Evidence map›Paper›PMID 31143656›Full record

ArticleQuantitative imaging in medicine and surgery2019

The influence of liver fat deposition on the quantification of the liver-iron fraction using fast-kilovolt-peak switching dual-energy CT imaging and material decomposition technique: an

Tingting Xie, Yongbin Li, Guanyong He, Zhen Zhang, Qiao Shi, Guanxun Cheng

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Article in Quantitative imaging in medicine and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

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10citing papers in PubMed
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3 · Its place in the literature

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10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Harnessing dual-energy CT for glycogen quantification: a phantom analysis.Quantitative imaging in medicine and surgery · 2023
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
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5 · Who and what money

Authors and funding

6 authors.

Tingting XieMedical Imaging Center, Peking University Shenzhen Hospital, Shenzhen 518036, China.
Yongbin LiDepartment of Ultrasound Imaging, Peking University Shenzhen Hospital, Shenzhen 518036, China.
Guanyong HeMedical Imaging Center, Peking University Shenzhen Hospital, Shenzhen 518036, China.
Zhen ZhangMedical Imaging Center, Peking University Shenzhen Hospital, Shenzhen 518036, China.
Qiao ShiMedical Imaging Center, Peking University Shenzhen Hospital, Shenzhen 518036, China.
Guanxun ChengMedical Imaging Center, Peking University Shenzhen Hospital, Shenzhen 518036, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo assess the feasibility of dual-energy spectral computed tomography (DECT) for quantifying the liver iron content (LIC) with material decomposition (MD) technique

methodsLiver-iron mixture samples (model A) and liver-iron-fat mixture samples (model B) were prepare and scanned by a single source DECT using GSI mode with successive tube currents of 200, 320, and 485 mA. A standard algorithm of 1.25 mm was used to reconstruct iron (fat) MD images and iron (water) MD images. The iron concentrations of all samples were measured and analyzed by Spearman's rank correlation and linear regression analysis.

resultsSignificant positive linear correlations were found between virtual iron content (VIC) and LIC in the absence of fat (model A) and in the presence of fat (model B) in the range of LIC 0 to 25 mg/mL. The lines of best fit to model A had slopes around 1.1 and an intercept around (-1.5) mg/mL for iron (water) MD images, and had slopes around 1.1 and an intercept around (-10) mg/mL for iron (fat) MD images. The lines of best fit to the model B had slopes around 1.5 and an intercept around (-15) mg/mL. At the same value of LIC (LIC >0), the VIC values of model A were always higher than those of model B. At the high value of LIC (12.5 mg/mL), the VIC values of model B were similar, but they differed greatly from those of model A.

conclusionsThe fast-kilovolt-peak switching dual-energy CT imaging and MD techniques allow for quantification of iron content. Fat and the post-reconstruction algorithm of iron (fat) MD images, were confounding factors, and led to the underestimation and overestimation of LIC, respectively.

Indexed as

fatironlivermaterial decomposition (MD)Single-source dual-energy CT

Identifiers

PMID31143656
PMCPMC6511718

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