Quantitative Imaging of Stroke

Studies suggest that the size of the cerebral infarct on diffusion weighted imaging may be an important consideration in the selection of patients for treatment with thrombolytic therapy. Furthermore, accuracy in the measurement of lesion size may be improved by the use of computational methodology. Thus, a clinical trial was initiated, in collaboration with the Stroke Imaging Repository Consortium, on the development of a novel computational algorithm for the segmentation of cerebral infarcts on diffusion weighted imaging.

The clinical study was designed to examine the following hypotheses:

The graph-cut algorithm can reduce inter-observer variability in the segmentation of cerebral infarct size from diffusion-weighted magnetic resonance images and/or from apparent diffusion coefficient images.

Infarct size estimated by the graph-cut algorithm from diffusion weighted imaging and/or the apparent diffusion coefficient imaging is predictive of final infarct size as assessed at follow-up imaging.

The study will be conducted in the following manner. Magnetic resonance imaging will be analyzed from at least 25 stroke patients. The series will include diffusion imaging obtained in the acute phase of stroke and T2-weighted imaging obtained in the same set of patients at the sub-acute phase. Final infarct size will be established based on T2-weighted images. Cases will only be included in which the infarct is visible on diffusion imaging.


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