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.
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.
Entities:
Keywords:
dual-energy CT; iMAR; metal artifact; spine; virtual monochromatic imaging
Authors: Anushri Parakh; Chansik An; Simon Lennartz; Prabhakar Rajiah; Benjamin M Yeh; Frank J Simeone; Dushyant V Sahani; Avinash R Kambadakone Journal: Radiographics Date: 2021-02-19 Impact factor: 5.333
Authors: Jacob L Goldberg; Ross M Meaden; Ibrahim Hussain; Pravesh S Gadjradj; Danyal Quraishi; Fabian Sommer; Joseph A Carnevale; Branden Medary; Drew Wright; K Daniel Riew; Roger Hartl Journal: Brain Spine Date: 2022-08-22