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Stroke. 2007;38:1718-1719
Published online before print May 10, 2007, doi: 10.1161/STROKEAHA.107.487215
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(Stroke. 2007;38:1718.)
© 2007 American Heart Association, Inc.


Editorials

Mismatch and Defuse

Harvesting the Riches of Multicenter Neuroimaging-Based Stroke Studies

Chelsea S. Kidwell, MD Steven Warach, MD, PhD

From the Georgetown University (C.S.K.), Washington, DC; the Washington Hospital Center (C.S.K., S.W.), Washington, DC; and the National Institute of Neurological Disorders and Stroke (S.W.), National Institutes of Health, Bethesda, Md.

Correspondence to Chelsea S. Kidwell, MD, 110 Irving St NW, East Building Rm 6126, Washington, DC 20010. E-mail Ck256{at}georgetown.edu

See related article, pages 1826–1830.


Key Words: acute stroke • magnetic resonance • thrombolysis

The goal of acute stroke evaluation is to determine not only stroke type (ischemic versus hemorrhagic) and localization (anatomical and vascular), but perhaps more importantly, to determine reversibility (presence of an ischemic penumbra that may be salvaged with acute therapy). Traditionally, neurologists have relied on history and neurological examination to provide much of this information. However, long experience has demonstrated that the neurological examination is imperfect at best in determining lesion localization and grossly limited in its ability to provide insights into the presence of penumbral tissue. This is evidenced by the only modest correlations between National Institutes of Health Stroke Scale (NIHSS) score and perfusion-weighted imaging lesion volume.1,2

The last decade has seen a striking growth in neuroimaging techniques that provide important real-time information about acute stroke pathophysiology. In the mid-1990s the advent of diffusion-weighted imaging revolutionized the role of MRI in acute stroke evaluation. Not only could diffusion-weighted imaging provide evidence of tissue injury within minutes of symptom onset, but also the diffusion-perfusion mismatch model offered a simple and practical means of identifying the ischemic penumbra and thus patients most likely to respond to reperfusion therapies, particularly in the late time window (>3 hours from symptom onset).3 Multiple prior studies have shown that if blood flow is not restored, the diffusion lesion will grow into the mismatch region and become a permanent infarct.4 Although this model continues to offer an imperfect approach to defining the penumbra, it has clearly been shown to provide a good approximation of penumbral tissue.5–7

Davalos and colleagues first proposed the clinical-diffusion model (CDM) as an alternative means to estimate the presence of penumbral tissue.8 According to this model, NIHSS score substitutes for perfusion-weighted imaging lesion volume because it was felt that perfusion imaging was technically challenging and that many centers with diffusion-weighted imaging capability did not have perfusion-weighted imaging capability. In their study of 166 patients with a hemispheric ischemic stroke of <12 hours duration, CDM was defined as a diffusion-weighted imaging lesion volume <25 mL and an NIHSS score ≥8. They found that patients with CDM were more likely to have infarct growth and early neurological deterioration compared with those without CDM.

In this month’s issue of Stroke, Lansberg and colleagues report the results of an analysis of clinical-diffusion and perfusion-diffusion mismatch models to predict the presence of penumbra from patients enrolled in the Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution (DEFUSE) trial.9,10 This report provides not only new important data addressing this specific question, but also reminds us of several additional important insights into acute stroke evaluation and neuroimaging.

First, the authors demonstrate in a large, well-designed, prospective treatment study of IV tissue plasminogen activator administered 3 to 6 hours from symptom onset, the limited role of the clinical-diffusion mismatch model for identifying salvageable brain tissue in the acute stroke setting. There was no agreement beyond chance between the 2 mismatch models. Moreover, patients with diffusion-perfusion mismatch model were more likely to achieve good clinical outcome with reperfusion compared with those without; however, this association was not true for patients with CDM. These findings are not unexpected. Our routine clinical experience has shown us that a small, strategically located lesion can mimic involvement of a much larger vascular territory and, alternatively, a large lesion of a relatively silent region can evade detection on the NIHSS score. It is also important to note that perfusion-weighted imaging is no longer technically challenging—most current scanners capable of diffusion imaging are fully equipped for performing perfusion imaging as well as postprocessing.

This is an important reminder that every step away from pathophysiology introduces error and will be a less accurate predictor of tissue outcome and physiological response to intervention. Second, we are reminded that the neurological examination, and by default the NIHSS, are imperfect instruments to describe ischemic pathology (by size, region). A third important insight from this study is that, to date, there is no perfusion postprocessing algorithm or mismatch definition that is clearly superior to others. This finding points to the need for standardization and comparisons on large pooled data sets.

In summary, the authors are to be congratulated not only for demonstrating the usefulness of perfusion-diffusion mismatch compared with clinical-diffusion mismatch in acute stroke therapy, but also providing us with a glimpse of the wealth of data and knowledge that will be forthcoming from large, well-designed, multicenter clinical trials and collaborations of neuroimaging-based acute stroke therapies.

Acknowledgments

Disclosures

None.

Footnotes

The opinions in this editorial are not necessarily those of the editors or of the American Heart Association.

References

1. Nuutinen J, Liu Y, Laakso MP, Karonen JO, Roivainen R, Vanninen RL, Partanen K, Ostergaard L, Sivenius J, Aronen HJ. Assessing the outcome of stroke: a comparison between MRI and clinical stroke scales. Acta Neurol Scand. 2006; 113: 100–107.[CrossRef][Medline] [Order article via Infotrieve]

2. Barber PA, Darby DG, Desmond PM, Yang Q, Gerraty RP, Jolley D, Donnan GA, Tress BM, Davis SM. Prediction of stroke outcome with echoplanar perfusion- and diffusion-weighted MRI. Neurology. 1998; 51: 418–426.[Abstract/Free Full Text]

3. Baird AE, Warach S. Magnetic resonance imaging of acute stroke. J Cereb Blood Flow Metab. 1998; 18: 583–609.[CrossRef][Medline] [Order article via Infotrieve]

4. Warach S, Pettigrew LC, Dashe JF, Pullicino P, Lefkowitz DM, Sabounjian L, Harnett K, Schwiderski U, Gammans R; Citicoline 010 Investigators. Effect of citicoline on ischemic lesions as measured by diffusion- weighted magnetic resonance imaging. Ann Neurol. 2000; 48: 713–722.[CrossRef][Medline] [Order article via Infotrieve]

5. Kidwell CS, Alger JR, Saver JL. Beyond mismatch: evolving paradigms in imaging the ischemic penumbra with multimodal magnetic resonance imaging. Stroke. 2003; 34: 2729–2735.[Abstract/Free Full Text]

6. Parsons MW, Barber PA, Chalk J, Darby DG, Rose S, Desmond PM, Gerraty RP, Tress BM, Wright PM, Donnan GA, Davis SM. Diffusion- and perfusion-weighted MRI response to thrombolysis in stroke. Ann Neurol. 2002; 51: 28–37.[CrossRef][Medline] [Order article via Infotrieve]

7. 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. 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]

8. 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]

9. Lansberg MG, Thijs VN, Hamilton S, Schlaug G, Bammer R, Kemp S, Albers GW; on behalf of The DEFUSE Investigators. Evaluation of the clinical-diffusion and perfusion-diffusion mismatch modles in defuse. Stroke. 2007; 38: 1826–1830.[Abstract/Free Full Text]

10. 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. 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]


Related Article:

Evaluation of the Clinical–Diffusion and Perfusion–Diffusion Mismatch Models in DEFUSE
Maarten G. Lansberg, Vincent N. Thijs, Scott Hamilton, Gottfried Schlaug, Roland Bammer, Stephanie Kemp, Gregory W. Albers on behalf of the DEFUSE Investigators
Stroke 2007 38: 1826-1830. [Abstract] [Full Text] [PDF]




This Article
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