Michael Howard Lev, M.D.
|Title||Professor of Radiology|
|Institution||Massachusetts General Hospital|
|Address||Massachusetts General Hospital|
Radiology, GRB 285
55 Fruit St
Boston MA 02114
Available: 07/23/12, Expires: 07/31/15
One of the first questions asked by stroke patients and their families at admission is if and how soon they can expect improvement in their functional deficits. The ability to quantify the likelihood of such improvement could therefore be of great clinical interest.
Important prognostic variables in current clinical practice include the admission NIH
Stroke Scale (NIHSS) score and admission “core infarct” lesion volume on magnetic resonance diffusion-weighted imaging (DWI). However, admission infarct volume and clinical stroke severity alone can only predict 30% to 50% of the variance in motor impairment improvement; thus a predictive model may also include information regarding the infarction location, structural integrity of descending motor pathways, and cortical activation in fMRI studies.
The accuracy of such prognostication
might be improved with the addition of kinetic cerebral perfusion parameters to predictive models. Whereas acute DWI lesions are highly specific for infarction, perfusion scans can provide complementary information by detecting regions of severely impaired blood flow with high probability of infarction. The precise spatial localization of cerebral hypoperfusion can substantially contribute to the accuracy of predictive models of stroke outcome, especially when used in combination with other clinical information.
In present study, we combined admission
clinical and topographic hemodynamic imaging
data to develop prognostic models for prediction of early functional improvement in
acute stroke patients presenting with single
extremity motor deficits. An automated
location-weighted atlas-based methodology
was used to quantify the effects of the complex spatial pattern of admission cerebral perfusion deficits on early functional outcome.
Local representatives can answer questions about the Profiles website or help with editing a profile or issues with profile data. For assistance with this profile: HMS/HSDM faculty should contact Human Resources at faculty_serviceshms.harvard.edu.