Improved coronary in-stent visualization using a combined high-resolution kernel and a hybrid iterative...

To investigate the diagnostic performance of 256-slice cardiac CT for the evaluation of the in-stent lumen by using a hybrid iterative reconstruction (HIR) algorithm combined with a high-resolution kernel.

This study included 28 patients with 28 stents who underwent cardiac CT. Three different reconstruction images were obtained with: (1) a standard filtered back projection (FBP) algorithm with a standard cardiac kernel (CB), (2) an FBP algorithm with a high-resolution cardiac kernel (CD), and (3) an HIR algorithm with the CD kernel. We measured image noise and kurtosis and used receiver operating characteristics analysis to evaluate observer performance in the detection of in-stent stenosis.

Image noise with FBP plus the CD kernel (80.2 ± 15.5 HU) was significantly higher than with FBP plus the CB kernel (28.8 ± 4.6 HU) and HIR plus the CD kernel (36.1 ± 6.4 HU). There was no significant difference in the image noise between FBP plus the CB kernel and HIR plus the CD kernel. Kurtosis was significantly better with the CD- than the CB kernel. The kurtosis values obtained with the CD kernel were not significantly different between the FBP- and HIR reconstruction algorithms. The areas under the receiver operating characteristics curves with HIR plus the CD kernel were significantly higher than with FBP plus the CB- or the CD kernel. The difference between FBP plus the CB- or the CD kernel was not significant. The average sensitivity, specificity, and positive and negative predictive value for the detection of in-stent stenosis were 83.3, 50.0, 33.3, and 91.6% for FBP plus the CB kernel, 100, 29.6, 40.0, and 100% for FBP plus the CD kernel, and 100, 54.5, 40.0, and 100% for HIR plus the CD kernel.

The HIR algorithm combined with the high-resolution kernel significantly improved diagnostic performance in the detection of in-stent stenosis.