Quantifying near metal visibility using dual energy computed tomography and iterative metal artifact reduction in a fracture phantom

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Abstract

Purpose: To quantitatively assess CT image quality and fracture visibility using virtual monochromatic imaging and iterative metal artifact reduction (iMAR) in a femoral bone fracture phantom with different fixation implants. Methods: A custom made phantom was scanned at 120-kVp and 140-kVp single-energy and 100/150-kVp dual-energy. Three stainless steel and two titanium implants with different thicknesses were placed on the phantom containing simulated one and two mm fractures. Single-energy CT images were reconstructed with and without iMAR, while DECT images were reconstructed at monochromatic energies between 70 and 190 keV. Non-metal scans were used as a reference. A Fourier power spectrum method and fracture model were used to analyze several anatomical areas. Results: CT-value deviations of titanium implants were much lower compared to stainless steel implants. These deviations decreased for both DECT and iMAR. Fracture visibility, measured with the fracture model, improved the most when DECT was used while artifact reduction benefitted more from iMAR. The optimal monochromatic energy for metal artifact reduction, based on CT-value deviation, varied for each metal between 130 and 150 keV. The fracture model provided a signal-to-noise ratio for the near metal fracture visibility, providing the optimal keV. Conclusion: iMAR and high keV monochromatic images extracted from DECT both reduce metal artifacts caused by different metal fixation implants. Quantitative femoral phantom results show that DECT is superior to iMAR regarding fracture visualization adjacent to metal fixation implants. The introduction of new artifacts when using iMAR impedes its value in near metal fixation implant imaging.
Original languageEnglish
Pages (from-to)9-18
Number of pages10
JournalPhysica medica
Volume69
DOIs
Publication statusPublished - 1 Jan 2020

Keywords

  • Dual-energy CT
  • Femur phantom
  • Fracture modeling
  • Metal artifact reduction
  • iMAR

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