Objective: The objective of this study was to compare image quality for abdominal computed tomographic (CT) images acquired at 200 and 50 mA s and reconstructed with image-based iterative reconstruction.
Materials and Methods: In this institutional review board–approved prospective study, 22 patients (mean [SD] age, 64.3 [14.4] years; male-female ratio, 12:10) gave informed consent for acquisition of additional abdominal CT images on 64-slice multi-detector CT (MDCT) (Siemens Definition Flash). Standard-dose images were acquired at 200 quality reference mA s, whereas low-dose images were acquired at 50 mA s (all series: 120 kV; 5-mm section thickness; pitch, 0.9:1). The low-dose images were reconstructed with a nonlinear 3-dimensional iterative image reconstruction (3D-IIR) (SafeCT; MedicVision, Tirat Carmel, Israel) (4 settings, namely, A1, A2, A3, and A4) and were assessed by 3 abdominal radiologists for lesion detection, image noise, and visibility of small structures. CATPHAN 500 was scanned at the respective doses to obtain noise spectral density and modulation transfer function.
Results: Subjective image noise was unacceptable at 50-mA s filtered back projection and improved to average in 50-mA s A1 and minimal or no noise in 50-mA s A4. However, the visibility of small structures was similar to standard-dose filtered back projection images on 50-mA s A2. Objective image noise was reduced to 66% for the 50-mA s 3D-IIR images (9.08 [2.3]/26.75 [6.8]). The modulation transfer function curve demonstrated resolution improvement in the low-dose images with the 3D-IIR technique, whereas the noise spectral density curve confirmed noise suppression in the 50-mA s 3D-IIR images.
Conclusions: Three-dimensional iterative image reconstruction helps to lower image noise without affecting the visibility of small structures at “moderate” settings. Diagnostically acceptable abdominal CT examinations can be acquired at 75% lower-radiation dose with the help of the image-based iterative reconstruction technique.
From the *Department of Radiology, Massachusetts General Hospital, Boston, MA; and †Center for Medical Image Science and Visualization, Linköpings universitet/US, Linköping, Sweden.
Received for publication April 25, 2013; accepted June 19, 2013.
Reprints: Sarvenaz Pourjabbar, MD, Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114 (e-mail: firstname.lastname@example.org).
None of the coauthors have any pertinent financial disclosures.