Clinical Assessment of Metal Artifact Reduction Methods in Dual-Energy CT Examinations of Instrumented Spines

OBJECTIVE. The purpose of this study was to evaluate the performance of three metal artifact reduction methods in dual-energy CT (DECT) examinations of instrumented spines. MATERIALS AND METHODS. Twenty patients with instrumented spines who underwent spine DECT were retrospectively identified. All scans were obtained on a dual-source 128-MDCT scanner. In addition to the original DE mixed images, DECT images were reconstructed using an iterative metal artifact reconstruction algorithm (DE iMAR), virtual monochromatic imaging (VMI) algorithm (DE Mono+), and a combination of the two algorithms DE iMAR and DE Mono+, which we refer to here as DE iMAR Mono+. The four image series were anonymized and randomized for a reader study. Four experienced neuroradiologists rated the images in terms of artifact scores of four anatomic regions and overall image quality scores in both bone and soft-tissue display window settings. In addition, a quantitative analysis was performed to assess the performance of the three metal artifact reduction methods. RESULTS. There were statistically significant differences in the artifact scores and overall image quality scores among the four methods (both, p < 0.001). DE iMAR Mono+ showed the best artifact scores and quality scores (all, p < 0.001). The intraclass correlation coefficient for the overall image quality score was 0.779 using the bone display window and 0.892 using the soft-tissue display window (both, p < 0.001). In addition, DE iMAR Mono+ reduced the artifacts by the greatest amount in the quantitative analysis. CONCLUSION. The method that used DE iMAR Mono+ showed the best performance of spine metal artifact reduction using DECT data. These results may be specific to this CT vendor and implant type.