Author(s)

S. M. Maniega, M. E. Bastin, P. A. Armitage, A. J. Farrall, T. K. Carpenter, P. J. Hand, V. Cvoro, C. S. Rivers, J. M. Wardlaw

ISBN

0022-3050

Publication year

2004

Periodical

Journal of Neurology Neurosurgery and Psychiatry

Periodical Number

12

Volume

75

Pages

1714-1718

Author Address

Full version

Objectives: Our purpose was to investigate whether differences exist in the values and temporal evolution of mean diffusivity () and fractional anisotropy (FA) of grey and white matter after human ischaemic stroke. Methods: Thirty two patients with lesions affecting both grey and white matter underwent serial diffusion tensor magnetic resonance imaging (DT-MRI) within 24 hours, and at 4-7 days, 10-14 days, 1 month, and 3 months after stroke. Multiple small circular regions of interest (ROI) were placed in the grey and white matter within the lesion and in the contralateral hemisphere. Values of {grey}, {white}, FA{grey} and FA{white} were measured in these ROI at each time point and the ratios of ischaemic to normal contralateral values ((R) and FA(R)) calculated. Results: and FA showed different patterns of evolution after stroke. After an initial decline, the rate of increase of {grey} was faster than {white} from 4-7 to 10-14 days. FA{white} decreased more rapidly than FA{grey} during the first week, thereafter for both tissue types the FA decreased gradually. However, FA{white} was still higher than FA{grey} at three months indicating that some organised axonal structure remained. This effect was more marked in some patients than in others. R{grey} was significantly higher than, (R){white} within 24 hours and at 10-14 days (p<0.05), and FAR{white} was significantly more reduced than FAR{grey} at all time points (p<0.001). Conclusions: The values and temporal evolution of and FA are different for grey and white matter after human ischaemic stroke. The observation that there is patient-to-patient variability in the degree of white matter structure remaining within the infarct at three months may have implications for predicting patient outcome.