The overall goal of this research is to evaluate diffusion- and perfusion-weighted MR methodologies for the diagnostic advantages and predictive value they bring to the management of clinical stroke. At present, identification of stroke relies primarily on neurological assessment rather than physiological measurement, since the ability to study ischemic pathophysiology in humans has been limited. Rapid identification of the relevant lesions represents a particularly difficult challenge. We believe that diffusion- and perfusion-sensitive MRI techniques can improve the management of stroke in these regions by rapidly providing diagnostic information that is not available from neurological assessments and that cannot be obtained by presently-used CT or conventional MRI methods. We will focus on diffusion-weighted (DWI), perfusion-weighted MR (PWI), and time-resolved vascular MR imaging because of its inherent sensitivity to cellular energy failure and to the underlying hemodynamic behaviors. During all years of funding, parameters of stroke severity (volume, location, and circulation) measured by MR will be correlated to acute and chronic stroke severity measured by neurological assessments based on the National Institutes of Health Stroke Scale Scores (NIHSSS) and the Bamford Classification, and to the final T2-weighted images. We will build a comprehensive database of stroke severity (volume, location, and circulation) from both large and small strokes (anterior and posterior) from 24 patients per year.
Our aims are to determine the correlation of diffusion- and perfusion-weighted MR parameters of stroke severity with clinical assessment of stroke severity at the acute timepoint, identify diagnostic predictors of the clinical outcome of stroke, and to derive the relationship between vascular risk and metabolic status. The successful completion of this work will deliver an integrated battery of MR measurements best predictive of stroke severity and clinical outcome. It will also provide objective criteria beyond the neurological exam and a rapid, non-invasive tool for the neurologist to improve the diagnosis and management of patients with acute stroke.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Diagnostic Radiology Study Section (RNM)
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Jacobs, Tom P
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Stanford University
Schools of Medicine
United States
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Liu, Chunlei; Bammer, Roland; Moseley, Michael E (2007) Parallel imaging reconstruction for arbitrary trajectories using k-space sparse matrices (kSPA). Magn Reson Med 58:1171-81
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