Objective
To assess the effects of iterative model reconstruction (IMR) on image quality for demonstrating non-calcific high-risk plaque characteristics of coronary arteries.
Materials and Methods
This study included 66 patients (53 men and 13 women; aged 39–76 years; mean age, 55 ± 13 years) having single-vessel disease with predominantly non-calcified plaques evaluated using prospective electrocardiogram-gated 256-slice CT angiography. Paired image sets were created using two types of reconstruction: hybrid iterative reconstruction (HIR) and IMR. Plaque characteristics were compared using the two algorithms. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the images and the CNR between the plaque and adjacent adipose tissue were also compared between the two reformatted methods.
Results
Seventy-seven predominantly non-calcified plaques were detected. Forty plaques showed napkin-ring sign with the IMR reformatted method, while nineteen plaques demonstrated napkin-ring sign with HIR. There was no statistically significant difference in the presentation of positive remodeling, low attenuation plaque, and spotty calcification between the HIR and IMR reconstructed methods (all
p
> 0.5); however, there was a statistically significant difference in the ability to discern the napkin-ring sign between the two algorithms (χ
2
= 12.12,
p
< 0.001). The image noise of IMR was lower than that of HIR (10 ± 2 HU versus 12 ± 2 HU;
p
< 0.01), and the SNR and CNR of the images and the CNR between plaques and surrounding adipose tissues on IMR were better than those on HIR (
p
< 0.01).
Conclusion
IMR can significantly improve image quality compared with HIR for the demonstration of coronary artery and atherosclerotic plaques using a 256-slice CT.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.