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Single-energy versus dual-energy imaging during CT-guided biopsy using dedicated metal artifact reduction algorithm in an in vivo pig model

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Listed:
  • Thuy Duong Do
  • Julia Heim
  • Stephan Skornitzke
  • Claudius Melzig
  • Dominik F Vollherbst
  • Michael Faerber
  • Philippe L Pereira
  • Hans-Ulrich Kauczor
  • Christof Matthias Sommer

Abstract

Purpose: To evaluate dual-energy CT (DE) and dedicated metal artifact reduction algorithms (iMAR) during CT-guided biopsy in comparison to single-energy CT (SE). Methods: A trocar was placed in the liver of six pigs. CT acquisitions were performed with SE and dose equivalent DE at four dose levels(1.7–13.5mGy). Iterative reconstructions were performed with and without iMAR. ROIs were placed in four positions e.g. at the trocar tip(TROCAR) and liver parenchyma adjacent to the trocar tip(LIVER-1) by two independent observers for quantitative analysis using CT numbers, noise, SNR and CNR. Qualitative image analysis was performed regarding overall image quality and artifacts generated by iMAR. Results: There were no significant differences in CT numbers between DE and SE at TROCAR and LIVER-1 irrespective of iMAR. iMAR significantly reduced metal artifacts at LIVER-1 for all exposure settings for DE and SE(p = 0.02-0.04), but not at TROCAR. SNR, CNR and noise were comparable for DE and SE. SNR was best for high dose levels of 6.7/13.5mGy. Mean difference in the Blant-Altman analysis was -8.43 to 0.36. Cohen’s kappa for qualitative interreader-agreement was 0.901. Conclusions: iMAR independently reduced metal artifacts more effectively and efficiently than CT acquisition in DE at any dose setting and its application is feasible during CT-guided liver biopsy.

Suggested Citation

  • Thuy Duong Do & Julia Heim & Stephan Skornitzke & Claudius Melzig & Dominik F Vollherbst & Michael Faerber & Philippe L Pereira & Hans-Ulrich Kauczor & Christof Matthias Sommer, 2021. "Single-energy versus dual-energy imaging during CT-guided biopsy using dedicated metal artifact reduction algorithm in an in vivo pig model," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-14, April.
  • Handle: RePEc:plo:pone00:0249921
    DOI: 10.1371/journal.pone.0249921
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