Each year, about 800,000 Americans have a new or recurrent stroke, or “brain attack.” Many strokes are caused by carotid stenosis, a build-up of plaque in the carotid arteries on either side of the neck that carry blood and oxygen to the brain; the result is brain damage and often other physical harm.
My team is developing software that analyzes ultrasound images. Different colors in the ultrasound images indicate where the plaque is located, and how severe it is. Our goal is to provide a tool that will predict which patients are at greater risk of stroke, which will help the physician decide on the best way to treat it.
Fellowship - Cleveland Clinic
Cleveland, OH USA
Medical Education - University of Liverpool Faculty of Medicine
Undergraduate - Leicester DeMontford University
Medical Sciences & Chemistry
Stroke is a major cause of morbidity and mortality among patients with cardiovascular disease, and the leading cause of long-term disability in the United States. Current imaging modalities are primarily used to determine the severity of luminal stenosis caused by carotid plaque. However, cerebrovascular accidents (CVA) are often associated with the rupture of plaques from regions with non-significant luminal stenosis. Accurate identification of these high-risk, rupture-prone plaques could prevent CVA in a significant number of patients.
Plaque composition is an additional and perhaps more important risk factor for CVA. Unfortunately, in clinical implementation, duplex ultrasound images are not cost-effective, and are technically unreliable and often invasive.
There is a clear unmet clinical need for a non-invasive, low-cost method to accurately characterize the composition of carotid plaques. My team is developing mathematical algorithms based upon quantitative ultrasound and acoustic radiation force impulse imaging that can better analyze ultrasound images of carotid arteries. The new system creates a spectrum in which different colors indicate where and how bad the plaque build-up is by using information from scattered ultrasound points during the creation of standard ultrasound images. Our goal is to provide a tool that will predict which patients are at increased risk for stroke.
View publications for D. Geoffrey Vince, PhD
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|US Patent||Patent Title||Issue Date||First-Named Inventor|
|8,630,492||System and Method for Identifying a Vascular Border||01/14/2014||D. Geoffrey Vince, PhD|
|8,622,910||System and Method of Acquiring Blood-Vessel Data||01/04/2014||D. Geoffrey Vince, PhD|
|6,200,268||Vascular Plaque Characterization||03/13/2001||D. Geoffrey Vince, PhD|
Dr. Vince will lead the commercialization arm of Cleveland Clinic, which turns medical breakthrough inventions into patient-benefiting medical products and companies.
With a new award from the Department of Defense, Dr. Vince will use non-invasive ultrasound and a novel artificial intelligence algorithm that predicts carotid artery plaque composition to detect patients at high risk of future stroke.