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

Abstract

Purpose: Metallic 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.

Methods: This 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.

Results: Stent 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).

Conclusion: In 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.

Fig 1. Method of quantitative stent wall thickness measurement.

Coronary stent reformation in short axis perpendicular to centerline. Upper row (A–E), images after reconstruction with a medium-smooth kernel (XCB, Philips Healthcare, Cleveland, OH, USA); lower row, (F–J), images after reconstruction with an edge-enhancing kernel (XCD, Philips Healthcare, Cleveland, OH, USA). Internal (B, G) and external (C, H) stent areas measured using a semi-automatic segmentation software, with manual correction when needed (circumference thickness method). Internal (D, I) and external (E, J) stent diameters measured using manual placement of an electronic caliper for distance measurements (orthogonal thickness method).

Fig 2. Stent wall thickness overestimation with smooth and sharp kernels.

Box plots: Stent wall thickness overestimation using the XCD kernel was significantly less than with the XCB kernel (p < 0.005). In this figure, merged data is used for both diameter and circumference methods, as well as for both observers no 1 and 2.

Fig 3. Qualitative stent image quality with smooth and sharp kernels.

Average scores of visual assessment of image quality in 71 stented coronary artery segments. Distribution of average scores of visual assessment of image quality in 71 stented segments, as evaluated with 256-slice MDCT and prospective ECG-gating, after image reconstruction with medium-smooth (XCB) and edge-enhancing (XCD) reconstruction kernels. In this figure, each score is the average of the visual score of the two independent observers 1 and 2 for a given stent.

Fig 4. Reduced stent blooming artifacts and improved strut definition with sharp (XCD) in comparison to smooth (XCB) kernel.

77-year-old female, right proximal coronary artery patent bare-metal stent (Abbott Vision, length 15 mm, diameter 4 mm, nominal thickness 0.08 mm). 256-slice CT acquisition with prospective ECG-gating, and image reconstuction with a medium-soft (XCB, left) and edge-enhancing (XCD, right) reconstruction kernels, multiplanar reformat. Window width, 1500 HU; window centre: 300 HU, for both kernels. For observer 1, stent wall thickness for the XCB and XCD kernels with the orthogonal thickness method was 1.44 mm and 1.24 mm, and 1.66 mm and 1.58 mm with the circumference method, respectively. Image quality scores for observer 1 were 3 and 4, respectively. For observer 2, stent wall thickness for the XCB and XCD kernels with the orthogonal thickness method was 0.89 mm and 1.15 mm, and 1.20 mm and 0.93 mm with the circumference method, respectively. Image quality scores for observer 2 were 3 and 4, respectively.

Fig 5. Reduced stent blooming artifacts and improved strut definition with sharp (XCD) in comparison to smooth (XCB) kernel.

69-year-old female, first obtuse marginal artery stent. 256-slice CT acquisition with prospective ECG-gating, and image reconstuction with a medium-soft (XCB, left) and edge-enhancing (XCD, right) reconstruction kernels, multiplanar reformat. Window width, 1500 HU; window centre: 300 HU, for both kernels. For observer 1, stent wall thickness for the XCB and XCD kernels with the orthogonal thickness method was 1.29 mm and 1.05 mm, and 1.26 mm and 1.26 mm with the circumference method, respectively. Image quality scores for observer 1 were 3 and 4, respectively. For observer 2, stent wall thickness for the XCB and XCD kernels with the orthogonal thickness method was 0.97 mm and 0.71 mm, and 0.82 mm and 0.83 mm with the circumference method, respectively. Image quality scores for observer 2 were 2 and 3, respectively.