ArticleMagma (New York, N.Y.)2023
Numerical approach to investigate MR imaging artifacts from orthopedic implants at different field strengths according to ASTM F2119.
Article in Magma (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Open-Source Simulator of Imaging Near Metal at Arbitrary Magnetic Field Strengths.Magnetic resonance in medicine · 2026Article
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Authors and funding
4 authors.
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Abstract
objectiveThis study presents an extended evaluation of a numerical approach to simulate artifacts of metallic implants in an MR environment.
methodsThe numerical approach is validated by comparing the artifact shape of the simulations and measurements of two metallic orthopedic implants at three different field strengths (1.5 T, 3 T, and 7 T). Furthermore, this study presents three additional use cases of the numerical simulation. The first one shows how numerical simulations can improve the artifact size evaluation according to ASTM F2119. The second use case quantifies the influence of different imaging parameters (TE and bandwidth) on the artifact size. Finally, the third use case shows the potential of performing human model artifact simulations.
resultsThe numerical simulation approach shows a dice similarity coefficient of 0.74 between simulated and measured artifact sizes of metallic implants. The alternative artifact size calculation method presented in this study shows that the artifact size of the ASTM-based method is up to 50% smaller for complex shaped implants compared to the numerical-based approach.
conclusionIn conclusion, the numerical approach could be used in the future to extend MR safety testing according to a revision of the ASTM F2119 standard and for design optimization during the development process of implants.
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