Correction of lumen contrast-enhancement influence on non-calcified coronary atherosclerotic plaque quantification on CT

被引:0
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作者
Wisnumurti Kristanto
Volkan Tuncay
Rozemarijn Vliegenthart
Peter M. A. van Ooijen
Matthijs Oudkerk
机构
[1] University of Groningen,Department of Radiology, Center for Medical Imaging – North East Netherlands, University Medical Center Groningen
关键词
Non-calcified atherosclerotic plaque; Computed-tomography; Lumen influence; Contrast-enhancement;
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摘要
Lumen contrast-enhancement influences non-calcified atherosclerotic plaque Hounsfield-unit (HU) values in computed tomography (CT). This study aimed to construct and validate an algorithm to correct for this influence. Three coronary vessel phantoms with 1, 2, and 4 mm circular hollow lumina; with normal and plaque-infested walls were scanned simultaneously in oil using a dual-source CT scanner. Scanning was repeated as the lumina were alternately filled with water and four contrast solutions (100–400 HU, at 100 HU intervals). Images were reconstructed at 0.4 mm x–y pixel size. Pixel-by-pixel comparisons of contrast-enhanced and non-contrast-enhanced images confirmed exponential declining patterns in lumen contrast-enhancement influence on wall HU-values from the lumen border (y = Ae−λx + c). The median difference of the inside and outside 2-pixel radius part of the contrast-enhanced coronary phantom wall to the reference (non-contrast-enhanced images) was 45 and 2 HU, respectively. Based on the lumen contrast-enhancement influence patterns, a generalized correction algorithm was formulated. Application of the generalized correction algorithm to the inside 2-pixel radius part of the wall reduced the median difference to the reference to 4 HU. In conclusion, lumen contrast-enhancement influence on the vessel wall can be defined by an exponential approximation, allowing correction of the CT density of the vessel wall closest to the lumen. With this correction, a more accurate determination of vessel wall composition can be made.
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页码:429 / 436
页数:7
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