Clinical impact of model-based type iterative reconstruction with fast reconstruction time on image quality of low-dose screening chest CT

Background: Model-based type iterative reconstruction algorithms with fast reconstruction times are now available. The clinical feasibility of their reconstruction has not been evaluated adequately.

Purpose: To investigate the effects of model-based type iterative reconstruction, i.e. iterative model reconstruction (IMR), with fast reconstruction time on the qualitative and quantitative image quality at low-dose chest computed tomography (CT).

Material and methods: Thirty-one patients undergoing low-dose screening chest CT were enrolled. Images were reconstructed using filtered back projection (FBP), hybrid iterative reconstruction (HIR), and IMR algorithms. The CT attenuation and image noise for all reconstructions were calculated at the lung apex, middle, and base. Using a 4-point scale, two reviewers visually evaluated the image quality with respect to vessel sharpness, streak artifact, the mediastinum, and the overall image quality of each reconstruction method.

Results: The mean estimated effective dose was 1.0 ± 0.3 mSv. There was no significant difference in the CT attenuation among the three reconstructions. The mean image noise of FBP, HIR, and IMR images was 124.3 ± 57.3, 34.8 ± 10.2, and 22.9 ± 5.8 HU, respectively. There were significant differences for all comparison combinations among the three methods (P < 0.01). The best subjective overall image quality for the lung and mediastinum was obtained with IMR (P < 0.01). The reconstruction time for IMR was within 3 min in all cases.

Conclusion: At low-dose chest CT, IMR can improve the qualitative and quantitative visualization of both lung and mediastinal structures especially in the lung apex at a clinically acceptable reconstruction time. Its application may improve diagnostic performance.