High-definition computed tomography for coronary artery stents imaging: Initial evaluation of the optimal reconstruction algorithm

Cui, Xiaoming; Li, Tao; Li, Xin; Zhou, Weihua

doi:10.1016/j.ejrad.2015.02.004

Cited by 10 publications

(13 citation statements)

References 24 publications

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“…On the other hand, in vivo studies that quantitatively assessed the effect of CT kernels on coronary artery stent blooming artifacts are scarce [ 18 – 20 , 32 ]. Hong et al [ 18 ] and Seifarth et al [ 20 ] assessed artificial coronary stent lumen narrowing using 16-slice scanners and image reconstruction with both sharp (B46f) and medium-smooth (B30f) kernels.…”

Section: Discussionmentioning

confidence: 99%

Coronary Stent Artifact Reduction with an Edge-Enhancing Reconstruction Kernel – A Prospective Cross-Sectional Study with 256-Slice CT

et al. 2016

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PurposeMetallic artifacts can result in an artificial thickening of the coronary stent wall which can significantly impair computed tomography (CT) imaging in patients with coronary stents. The objective of this study is to assess in vivo visualization of coronary stent wall and lumen with an edge-enhancing CT reconstruction kernel, as compared to a standard kernel.MethodsThis is a prospective cross-sectional study involving the assessment of 71 coronary stents (24 patients), with blinded observers. After 256-slice CT angiography, image reconstruction was done with medium-smooth and edge-enhancing kernels. Stent wall thickness was measured with both orthogonal and circumference methods, averaging thickness from diameter and circumference measurements, respectively. Image quality was assessed quantitatively using objective parameters (noise, signal to noise (SNR) and contrast to noise (CNR) ratios), as well as visually using a 5-point Likert scale.ResultsStent wall thickness was decreased with the edge-enhancing kernel in comparison to the standard kernel, either with the orthogonal (0.97 ± 0.02 versus 1.09 ± 0.03 mm, respectively; p<0.001) or the circumference method (1.13 ± 0.02 versus 1.21 ± 0.02 mm, respectively; p = 0.001). The edge-enhancing kernel generated less overestimation from nominal thickness compared to the standard kernel, both with the orthogonal (0.89 ± 0.19 versus 1.00 ± 0.26 mm, respectively; p<0.001) and the circumference (1.06 ± 0.26 versus 1.13 ± 0.31 mm, respectively; p = 0.005) methods. The edge-enhancing kernel was associated with lower SNR and CNR, as well as higher background noise (all p < 0.001), in comparison to the medium-smooth kernel. Stent visual scores were higher with the edge-enhancing kernel (p<0.001).ConclusionIn vivo 256-slice CT assessment of coronary stents shows that the edge-enhancing CT reconstruction kernel generates thinner stent walls, less overestimation from nominal thickness, and better image quality scores than the standard kernel.

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Section: Discussionmentioning

confidence: 99%

Coronary Stent Artifact Reduction with an Edge-Enhancing Reconstruction Kernel – A Prospective Cross-Sectional Study with 256-Slice CT

et al. 2016

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“…In a 256-slice scanner study using a CT pixel attenuation profile method on 28 stents, Oda et al [19] measured less blooming artifacts with a sharp kernel (CD), in comparison to a soft (CB) kernel. Of note, the observers in the study of Cui et al [32] were blinded to the type of reconstruction kernel, in contrast to former studies [18][19][20]. However, in the study of Cui et al [32], stent blooming quantification was performed by comparing the stent inner diameter to the nominal stent diameter.…”

Section: Discussionmentioning

confidence: 99%

“…Of note, the observers in the study of Cui et al [32] were blinded to the type of reconstruction kernel, in contrast to former studies [18][19][20]. However, in the study of Cui et al [32], stent blooming quantification was performed by comparing the stent inner diameter to the nominal stent diameter. As mentioned by the authors, the true in vivo stent diameter depends on the vessel shape, the dilatation pressure during the stenting procedure, with possible recoil after placement, and does not necessarily correspond to the nominal stent diameter provided by the manufacturer [32].…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, in vivo studies that quantitatively assessed the effect of CT kernels on coronary artery stent blooming artifacts are scarce [18][19][20]32]. Hong et al [18] and Seifarth et al [20] assessed artificial coronary stent lumen narrowing using 16-slice scanners and image reconstruction with both sharp (B46f) and medium-smooth (B30f) kernels.…”

Section: Discussionmentioning

confidence: 99%

“…However, in the study of Cui et al [32], stent blooming quantification was performed by comparing the stent inner diameter to the nominal stent diameter. As mentioned by the authors, the true in vivo stent diameter depends on the vessel shape, the dilatation pressure during the stenting procedure, with possible recoil after placement, and does not necessarily correspond to the nominal stent diameter provided by the manufacturer [32]. In our study, we used blinded observers with randomized assignment to kernel measurement.…”

Section: Discussionmentioning

confidence: 99%

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Coronary Stent Artifact Reduction With an Edge-Enhancing Reconstruction Kernel - A Prospective Cross-Sectional Study With 256-Slice Ct

Tan¹,

Soulez²,

Stevens³

et al. 2015

Canadian Journal of Cardiology

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PurposeMetallic artifacts can result in an artificial thickening of the coronary stent wall which can significantly impair computed tomography (CT) imaging in patients with coronary stents. The objective of this study is to assess in vivo visualization of coronary stent wall and lumen with an edge-enhancing CT reconstruction kernel, as compared to a standard kernel. MethodsThis is a prospective cross-sectional study involving the assessment of 71 coronary stents (24 patients), with blinded observers. After 256-slice CT angiography, image reconstruction was done with medium-smooth and edge-enhancing kernels. Stent wall thickness was measured with both orthogonal and circumference methods, averaging thickness from diameter and circumference measurements, respectively. Image quality was assessed quantitatively using objective parameters (noise, signal to noise (SNR) and contrast to noise (CNR) ratios), as well as visually using a 5-point Likert scale. ResultsStent wall thickness was decreased with the edge-enhancing kernel in comparison to the standard kernel, either with the orthogonal (0.97 ± 0.02 versus 1.09 ± 0.03 mm, respectively; p<0.001) or the circumference method (1.13 ± 0.02 versus 1.21 ± 0.02 mm, respectively; p = 0.001). The edge-enhancing kernel generated less overestimation from nominal thickness compared to the standard kernel, both with the orthogonal (0.89 ± 0.19 versus 1.00 ± 0.26 mm, respectively; p<0.001) and the circumference (1.06 ± 0.26 versus 1.13 ± 0. mm, respectively; p = 0.005) methods. The edge-enhancing kernel was associated with lower SNR and CNR, as well as higher background noise (all p < 0.001), in comparison to the medium-smooth kernel. Stent visual scores were higher with the edge-enhancing kernel (p<0.001). ConclusionIn vivo 256-slice CT assessment of coronary stents shows that the edge-enhancing CT reconstruction kernel generates thinner stent walls, less overestimation from nominal thickness, and better image quality scores than the standard kernel.

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A noise-optimized virtual monochromatic reconstruction algorithm improves stent visualization and diagnostic accuracy for detection of in-stent re-stenosis in lower extremity run-off CT angiography

et al. 2016

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• The impact of noise-optimized virtual monochromatic imaging on stent visualization was assessed. • Virtual monochromatic imaging significantly improves stent lumen visualization and diagnostic confidence. • At 80 keV diagnostic performance for detection of in-stent restenosis was increased. • 80 keV virtual monochromatic images are recommended for stent evaluation of lower extremity vasculature.

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High-definition computed tomography for coronary artery stents imaging: Initial evaluation of the optimal reconstruction algorithm

Cited by 10 publications

References 24 publications

Coronary Stent Artifact Reduction with an Edge-Enhancing Reconstruction Kernel – A Prospective Cross-Sectional Study with 256-Slice CT

Coronary Stent Artifact Reduction with an Edge-Enhancing Reconstruction Kernel – A Prospective Cross-Sectional Study with 256-Slice CT

Coronary Stent Artifact Reduction With an Edge-Enhancing Reconstruction Kernel - A Prospective Cross-Sectional Study With 256-Slice Ct

A noise-optimized virtual monochromatic reconstruction algorithm improves stent visualization and diagnostic accuracy for detection of in-stent re-stenosis in lower extremity run-off CT angiography

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