A cylindrical phantom made from acrylic and artificial hip joint were used in this study (Fig. 1). The diameter and length of the phantom were 216 mm and 186 mm. The artificial hip joint consisted of the alloclassic stem (titanium), the durasul head (alumina ceramic) and the IOI bipolar cup (polyethylene). The artificial hip joint was fixed at the center of the phantom filled with water.
Ct Image Acquisition
The CT images were performed using a 80-detector row CT scanner (Aquilion PRIME SP; Canon Medical Systems, Otawara, Japan) in this study. the CT acquisition parameters were as follows: acquisition mode, helical; gantry rotation time, 0.5 s/rotation; C-FOVs, 320 and 500 mm; tube voltage, 120 kV; tube current, 75 mAs with C-FOV size of 320 mm and 90 mAs with C-FOV size of 500 mm (tube currents of two C-FOV sizes were set to standard deviation (SD) value of 10 for the water CT value of the phantom without artificial hip joint); number of scans, 10. Reconstruction conditions were slice thickness of 5.0 mm, display-FOV of 250 mm, and FC03 kernel (i.e. soft-tissue kernel). CT images were reconstructed with FBP, adaptive iterative dose reduction three dimensional (AIDR3D, Canon Medical Systems, Otawara, Japan), and AiCE, with and without SEMAR, respectively.
Quantitative image analysis was calculated using the free software package ImageJ (NIH) . Rectangle regions of interest (ROIs) were placed around the artificial hip joint and in a metal implant-free slice to measure the standard deviation (SD) of the CT value in these ROIs (Fig. 2). The relative artifact index (AIr) was calculated using the measured SDs by the following formula:
SD A and SDB indicate the SD values around the artificial hip joint and the background SD values, respectively .
Takada et al.  indicated that AIr, which divided artifact index (AI) of Eq. (2) by the SD value of the background, can evaluate quantitative artifact amount independent of image noise.
AI is defined not by the ratio of SDs in the metal artifact image and the background image, but by the difference between those of SDs [7–10, 13]. Therefore, CT images with high image noise increase the difference between the SDs of the metal artifact image and the SDs of the background image. In other words, it may not be possible to determine whether fluctuations in the AI values are affected by metal artifacts or image noise. In this study, which evaluated metal artifacts by changing the reconstruction methods and C-FOVs size, the image noise of the CT images in this analysis depends on the reconstruction methods and C-FOVs size. Therefore, the AIr was used to evaluate the degree of metal artifacts in this study.
Subjective Image Analysis
Seven radiology technologists (13 ± 5.8 years of experience, two of them were qualified as Japanese certifying organization of X-ray CT technologists for radiological technologists) were included in the subjective image analysis. All images were presented on a monochrome liquid crystal display monitor with scan data and reconstruction algorithms blinded for independent assessment of images. Total degree of artifacts was evaluated using a five-point scale (1 = no artifacts, 2 = mild artifacts, 3 = moderate artifacts, 4 = strong artifacts and 5 = extensive artifacts) .
Calculated values are presented as mean ± SD. Wilcoxon signed-ranks test was used to compare the C-FOVs between M and L and the reconstruction methods between FBP, AIDR3D, and AiCE. All statistical analysis was performed using the software package easy R (EZR) . A p value of < 0.05 was statistically considered significant.