Clinical evaluation of the normalized metal artefact reduction algorithm caused by dental fillings in CT

The aim of this study was to evaluate the performance of a normalized metal artefact reduction (NMAR) algorithm in patients with high-density dental fillings in CT images, and compare the results with weighted filtered back-projection (WFBP) and linear interpolation metal artefact reduction (MARli) algorithms. A total of 15 patients who had dental fillings were included in this study. The CT raw data sets were processed on an offline workstation. For each data set, one image series was reconstructed with WFBP, one with MARli and one with NMAR. Two observers qualitatively graded the severity of metal artefacts and their impacts on surrounding and distant soft tissue using a five-point scale. Six regions of interest were selected to measure the CT values and the standard deviation (SD) for quantitatively evaluating the effects of artefact reduction. A total of 217 slices with metal artefacts from 15 patients were included in the qualitative analysis. The average score (mean ± SD) with the WFBP and MARli algorithms was 2.24 ± 1.06 and 2.71 ± 0.73, respectively. Image artefacts were significantly reduced using the NMAR algorithm compared with the other two algorithms, with an average score of 1.70 ± 0.83. The mean CT value in the most hypodense streak artefacts around the metal fillings was significantly improved with both MARli and NMAR. The mean SDs of measured CT values from surrounding or distant soft tissues were lower in NMAR images than in WFBP and MARli images. The NMAR algorithm can significantly reduce the artefacts caused by dental fillings, compared with the WFBP and linear interpolation algorithms.