [Abstract] [Full Text] [PDF] |
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S. E. Rose, A. L. Janke, M. Griffin, S. Finnigan, and J. B. Chalk Improved Prediction of Final Infarct Volume Using Bolus Delay-Corrected Perfusion-Weighted MRI: Implications for the Ischemic Penumbra Stroke, November 1, 2004; 35(11): 2466 - 2471. [Abstract] [Full Text] [PDF] |
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J. Alvarez-Sabin, C. A. Molina, M. Ribo, J. F. Arenillas, J. Montaner, R. Huertas, E. Santamarina, and M. Rubiera Impact of Admission Hyperglycemia on Stroke Outcome After Thrombolysis: Risk Stratification in Relation to Time to Reperfusion Stroke, November 1, 2004; 35(11): 2493 - 2498. [Abstract] [Full Text] [PDF] |
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M. Fisher and M. Ginsberg Current Concepts of the Ischemic Penumbra: Introduction Stroke, November 1, 2004; 35(11_suppl_1): 2657 - 2658. [Full Text] [PDF] |
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S Husain Clinical and radiological predictors of recanalisation: time to define a rapid scoring system J. Neurol. Neurosurg. Psychiatry, June 1, 2004; 75(6): 811 - 812. [Full Text] [PDF] |
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M. Arnold, K. Nedeltchev, C. Brekenfeld, U. Fischer, L. Remonda, G. Schroth, and H. Mattle Outcome of Acute Stroke Patients Without Visible Occlusion on Early Arteriography Stroke, May 1, 2004; 35(5): 1135 - 1138. [Abstract] [Full Text] [PDF] |
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I. Linfante Editorial Comment--Can MRI Reliably Detect Hyperacute Intracerebral Hemorrhage? Ask the Medical Student Stroke, February 1, 2004; 35(2): 506 - 507. [Full Text] [PDF] |
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