Estimation of Contrast Concentration from Angiograms in Presence Of Vessel Overlap
SUMMARY
UCLA researchers have developed an image processing technique for quantitative measurement of brain hemodynamics using x-ray digital subtraction angiography (DSA) images. The technology generates color-coded parametric maps of cerebral blood perfusion that augment the image reader’s ability to diagnose several pathophysiological events in acute ischemic stroke patients that are not otherwise easily visible on grayscale angiograms.
BACKGROUND
Quantification of cerebral blood perfusion is of significant importance for evaluating therapeutic strategies and guiding management therapies in patients suffering from acute ischemic stroke. Currently used methods for evaluating cerebral blood perfusion such as Thrombolysis in Cerebral Infarction (TICI) and NIH Stroke Scale (NIHSS) are highly subjective and vary from one radiologist to the other. Algorithms have been previously proposed to quantify cerebral perfusion. However, these algorithms have not been widely adopted because of difficulties in implementing them in real-time on DSA systems and their inability to address the problem of overlapping vessels.
INNOVATION
UCLA researchers have developed an image processing technique for quantitative measurement of brain hemodynamics using x-ray digital subtraction angiography (DSA) images. The technology generates color-coded parametric maps of cerebral blood perfusion that augment the image reader’s ability to diagnose several pathophysiological events in acute ischemic stroke patients that are not otherwise easily visible on grayscale angiograms. The technology produces data on quantitative blood flow dynamics, resulting in more accurate data on multiple overlapping blood vessels within the imaging plane.
APPLICATIONS
ADVANTAGES
STATE OF DEVELOPMENT
The invention was successfully demonstrated in April 2014 and has been used to perform analysis on several hundreds of multi-center images.
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