9 March 2017 Detection of increased vasa vasorum in artery walls: improving CT number accuracy using image deconvolution
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Abstract
Changes in arterial wall perfusion are an indicator of early atherosclerosis. This is characterized by an increased spatial density of vasa vasorum (VV), the micro-vessels that supply oxygen and nutrients to the arterial wall. Detection of increased VV during contrast-enhanced computed tomography (CT) imaging is limited due to contamination from blooming effect from the contrast-enhanced lumen. We report the application of an image deconvolution technique using a measured system point-spread function, on CT data obtained from a photon-counting CT system to reduce blooming and to improve the CT number accuracy of arterial wall, which enhances detection of increased VV. A phantom study was performed to assess the accuracy of the deconvolution technique. A porcine model was created with enhanced VV in one carotid artery; the other carotid artery served as a control. CT images at an energy range of 25-120 keV were reconstructed. CT numbers were measured for multiple locations in the carotid walls and for multiple time points, pre and post contrast injection. The mean CT number in the carotid wall was compared between the left (increased VV) and right (control) carotid arteries. Prior to deconvolution, results showed similar mean CT numbers in the left and right carotid wall due to the contamination from blooming effect, limiting the detection of increased VV in the left carotid artery. After deconvolution, the mean CT number difference between the left and right carotid arteries was substantially increased at all the time points, enabling detection of the increased VV in the artery wall.
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Kishore Rajendran, Shuai Leng, Steven M. Jorgensen, Dilbar Abdurakhimova, Erik L. Ritman, Cynthia H. McCollough, "Detection of increased vasa vasorum in artery walls: improving CT number accuracy using image deconvolution", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101323O (9 March 2017); doi: 10.1117/12.2255676; https://doi.org/10.1117/12.2255676
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