title: Comparative study of hepatic venography using non-linear-blending images, monochromatic images and low-voltage images of dual-energy CT.
abstract: OBJECTIVE
  To investigate the use of non-linear-blending and monochromatic dual-energy CT (DECT) images to improve the image quality of hepatic venography.
  
  
  METHODS
  82 patients undergoing abdominal DECT in the portal venous phase were enrolled. For each patient, 31 data sets of monochromatic images and 7 data sets of non-linear-blending images were generated. The data sets of the non-linear-blending and monochromatic images with the best contrast-to-noise ratios (CNRs) for hepatic veins were selected and compared with the images obtained at 80 kVp and a simulated 120 kVp. The subjective image quality of the hepatic veins was evaluated using a four-point scale. The image quality of the hepatic veins was analysed using signal-to-noise ratio (SNR) and CNR values.
  
  
  RESULTS
  The optimal CNR between hepatic veins and the liver was obtained with the non-linear-blending images. Compared with the other three groups, there were significant differences in the maximum CNR, the SNR, the subjective ratings and the minimum background noise (p < 0.001). A comparison of the monochromatic and 80-kVp images revealed that the CNR and subjective ratings were both improved (p < 0.001). There was no significant difference in the CNR or subjective ratings between the simulated 120-kVp group and the control group (p = 0.090 and 0.053, respectively).
  
  
  CONCLUSIONS
  The non-linear-blending technique for acquiring DECT provided the best image quality for hepatic venography.
  
  
  CONCLUSIONS
  DECT can enhance the contrast of hepatic veins and the liver, potentially allowing the wider use of low-dose contrast agents for CT examination of the liver.
authors: 1 Department of Radiology, the Fourth Clinical Hospital of Hebei Medical University, Shijiazhuang, China.
authors: Q
authors: Q
authors: Wang
authors: S
authors: S
authors: Gaofeng
authors: F
authors: F
authors: Xueli
authors: W
authors: W
authors: Lijia
authors: W
authors: W
authors: Runze
mesh_terms: D000005:Abdomen; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003287:Contrast Media; D005260:Female; D005471:Fluoroscopy; D006503:Hepatic Veins / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008099:Liver / Q000098:blood supply*; D008297:Male; D008875:Middle Aged; D010690:Phlebography / Q000379:methods; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D011860:Radiography, Abdominal / Q000379:methods; D059629:Signal-To-Noise Ratio; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D003287:Contrast Media