CT blurring induced bias of quantitative in-stent restenosis analyses

Henk A. Marquering; Berend C. Stoel; Jouke Dijkstra; Koos Geleijns; Marion Persoon; J. Wouter Jukema M.D.; Geert J. Streekstra; Johan H. C. Reiber

doi:10.1117/12.771160

18 March 2008 CT blurring induced bias of quantitative in-stent restenosis analyses

Henk A. Marquering, Berend C. Stoel, Jouke Dijkstra, Koos Geleijns, Marion Persoon, J. Wouter Jukema M.D., Geert J. Streekstra, Johan H. C. Reiber

Author Affiliations +

Proceedings Volume 6913, Medical Imaging 2008: Physics of Medical Imaging; 69131J (2008) https://doi.org/10.1117/12.771160
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Rational and Objective: In CT systems, blurring is the main limiting factor for imaging in-stent restenosis. The aim of this study is to systematically analyze the effect of blurring related biases on the quantitative assessment of in-stent restenosis and to evaluate potential correction methods. Methods: 3D analytical models of a blurred, stented vessel are presented to quantify blurring related artifacts in the stent diameter measurement. Two correction methods are presented for an improved stent diameter measurement. We also examine the suitability of deconvolution techniques for correcting blurring artifacts. Results: Blurring results in a shift of the maximum of the signal intensity towards the center position of the stent, resulting in an underestimation of the stent diameter. This shift can be expressed as a function of the stent radius and width of the point spread function. The correction for this phenomenon reduces the error with 75 percent. Deconvolution reduces the blurring artifacts but introduces a ringing artifact. Conclusion: The analytical vessel models are well suited to study the influence of various parameters on blurring-induced artifacts. The blurring-related underestimation of the stent diameter can significantly be reduced using the presented corrections. Care should be taken into choosing suitable deconvolution filters since they may introduce new artifacts.

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Henk A. Marquering, Berend C. Stoel, Jouke Dijkstra, Koos Geleijns, Marion Persoon, J. Wouter Jukema M.D., Geert J. Streekstra, and Johan H. C. Reiber "CT blurring induced bias of quantitative in-stent restenosis analyses", Proc. SPIE 6913, Medical Imaging 2008: Physics of Medical Imaging, 69131J (18 March 2008); https://doi.org/10.1117/12.771160

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KEYWORDS

Deconvolution

Point spread functions

Imaging systems

Tissues

X-ray computed tomography

3D modeling

Data modeling

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