Cerebral network disruption as a possible mechanism for impaired recovery after acute pontine stroke - Förster, Alex; Griebe, Martin; Ottomeyer, Caroline; Roßmanith, Christina; Gass, Achim; Kern, Rolf; Hennerici, Michael G.; Szabo, Kristina (Cerebrovascular diseases, 2011)
Background: Recovery from stroke is presumed to be a function of a widespread cerebral network. Chronic white matter lesions (WML) have been proposed to be a predictor of poor outcome after acute stroke. We tested the hypothesis that the extent of WML has an effect on functional recovery in acute pontine stroke by disrupting the integrity of the supratentorial cerebral network. Methods: Seventeen patients with acute unilateral pontine stroke who had received a standardized stroke workup and additional diffusion tensor imaging (DTI) were studied. After grading the extent of WML according to the Fazekas scale and semiautomated lesion volume calculation, we compared patients with acute pontine infarction and advanced WML to those with absent or minimal WML regarding baseline characteristics, stroke subtype and clinical outcome. In addition, we used tract-based spatial statistics for voxel-wise analysis of the DTI-derived parameter fractional anisotropy in the white matter tracts. Results: The volume of WML ranged between 0.1 and 42.1 cm3 (mean = 15.9) and was graded as follows: 0 in 5.9%, 1 in 35.3%, 2 in 41.2% and 3 in 17.6%. Both patients with Fazekas grades 2-3 (p = 0.014) as well as those with larger WML volumes (p = 0.037) had severer functional deficits at the 3-month follow-up. White matter tracts displaying a significant decrease in fractional anisotropy values were the corpus callosum, the anterior thalamic radiation and the inferior fronto-occipital fasciculus. Conclusions: Chronic WML contribute to a less favorable clinical outcome after pontine stroke depending on (1) the extent of pre-existing WML and (2) the degree of disruption of cerebral connectivity as indicated by reduced tissue integrity in the white matter not affected by WML as detected by DTI and tract-based spatial statistics.
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