X-Ray Dose Reduction in Abdominal Computed Tomography Using Advanced Iterative Reconstruction Algorithms

Objective: This work aims to explore the effects of adaptive statistical iterative reconstruction (ASiR) and model-based iterative reconstruction (MBIR) algorithms in reducing computed tomography (CT) radiation dosages in abdominal imaging. Methods: CT scans on a standard male phantom were performed at different tube currents. Images at the different tube currents were reconstructed with the filtered back-projection (FBP), 50 % ASiR and MBIR algorithms and compared. The CT value, image noise and contrast-to-noise ratios (CNRs) of the reconstructed abdominal images were measured. Volumetric CT dose indexes (CTDIvol) were recorded. Results: At different tube currents, 50 % ASiR and MBIR significantly reduced image noise and increased the CNR when compared with FBP. The minimal tube current values required by FBP, 50 % ASiR, and MBIR to achieve acceptable image quality using this phantom were 200, 140, and 80 mA, respectively. At the identical image quality, 50 % ASiR and MBIR reduced the radiation dose by 35.9 % and 59.9 % respectively when compared with FBP. Conclusions: Advanced iterative reconstruction techniques are able to reduce image noise and increase image CNRs. Compared with FBP, 50 % ASiR and MBIR reduced radiation doses by 35.9 % and 59.9%, respectively