Knowledge-based iterative reconstructions for imaging of coronary artery stents: first in-vitro experience and comparison of different radiation dose levels and kernel settings

Abstract

Background Advanced knowledge-based iterative model reconstructions (IMR) became recently available for routine computed tomography (CT). Using more realistic physical models it promises improved image quality and potential radiation dose reductions, both possibly beneficial for non-invasive assessment of coronary stents. Purpose To evaluate the influence of different IMR settings at different radiation doses on stent lumen visualization in comparison to filtered back projection (FBP) and first-generation (hybrid) iterative reconstruction (HIR). Material and Methods Ten coronary stents in a coronary phantom were examined at four different dose settings (120 kV/125 mAs, 120 kV/75 mAs, 100 kV/125 mAs, 100 kV/75 mAs). Images were reconstructed with stent-specific FBP and HIR kernels and with IMR using CardiacRoutine (CR) and CardiacSharp (CS) settings at three different iteration levels. Image quality was evaluated using established parameters: image noise; in-stent attenuation difference; and visible lumen diameter. Results Image noise was significantly lower in IMR than in corresponding HIR and FBP images. At lower radiation doses, image noise increased significantly except with IMR CR3 and IMR CS3. Visible lumen diameters were significantly larger with IMR CS than with FBP, HIR, and IMR CR. IMR CR showed the smallest attenuation difference, while attenuation was artificially decreased extensively with IMR CS. FBP and HIR showed moderately increased in-stent attenuations. No relevant influence of used radiation doses on visible lumen diameters or attenuation differences was found. Conclusion IMR CR reduces image noise significantly while offering comparable stent-specific image quality in comparison to FBP and HIR and therefore potentially facilitates stent lumen delineation. Utilization of IMR CS for stent evaluation seems unfavorable due to artificial image alterations.