Ischemic stroke continues to be one of leading sources of mortality and morbidity in the U.S. For clinicians who treat acute stroke victims, it is challenging to reliably discriminate salvageable from irreversibly injured tissue as well as to predict which patients are most likely to respond favorably to reperfusion therapy and which patients should have treatment withheld to avoid severe complications. Similar to the diagnostic parameters needed for the workup of acute stroke patients, the specific aims of this project will focus on: (1) the detection of irreversibly damaged tissue (stroke core);(2) the identification of potentially salvageable tissue (at-risk tissue);(3) the detection of leakage from the vascular into the interstitial space and prediction f hemorrhage (hemorrhagic transformation);and (4) the involvement of specific brain regions and their respective functions when assessing stroke severity and predicting outcome. Note that the difference between stroke core and at-risk tissue is often referred to as penumbra. With these four aims in mind, the overarching aim of this project is to collect CT and MR imaging data over a period of 4 years from 60 acute stroke victims (whose scans are performed ?30min apart) and to prospectively compare for the first time at such narrow time interval the ability of CT and MR to identify irreversibly damaged tissue, at-risk-tissue, and tissue that will most likely transform into (symptomatic) hemorrhage. This project will also assess each modality's ability to identify patients who will respond favorably to clot lysis/retrieval (a.k.a., reperfusion therapy) as well a those who will not benefit or who might actually sustain harm from the complications of reperfusion. Other project deliverables include improved MRI acquisition methods;optimized scan protocols for CT and MR in acute stroke;assessment of the role of iterative CT reconstructions in CT perfusion;new and refined outcome predictors;and a fully automated software that can be deployed at stroke centers nationwide (e.g., via NITRC). In summary, the project combines a sophisticated trial design with innovative imaging methods, medical image processing algorithms, and long-standing clinical and technical expertise in stroke imaging. This unique combination will produce invaluable clinical/imaging data from acute stroke patients;new clinical profiles and tools for patient triage;and a quantifiable assessment of the diagnostic strengths and weaknesses of advanced CT and MR methods as well as their clinical yield in acute stroke.
Stroke is the primary source of disability in the United States. Each year, 800,000 patients suffer a new stroke in the U.S., and approximately 90% of these patients do not receive any acute therapy. This is primarily because they present beyond the short treatment window for approved therapies, and clinicians have no aces to imaging markers that can identify salvageable tissue in late time windows. With roughly 500,000 stroke patients potentially qualifying for urgent stroke imaging in the U.S., developing a more objective decision-making process for selecting patients to receive acute therapy would be of tremendous value to public health by lowering patient morbidity and increasing cost savings. This project aims to compare for the first time the diagnostic ability of CT and MR to reliably identify ! irreversibly damaged tissue, at-risk (but potentially salvageable) tissue, and the leakiness of injured vessels in acute stroke patients. It will also assess each modality's ability to identify patients who will respond favorably to clot lysis/retrieval (a.k.a., reperfusion therapy) as well a those patients who would not benefit or who might actually sustain harm from the complications of reperfusion. In addition, this project delivers improved MRI acquisition methods, optimized scan protocols for CT and MR in acute stroke, information about the role of a novel family of CT reconstruction in CT perfusion imaging, as well as predictors that take into account the location of a stroke lesion and its likely impact on a patient's clinical disability.
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