A new approach to visualizing small and stenotic vasculature not readily visible with modern day diagnostic computed tomography angiography.
Coronary computed tomography angiography is a commonly utilized imaging technique to visualize a patient’s vasculature and potential vascular narrowing. Unfortunately, computed tomography angiography is unable to resolve small vessel cross-sectional area with a diagnostic accuracy of 50%. To overcome such shortcomings, vessel identification can be improved by a semi-automatic thresholding methodology. However, this method is highly dependent on the vessel size such that stenosis severity would be underestimated or overestimated based on the threshold selected. To address vessel measurements affected by arterial calcification, a pre-contrast image can be subtracted from a post contrast CT image to remove the unwanted artifact. Yet again, this method is not perfect and is limited by patient motion artifacts in between CT scans that yield inaccurate background subtraction. Clearly, an accurate and robust method that can measure vessel cross-section area (CSA) and stenosis severity in coronary CT angiography would be desirable.
UCI researchers have created a simple signal processing methodology that calculates the CSA of vessels. The method circumvents the problems associated by low resolution computed tomography systems at the voxel level by analyzing the conserved total signal in each area of interest. The proposed method improves the precision and accuracy of identifying small and narrowed vasculature by a factor of two and three, respectively.
|United States Of America||Published Application||20180153494||06/07/2018||2017-409|
The technology resides in the research and develop phase.