Influence of field of view size and reconstruction methods on single-energy metal artifact reduction: a phantom study

Abstract

The purpose of this study was to evaluate the effect of single-energy metal artifact reduction (SEMAR) for metal artifacts using CT images reconstructed with adaptive iterative dose reduction three dimensional (AIDR3D) and advanced intelligent clear-IQ engine (AiCE) in calibration-eld of view of various sizes. A prosthetic hip joint was arranged at the center of the phantom. The phantom images were scanned by changing calibration-eld of view of 320 mm and 500 mm, and were reconstructed using ltered back-projection (FBP), AIDR3D, and AiCE with and without SEMAR, respectively. The metal artifact reduction with SEMAR was evaluated by calculated the relative artifact index value and visual scores in degree of artifact by seven radiology technologists. Relative artifact index of FBP, AIDR3D, and AiCE with 320 mm/500 mm calibration-eld of views were 10.2/10.0, 16.3/16.4, and 17.8/17.9 without SEMAR, 3.3/3.1, 2.6/2.5, and 2.3/2.0 with SEMAR, respectively. Visual scores were not signi cantly different between 320 mm and 500 mm calibration-eld of views in all reconstruction methods. The effect of metal artifact reduction was not affected by calibration-eld of view sizes in the SEMAR combined with AIDR3D or AiCE.

Enhancing image quality in computed tomography angiography follow-ups after endovascular aneurysm repair: a comparative study of reconstruction techniques

“…Previous studies showed it embraces many outstanding advantages such as enhancing density and spatial resolution, reducing artifacts and noise, and creating extraordinarily high-quality images without increasing radiation dose [ 22 – 24 ]. In a phantom study, AiCE plus SEMAR performed the best in reducing artifacts compared to other algorithms [ 25 ]. Moreover, studies have shown that combining DLR with SEMAR further reduces image noise and artifacts, thus improving image quality, in CT images with metal implants [ 26 , 27 ].…”

Three-dimensional CT imaging in extensor tendons using deep learning reconstruction: optimal reconstruction parameters and the influence of dose

“…Thus, AiCE reconstruction technique has improved image noise and enables a reduction of radiation dose maintaining image quality compared to CT images using conventional iterative reconstruction (IR). It has been reported that AiCE is useful in various regions such as chest, cardiac, abdomen, CT angiography, and orthopedics [8][9][10][11][12][13][14]. However, it is not clear whether extensor tendons CT images reconstructed using AiCE enable a decrease in image noise and a reduction of radiation dose to better identify extensor tendons on 3D images.…”