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(Stroke. 2003;34:e87.)
© 2003 American Heart Association, Inc.
Research Reports |
Department of Neuroradiology, University Hospital Eppendorf, University of Hamburg, Hamburg, Germany
Recently, permanent and transient early ADC renormalization has been reported in stroke patients.13 Several other articles with different focus report on patients with substantial decrease of lesion volume from initial DWI to outcome T2-weighted imaging. Differences in the reported rates of patients showing ADC normalization may be due to varieties in imaging time points and application of thrombolytic therapy. These reports resulted in some confusion among stroke physicians about the clinical value of the ADC.
The accompanying article by Nicoli et al provides novel insights into the pathophysiological basis of DWI in patients with acute ischemic stroke. Using spectroscopic imaging, the authors describe a heterogeneous cellular metabolic injury within the region of decreased ADC values. This finding may help us to understand why severe ADC decreases do not necessarily predict irreversible tissue damage in stroke patients.1,2
What do we know about the ADC? Diffusion in tissues is referred to as random walk of water molecules restricted by fibers, membranes, and macromolecules. Despite some lack of understanding about the biophysical background of ADC decrease, we have learned much about its pathophysiological correlates from stroke models.4 It has been shown by different experimental modalities that cerebral ischemia results in failure of ion pumps and anoxic cell membrane depolarization. Water shifts from the extracellular to the intracellular space with consecutive cell swelling. The increase of the intracellular osmolarity as a result of lactate accumulation is considered the reason for cell swelling beyond depolarization. The time course of these changes corresponds to the evolution of ADC decreases,4 even when the precise biophysical link to ADC is not exactly known. The fundamental association between ion homeostasis and ADC has been shown by blocking the Na+ channels, which results in a delay of the rapid ADC decrease.5 The association between the degree of the perfusion deficit and the severity of ADC decrease has been confirmed in humans6 and recently has been shown to be time dependent.7
Unfortunately, the relationship between ADC and prediction of final tissue injury is less explicit. The degree of ADC decrease has been related to the location and extent of neuronal injury.8 On the other hand, similar ADC values may reflect various histological states of ischemic tissue changes.9,10 However, recent animal studies show that ADC mapping performed before thrombolysis provides reliable risk assessment of brain injury but, as a result of uncertainties of postischemic reperfusion, does not allow precise outcome prediction.11 The link between severe absolute ADC decreases and progress to infarction is also missed in individual stroke patients.2 The observations of Nicoli et al suggest that the use of ADC thresholds as parameter of tissue viability should be discussed critically at least; regions with comparable ADC values may be associated with heterogeneous metabolic injury and, possibly, heterogeneous fate.
How can we exploit ADC values for stroke imaging? The degree of ADC decreases during stroke evolution tells us much about pathological tissue properties related to age, degree, and duration of the perfusion deficit, modulated by the local susceptibility to ischemia. These changes are associated with the local tissue impairment but not necessarily with tissue outcome. One should keep in mind that hyperacute lesions in ADC maps may reverse transiently or permanently, especially after thrombolytic treatment. However, most acute stroke patients will show the time course of further ADC decrease if reperfusion is not achieved in a timely manner.
ADC is just one side of the coin and should be interpreted in context with time after stroke onset, perfusion- and T2-weighted imaging, localization, occlusion type, and clinical data. Multiparametric prediction maps may facilitate the review of this complex information in the future.
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