A Knowledge-based Iterative Model Reconstruction Algorithm: Can Super-Low-Dose Cardiac CT Be Applicable in Clinical Settings?

Rationale and Objectives: To investigate whether full iterative reconstruction, a knowledge-based iterative model reconstruction (IMR), enables radiation dose reduction by 80% at cardiac computed tomography (CT). Materials and Methods: A total of 23 patients (15 men, eight women; mean age 64.3 +/- 13.4 years) who underwent retrospectively electrocardiography-gated cardiac CT with-dose modulation were evaluated. We compared full-dose (FD; 730 mAs)images reconstructed with filtered back projection (FBP) technique and the low-dose (LD; 146 mAs) images reconstructed with FBP and IMR techniques. Objective and subjective image quality parameters were compared among the three different CT images. Results: There was no significant difference in the CT attenuation among the three reconstructions. The mean image noise of LD-IMR (18.3 +/- 10.6 Hounsfield units [HU]) was significantly lowest among the three reconstructions.(41.9 +/- 15.3 HU for FD-FBP and 109.9 +/- 42.6 HU for LD-FBP; P <.01). The contrast-to-noise ratio of LD-IMR was better than that of FD-FBP and LD-FBP (P <.01). Visual evaluation score was also highest for LD-IMR. Conclusions: The IMR can provide improved image quality at super-low-dose cardiac CT with 20% of the standard-tube current.