Assessment of hepatic fatty infiltration using spectral computed tomography imaging: A pilot study

Xiangpeng Zheng, Yanping Ren, William T. Phillips, Ming Li, Meifang Song, Yanqing Hua, Guozhen Zhang

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


OBJECTIVE: The objective of this study was to investigate the feasibility of using monochromatic spectral computed tomography (CT) imaging to assess fatty infiltration in liver. MATERIALS: With spectral CT imaging, phantoms with known fat concentrations were studied for scanning parameter optimization, then 52 patients enrolled into 4 groups (healthy, mild, moderate, and severe fatty infiltration) received abdominal scanning. Based on reconstructed monochromatic images, hepatic attenuation was analyzed, and dual-energy subtraction imaging (DESI) was created for quantifying fat infiltration. RESULTS: Corresponding to various hepatic fat infiltrations, 4 characteristic CT attenuation curve patterns were described. In DESI images, only fat and fatty components appeared bright. For livers without abnormal fat deposition, isolated bright pixels were visualized (% area = 0.5% ± 0.3%). With hepatic fat accumulation increasing, more bright pixels appeared in subtraction images with percentages of total liver area involved in 2.5%, 6.7%, and 13.4% of mild, moderate, and severe fat infiltration cases, respectively (P < 0.05). The corresponding CT values were as follows: 1.33, 2.53, 8.69, and 16.4 Hounsfield units (P < 0.01), which correlated with the % DESI area values (r = 0.9811). CONCLUSIONS: Spectral CT imaging is a promising method to quantitatively assess hepatic fat content and fatty infiltration with advantages compared with conventional CT imaging.

Original languageEnglish (US)
Pages (from-to)134-141
Number of pages8
JournalJournal of Computer Assisted Tomography
Issue number2
StatePublished - Mar 1 2013


  • Computed tomography
  • Dual-energy CT
  • Hepatic steatosis
  • Spectral imaging
  • Subtraction imaging

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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