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Proceedings Paper

Optimal processing of isotropic 3D black-blood MRI For accurate estimation of vessel wall thickness
Author(s): Bernard Chiu; Niranjan Balu; Li Dong; Xihai Zhao; Chun Yuan; William S. Kerwin
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Paper Abstract

Quantification of vessel wall thickness is important in longitudinal monitoring of atherosclerosis. Black-blood MRI has been useful in measuring vessel wall thickness. Studies using two-dimensional (2D) imaging protocols measured wall thickness by matching the arterial wall and lumen boundaries on an acquisition plane. If the acquisition plane is oblique to the artery, the wall thickness would be overestimated by a factor that is dependent on the obliqueness angle. This problem can be understood as a three-dimensional (3D) surface mismatch problem, and we evaluated the effect of this problem by comparing the thickness measurements obtained using a 2D contour matching method and a 3D surface matching method. In addition to the surface mismatch problem, two other parameters may affect the wall thickness estimation: reslicing angle and slice thickness. We measured the wall thickness using images resliced perpendicular to the centerline of the vessel and quantified the difference between the thickness measurements obtained from parallel and centerline-based resliced images. Images obtained from a 2D MRI protocol typically have a slice thickness of 2mm, while the 3D MRI technique applied in this study produced images with sub-millimeter isotropic voxel size. To investigate the effect of slice thickness, we simulated 2mm-thick images by averaging the 3D black-blood image. Our results show that the wall thickness measured from 2mm-thick images was overestimated, especially in the carotid artery, which is associated with a larger obliqueness angle. This result underscores the advantage of the 3D isotropic acquisition technique in wall thickness measurement, especially in more tortuous vessels.

Paper Details

Date Published: 27 February 2010
PDF: 8 pages
Proc. SPIE 7627, Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment, 76270J (27 February 2010); doi: 10.1117/12.843870
Show Author Affiliations
Bernard Chiu, Univ. of Washington (United States)
Niranjan Balu, Univ. of Washington (United States)
Li Dong, Univ. of Washington (United States)
Xihai Zhao, Univ. of Washington (United States)
Chun Yuan, Univ. of Washington (United States)
William S. Kerwin, Univ. of Washington (United States)

Published in SPIE Proceedings Vol. 7627:
Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment
David J. Manning; Craig K. Abbey, Editor(s)

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