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 P Conclusions The IMR can provide improved image quality at super-low-dose cardiac CT with 20% of the standard tube current.