This Article Abstract Full Text (PDF) All Versions of this Article: 38/6/1826    most recent STROKEAHA.106.480145v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Lansberg, M. G. Search for Related Content PubMed PubMed Citation Articles by Lansberg, M. G. Related Collections CT and MRI Acute Cerebral Infarction Acute Stroke Syndromes Emergency treatment of Stroke Computerized tomography and Magnetic Resonance Imaging Thrombolysis Related Article

(Stroke. 2007;38:1826.)
© 2007 American Heart Association, Inc.

Original Contributions

Evaluation of the Clinical–Diffusion and Perfusion–Diffusion Mismatch Models in DEFUSE

Maarten G. Lansberg, MD, PhD; Vincent N. Thijs, MD, PhD; Scott Hamilton, PhD; Gottfried Schlaug, MD; Roland Bammer, PhD; Stephanie Kemp, BS; Gregory W. Albers, MD on behalf of the DEFUSE Investigators

From Stanford Stroke Center, Stanford University Medical Center, Palo Alto, Calif (M.G.L., S.H., R.B., S.K., G.W.A.); Department of Neurology, University Hospitals of Leuven, Belgium (V.N.T.); Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston Mass (G.S.).

Correspondence to Maarten G. Lansberg, MD, PhD, Stanford University, Stanford Stroke Center, 701 Welch Road, Suite B 325, Palo Alto, CA 94304. E-mail Lansberg{at}stanford.edu

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Background and Purpose— The perfusion–diffusion mismatch (PDM) model has been proposed as a tool to select acute stroke patients who are most likely to benefit from reperfusion therapy. The clinical–diffusion mismatch (CDM) model is an alternative method that is technically less challenging because it does not require perfusion-weighted imaging. This study is an evaluation of these 2 models in the DEFUSE dataset.

Methods— DEFUSE is an open-label multicenter study in which acute stroke patients were treated with intravenous tPA between 3 and 6 hours after symptoms onset and an MRI was obtained before and 3 to 6 hours after treatment. Presence of PDM and CDM was determined for each patient.

Results— Based on conventional predefined mismatch criteria, PDM was present in 54% of the DEFUSE population and CDM in 62%. There was no agreement beyond chance between the 2 mismatch models (kappa 0.07). The presence of PDM was associated with an increased chance of favorable clinical response after reperfusion (OR, 5.4; P=0.039). Reperfusion was not associated with a significant increase in the rate of favorable clinical response in patients with CDM (OR, 2.2; P=0.34). Using optimized mismatch criteria, determined retrospectively based on DEFUSE data, the OR for favorable clinical response was 70 (P=0.001) for PDM and 5.1 (P=0.066) for CDM.

Conclusion— The PDM model appears to be more accurate than the CDM model for selecting patients who are likely to benefit from reperfusion therapy in the 3- to 6-hour time window.

Key Words: acute treatment • diffusion-weighted MRI • ischemic stroke • outcome • plasminogen activator • perfusion-weighted MRI • reperfusion

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Treatment of acute stroke patients with tissue plasminogen activator (tPA) has been demonstrated to be effective in the 0- to 3-hour time-window after symptom onset.¹ With longer time windows, the efficacy of tPA gradually declines.² As a result, randomized trials of tPA administered beyond 3 hours have failed to show a significant treatment benefit. However, it has been hypothesized that specific subgroups of patients, characterized by the presence of an ischemic penumbra, may still benefit from reperfusion therapy at later treatment times.³

The implication of this hypothesis is that future randomized studies of a reperfusion therapy administered beyond 3 hours are more likely to be successful if patient enrollment is limited to patients with a significant amount of salvageable ischemic tissue. To select these patients, it is necessary to estimate the volume of threatened brain tissue that is still potentially salvageable in the acute setting. It has been proposed that patients with a perfusion–diffusion mismatch (PDM) are likely to have an ischemic penumbra. The PDM is obtained by subtracting the lesion volume on diffusion-weighted MRI (DWI) from the lesion volume on perfusion-weighted MRI (PWI). The results of the Diffusion and Perfusion Imaging Evaluation For Understanding Stroke Evolution (DEFUSE) study support the PDM hypothesis.⁴ The DEFUSE study demonstrated that for stroke patients treated with tPA 3 to 6 hours after symptom onset, early reperfusion was associated with a favorable clinical response in patients with a PDM, whereas patients without a mismatch did not appear to benefit from early reperfusion.⁴

The clinical–diffusion mismatch (CDM) has been proposed as an easier alternative to the PDM for selecting patients with salvageable ischemic tissue.⁵ It is based on the assumption that patients with severe clinical deficits, but with relatively small lesion volumes on DWI, are likely to have an ischemic penumbra. Davalos et al,⁵ who first described the CDM model, demonstrated that patients with a CDM experienced greater infarct growth than patients without a clinical-diffusion mismatch, particularly for the subgroup of patients who had not received thrombolytic therapy. The aim of this study was to compare the CDM model to the PDM model in terms of their ability to select patients who are likely to benefit from a reperfusion therapy administered in the 3- to 6-hour time-window.

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Patients were enrolled prospectively in the DEFUSE study. DEFUSE is a multicenter open-label study of intravenous tPA administered during the 3- to 6-hour time window after stroke onset. Detailed methods of DEFUSE have been published elsewhere.⁴ Briefly, patients with a clinical syndrome consistent with acute ischemic stroke were eligible for enrollment if they had a National Institutes of Health Stroke Scale Score (NIHSSS) >5, no evidence of hemorrhage on CT, and were able to undergo an MRI scan with DWI and PWI. All enrolled patients, regardless of MRI findings, were treated with standard dose intravenous tPA in the 3- to 6-hour time window after symptom onset. A repeat MRI scan was obtained 3 to 6 hours after tPA administration.

NIHSSSs were obtained at baseline and at 30 days by investigators with NIHSSS certification. DWI and PWI lesion volumes were determined by an experienced reader (V.T.) at the central reading center. DWI lesion volumes were calculated using a semi-automated thresholding method to identify regions of interests with high DWI signal intensity (exceeding the DWI signal intensity of the contralateral hemisphere by >3 SD). PWI lesion volumes were determined on Tmax maps that were generated according to the Ostergaard method.^6,7 Again, semi-automated thresholding was used to identify hypoperfused tissue, defined as a delay of at least 2 seconds on the Tmax map.⁸

For this study, the prespecified primary end point of DEFUSE was adopted: favorable clinical response, defined as an improvement in NIHSSS of 8 points between baseline and 30 days, or a 30-day NIHSSS of 0 or 1. Reperfusion was defined as a reduction in PWI lesion volume between the baseline and the follow-up MRI of at least 30%. For the primary analysis we used the prespecified DEFUSE definition for PDM and the previously published definition for CDM.⁵ PDM was defined according to DEFUSE criteria as a PWI lesion volume that is at least 20% and 10 mL larger than the DWI lesion volume. CDM was defined as a DWI lesion volume <25 mL and an NIHSSS 8, according to criteria proposed by Davalos et al⁵ Additional mismatch criteria with potentially superior discriminating power than the predefined mismatch criteria were determined based on review of the following scatter plots: (1) baseline DWI lesion volume versus PWI lesion volume in patients with early reperfusion; (2) baseline DWI lesion volume versus NIHSSS in patients with early reperfusion; (3) baseline DWI lesion volume versus PWI lesion volume in patients without early reperfusion; and (4) baseline DWI lesion volume versus NIHSSS in patients without early reperfusion. In each scatter plot, data points for patients with a favorable clinical response and for those without a favorable clinical response were marked differently to visualize the favorable clinical response rate in patients with a mismatch and in those without a mismatch.

For each patient, the presence of a PDM and a CDM were determined. Agreement between the 2 mismatch models was described as the concordance rate and as Cohen’s kappa, a chance adjusted measure of agreement. Sensitivity and specificity for detection of a PDM using CDM criteria were calculated. In addition, ORs for favorable response in patients with mismatch and reperfusion compared with patients with mismatch but without reperfusion were determined. ORs were compared using a method described by Altman and Bland.⁹ Data were analyzed using SPSS statistical software version 13.0. P=0.05 was deemed significant for all analyses.

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Seventy-four patients were enrolled in DEFUSE. Of these, 68 had technically adequate baseline PWI and DWI examinations and were included in this study. Baseline characteristics of these patients are listed in Table 1. A PDM was present in 54% (37/68; 95% CI, 43% to 66%) of patients, and a CDM was present in 62% (42/68; 95% CI, 50% to 72%). The agreement between the PDM model and the CDM model is displayed in Table 2. Agreement between the two models was present in 54% of patients (37/68; 95% CI, 43% to 66%). Cohen’s kappa is 0.07 (95% CI, –0.17 to 0.30), indicating no significant agreement beyond chance between the 2 mismatch models. The correlation between baseline PWI lesion volume and baseline NIHSSS was moderate (r=0.473; 95% CI, 0.27 to 0.65). This correlation did not improve significantly when cases without a PWI lesion (n=10) were excluded (r=0.505; 95% CI, 0.29 to 0.68), or if cases with a posterior circulation stroke (n=3) were excluded (r=0.500; 95% CI, 0.29 to 0.66). The CDM model detected PDM with 65% sensitivity (95% CI, 49% to 78%) and 42% specificity (26% to 59%). The positive predictive value was 57% (95% CI, 42% to 70%). The majority (14 of 18) of the patients who had a CDM but no PDM (false-positive CDM) were patients with small DWI and PWI lesions (<10 mL). The negative predictive value was 50% (95% CI, 32% to 68%). The group of patients who had a PDM but no CDM (false-negative CDM) consisted primarily (11 of 13) of patients with large DWI lesion volumes (>25 mL).

View this table: [in this window] [in a new window]   TABLE 1. Patient Characteristics (n=68)

View this table: [in this window] [in a new window]   TABLE 2. Agreement Between PDM and CDM Models in Patients With Technically Adequate Baseline PWI Examinations

Patients without a follow-up PWI or with a technically unsatisfactory follow-up PWI were excluded from the analysis regarding response to reperfusion, because reperfusion status could not be determined in these patients. As a result, 3 of the 37 patients with a PDM at baseline were excluded and 2 of the 42 patients with a CDM at baseline were excluded for the OR analysis. As reported previously, mismatch patients selected based on the predefined PDM model were more likely to achieve a favorable clinical response with reperfusion than without reperfusion (OR, 5.4; 95% CI, 1.1 to 25.8; P=0.039; n=34).⁴ In contrast, there was no significant association between reperfusion and favorable clinical response in mismatch patients selected based on the CDM model (OR, 2.2; 95% CI, 0.6 to 7.8; P=0.34; n=40). These ORs did not change significantly after adjusting for baseline predictors of favorable clinical response (Table 3). The distribution of DWI lesion volumes and NIHSSS as well as DWI lesion volumes and PWI lesion volumes are plotted for patients with early reperfusion and patients without early reperfusion (Figure). Based on these scatter plots, the following additional mismatch criteria with potentially superior discriminating power were identified: (1) CDM defined as NIHSSS 8 and DWI lesion volume <15 mL; and (2) PDM defined as a PWI lesion volume that is at least 10 mL larger than the DWI lesion volume and DWI lesion volume <15 mL. The retrospective models define a smaller percentage of the overall patient population as having a "mismatch" compared with the prespecified models (30% versus 54% for PDM; 49% versus 63% for CDM). The point estimates for the ORs for favorable clinical response associated with early reperfusion were numerically greater for the retrospective models (PDM: OR, 70; 95% CI, 3.7 to 1318, P=0.001; CDM: OR, 5.1, 95% CI, 1.0 to 25.6; P=0.066) than for the prespecified models. There are no statistically significant differences between the ORs for the a priori and the retrospectively determined mismatch models (P>0.1).

View this table: [in this window] [in a new window]   TABLE 3. ORs for Favorable Outcome in Mismatch Patients With Reperfusion vs Mismatch Patients Without Reperfusion

View larger version (26K): [in this window] [in a new window]   Displayed are scatter plots of DWI lesion volume vs PWI lesion volume (A) and DWI lesion volume vs NIHSSS (B) for patients with reperfusion. Also shown are scatter plots of DWI lesion volume vs PWI lesion volume (C) and DWI lesion volume vs NIHSSS (D) for patients without reperfusion. Points that fall within the shaded areas reflect patients with a mismatch. Patients who achieved a favorable clinical response are indicated by circles () and patients who did not have a favorable clinical response are indicated by triangles (). Note that if the mismatch area is limited to patients with a DWI lesion volume <15 mL (left of dashed line) the proportion of mismatch patients who achieved a favorable clinical response (circles) increases in patients with reperfusion (A and B), but does not change markedly in patients without reperfusion (C and D).

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

 
These data demonstrate that there is no significant agreement beyond chance between the prespecified PDM and CDM models in the DEFUSE data set. The predefined PDM model successfully selected patients who had a favorable clinical response associated with early reperfusion in the 3- to 6-hour time-window, whereas reperfusion was not associated with a significant increase in the rate of favorable clinical response in patients with a CDM.

The PDM model has been proposed by several investigators as a method to select patients who are likely to benefit from reperfusion therapies.^3,10–13 Two recent randomized controlled studies suggest that treatment with the thrombolytic agent desmoteplase in the 3- to 9-hour time window is associated with improved clinical outcome in patients selected based on the presence of a PDM.^14,15 The DEFUSE study also demonstrated that patients with a PDM are likely to benefit from reperfusion in the 3- to 6-hour time window.⁴ The CDM model was first proposed by Davalos et al⁵ as a potentially easier method to select patients who are likely to benefit from reperfusion. Their study showed that patients with CDM, particularly those who had not received tPA, have a higher probability of infarct growth than patients without CDM. This suggests that the CDM model may identify patients with tissue at risk for infarction who, therefore, could benefit from reperfusion.

There are several important differences between the study by Davalos et al and the current study. First, because no data were available on reperfusion status, the interaction between CDM, reperfusion, and infarct growth could not be assessed in the study by Davalos et al. Second, Davalos et al included stroke patients up to 12 hours, whereas the DEFUSE study had a shorter imaging time frame (3 to 6 hours), which may be more relevant for clinical decision making. Third, Davalos et al studied a heterogeneous population including patients who were not treated acutely and patients who were treated with thrombolytics or neuroprotective agents. In contrast, all patients in DEFUSE were treated with intravenous tPA between 3 and 6 hours after symptom onset. Fourth, MRIs were obtained before treatment in DEFUSE and before, during, or after acute treatment in the study by Davalos et al Finally, Davalos et al investigated different end points (change in NIHSSS, change in lesion volume) than the DEFUSE study (favorable clinical response to reperfusion).

Our study is unique in that there has been no previous studies that have directly compared the PDM model to the CDM model in regard to their ability to select patients who are likely to have a favorable clinical response associated with early reperfusion in the 3- to 6-hour time window. One previous report by Prosser et al compared the PDM model to the CDM model, but differed from our study in several aspects: data were accrued retrospectively, the study was limited to patients not treated with thrombolytics, whereas our prospective study involved only patients treated with thrombolytics, the follow-up scan was obtained 3 to 5 days after symptom onset compared with 3 to 6 hours after tPA treatment in our study.¹⁶ As a result, the study by Prosser et al could not determine the association between early reperfusion and favorable clinical response, which was the primary analysis of our study. In the study by Prosser et al the agreement between the 2 mismatch models was slightly better (kappa=0.32) than in our study (kappa=0.07), the sensitivity of the CDM model to detect a PDM was slightly worse (53% versus 65%), and the specificity was better (93% versus 50%).

The lack of agreement between the CDM and the PDM models in this study is a direct result of the moderate degree of correlation between PWI lesion volume and NIHSSS in our study. The correlation coefficient between the 2 measures was 0.47 (r²=22%), indicating that only 22% of the variability in the NIHSSS can be explained by the PWI lesion volume. In contrast, if the correlation between PWI lesion volume and NIHSSS had been high, agreement between the 2 mismatch models would have been excellent as well. The relative lack of correlation between PWI and NIHSSS may be attributable to several factors, including the possibility that brain tissue that has recently been reperfused is not yet functional and the insensitivity of the NIHSSS to hypoperfusion in certain areas of the brain. Several other studies have reported correlation coefficients between PWI and NIHSSS in approximately the same range (r² between 25% and 35%).^16–18 In contrast, 2 studies have reported strong correlations (r² of 70% and 92%).^19,20 Differences in patient selection, statistical approach, and PWI lesion volume assessment are among the likely variables responsible for this discrepancy.

Exploratory analyses of our dataset revealed that alternative mismatch definitions may be better than the prespecified definitions for identifying patients who are likely to benefit from reperfusion. Specifically, when CDM was defined as a DWI lesion volume <15 mL and an NIHSSS 8 it selected a subgroup of patients for whom there was a stronger association that approached statistical significance between early reperfusion and favorable clinical response. The alternative PDM criteria appeared to be superior to both the predefined PDM model as well as any of the CDM models, as evidenced by a numerically higher point estimate of the OR for favorable outcome associated with reperfusion. These results should, however, be interpreted with caution. First, because our patient groups are relatively small, CIs surrounding the ORs are large and there is no statistical difference between the various ORs. Second, the retrospective approach, used to determine the optimized mismatch criteria, requires that the validity of these new mismatch definitions is verified in separate independent datasets. Third, these models limit the number of patients defined as having a "mismatch" to a smaller percentage of the overall patient population (30% to 49% of population) compared with our predefined definitions (54% to 63% of population). Therefore, some patients who appear to benefit from reperfusion may be excluded using these more restrictive definitions.

To design a successful trial of a reperfusion therapy for acute stroke patients outside of the 3-hour time window, it would be preferable to enrich the study population with patients who have salvageable brain tissue. However, the optimal method to select these patients is not known. This study suggests that the PDM model is better-suited to select these patients than the CDM model. A prospective placebo-controlled study in which patient selection is randomized between the CDM model and the PDM model would be required to confirm this.

	Acknowledgments

 
Sources of Funding

The funding for this study was provided by NIH grants K23 NS051372 (M.G.L.); RO1 NS39325 (G.W.A.); and K24 NS044848 (G.W.A.).

Disclosures

None.

Received December 12, 2006; accepted January 6, 2007.

	References

Top Abstract Introduction Subjects and Methods Results Discussion References

 
1. Tissue plasminogen activator for acute ischemic stroke. The national institute of neurological disorders and stroke rt-PA stroke study group. N Engl J Med. 1995; 333: 1581–1587.[Abstract/Free Full Text]

2. Association of outcome with early stroke treatment: Pooled analysis of Atlantis, ECASS, and NINDS rt-PA stroke trials. Lancet. 2004; 363: 768–774.[CrossRef][Medline] [Order article via Infotrieve]

3. Albers GW. Expanding the window for thrombolytic therapy in acute stroke. The potential role of acute MRI for patient selection. Stroke. 1999; 30: 2230–2237.[Abstract/Free Full Text]

4. Albers GW, Thijs VN, Wechsler L, Kemp S, Schlaug G, Skalabrin E, Bammer R, Kakuda W, Lansberg MG, Shuaib A, Coplin W, Hamilton S, Moseley M, Marks MP, for the DEFUSE Investigators. Magnetic resonance imaging profiles predict clinical response to early reperfusion: The diffusion and perfusion imaging evaluation for understanding stroke evolution (defuse) study. Ann Neurol. 2006; 60: 508–517.[CrossRef][Medline] [Order article via Infotrieve]

5. Davalos A, Blanco M, Pedraza S, Leira R, Castellanos M, Pumar JM, Silva Y, Serena J, Castillo J. The clinical-DWI mismatch: A new diagnostic approach to the brain tissue at risk of infarction. Neurology. 2004; 62: 2187–2192.[Abstract/Free Full Text]

6. Ostergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis. Magn Reson Med. 1996; 36: 715–725.[Medline] [Order article via Infotrieve]

7. Ostergaard L, Sorensen AG, Kwong KK, Weisskoff RM, Gyldensted C, Rosen BR. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part ii: Experimental comparison and preliminary results. Magn Reson Med. 1996; 36: 726–736.[Medline] [Order article via Infotrieve]

8. Thijs VN, Somford DM, Bammer R, Robberecht W, Moseley ME, Albers GW. Influence of arterial input function on hypoperfusion volumes measured with perfusion-weighted imaging. Stroke. 2004; 35: 94–98.[Abstract/Free Full Text]

9. Altman DG, Bland JM. Interaction revisited: The difference between two estimates. BMJ. 2003; 326: 219.[Free Full Text]

10. Schellinger PD, Fiebach JB, Hacke W. Imaging-based decision making in thrombolytic therapy for ischemic stroke: Present status. Stroke. 2003; 34: 575–583.[Abstract/Free Full Text]

11. Davis SM, Donnan GA, Butcher KS, Parsons M. Selection of thrombolytic therapy beyond 3 h using magnetic resonance imaging. Curr Opin Neurol. 2005; 18: 47–52.[Medline] [Order article via Infotrieve]

12. Warach S. New imaging strategies for patient selection for thrombolytic and neuroprotective therapies. Neurology. 2001; 57: S48–S52.[Abstract/Free Full Text]

13. Kohrmann M, Juttler E, Fiebach JB, Huttner HB, Siebert S, Schwark C, Ringleb PA, Schellinger PD, Hacke W. MRI versus CT-based thrombolysis treatment within and beyond the 3 h time window after stroke onset: a cohort study. The Lancet Neurology. 2006; 5: 661–667.[CrossRef]

14. Hacke W, Albers G, Al-Rawi Y, Bogousslavsky J, Davalos A, Eliasziw M, Fischer M, Furlan A, Kaste M, Lees KR, Soehngen M, Warach S, for The DIAS Study Group. The desmoteplase in acute ischemic stroke trial (dias): A phase II MRI-based 9-hour window acute stroke thrombolysis trial with intravenous desmoteplase. Stroke. 2005; 36: 66–73.[Abstract/Free Full Text]

15. Furlan AJ, Eyding D, Albers GW, Al-Rawi Y, Lees KR, Rowley HA, Sachara C, Soehngen M, Warach S, Hacke W, for the DEDAS Investigators. Dose escalation of desmoteplase for acute ischemic stroke (DEDAS): Evidence of safety and efficacy 3 to 9 hours after stroke onset. Stroke. 2006; 37: 1227–1231.[Abstract/Free Full Text]

16. Prosser J, Butcher K, Allport L, Parsons M, MacGregor L, Desmond P, Tress B, Davis S. Clinical-diffusion mismatch predicts the putative penumbra with high specificity. Stroke. 2005; 36: 1700–1704.[Abstract/Free Full Text]

17. Nighoghossian N, Hermier M, Adeleine P, Derex L, Dugor JF, Philippeau F, Ylmaz H, Honnorat J, Dardel P, Berthezene Y, Froment JC, Trouillas P. Baseline magnetic resonance imaging parameters and stroke outcome in patients treated by intravenous tissue plasminogen activator. Stroke. 2003; 34: 458–463.[Abstract/Free Full Text]

18. Rivers CS, Wardlaw JM, Armitage PA, Bastin ME, Carpenter TK, Cvoro V, Hand PJ, Dennis MS. Do acute diffusion- and perfusion-weighted mri lesions identify final infarct volume in ischemic stroke? Stroke. 2006; 37: 98–104.[Abstract/Free Full Text]

19. Tong DC, Yenari MA, Albers GW, O’Brien M, Marks MP, Moseley ME. Correlation of perfusion- and diffusion-weighted mri with nihss score in acute (<6.5 hour) ischemic stroke. Neurology. 1998; 50: 864–870.[Abstract/Free Full Text]

20. Shih LC, Saver JL, Alger JR, Starkman S, Leary MC, Vinuela F, Duckwiler G, Gobin YP, Jahan R, Villablanca JP, Vespa PM, Kidwell CS. Perfusion-weighted magnetic resonance imaging thresholds identifying core, irreversibly infarcted tissue. Stroke. 2003; 34: 1425–1430.[Abstract/Free Full Text]

Related Article:

Mismatch and Defuse: Harvesting the Riches of Multicenter Neuroimaging-Based Stroke Studies

Chelsea S. Kidwell and Steven Warach
Stroke 2007 38: 1718-1719. [Extract] [Full Text] [PDF]

This article has been cited by other articles:

				M. Ebinger, T. Iwanaga, J. F. Prosser, D. A. De Silva, S. Christensen, M. Collins, M. W. Parsons, C. R. Levi, C. F. Bladin, P. A. Barber, et al. Clinical-Diffusion Mismatch and Benefit From Thrombolysis 3 to 6 Hours After Acute Stroke Stroke, July 1, 2009; 40(7): 2572 - 2574. [Abstract] [Full Text] [PDF]

				W.-D. Heiss and A. G. Sorensen Advances in Imaging Stroke, May 1, 2009; 40(5): e313 - e314. [Full Text] [PDF]

				R. I. Aviv, C. D. d'Esterre, B. D. Murphy, J. J. Hopyan, B. Buck, G. Mallia, V. Li, L. Zhang, S. P. Symons, and T.-Y. Lee Hemorrhagic Transformation of Ischemic Stroke: Prediction with CT Perfusion Radiology, March 1, 2009; 250(3): 867 - 877. [Abstract] [Full Text] [PDF]

				C. Rosso, N. Hevia-Montiel, S. Deltour, E. Bardinet, D. Dormont, S. Crozier, S. Baillet, and Y. Samson Prediction of Infarct Growth Based on Apparent Diffusion Coefficients: Penumbral Assessment without Intravenous Contrast Material Radiology, January 1, 2009; 250(1): 184 - 192. [Abstract] [Full Text] [PDF]

				M. J. Alberts, R. A. Felberg, L. R. Guterman, S. R. Levine, and for Writing Group 4 Atherosclerotic Peripheral Vascular Disease Symposium II: Stroke Intervention: State of the Art Circulation, December 16, 2008; 118(25): 2845 - 2851. [Full Text] [PDF]

				M. G. Lansberg, V. N. Thijs, R. Bammer, J.-M. Olivot, M. P. Marks, L. R. Wechsler, S. Kemp, and G. W. Albers The MRA-DWI Mismatch Identifies Patients With Stroke Who Are Likely to Benefit From Reperfusion Stroke, September 1, 2008; 39(9): 2491 - 2496. [Abstract] [Full Text] [PDF]

				A. G. Sorensen and W.-D. Heiss Advances in Imaging 2007 Stroke, February 1, 2008; 39(2): 276 - 278. [Full Text] [PDF]

				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]

This Article Abstract Full Text (PDF) All Versions of this Article: 38/6/1826    most recent STROKEAHA.106.480145v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Lansberg, M. G. Search for Related Content PubMed PubMed Citation Articles by Lansberg, M. G. Related Collections CT and MRI Acute Cerebral Infarction Acute Stroke Syndromes Emergency treatment of Stroke Computerized tomography and Magnetic Resonance Imaging Thrombolysis Related Article