title: Improvement of low-contrast detectability in low-dose hepatic multidetector computed tomography using a novel adaptive filter: evaluation with a computer-simulated liver including tumors.
abstract: OBJECTIVE
  The purpose of this study was to investigate how much radiation dose can be reduced without loss of low-contrast detectability with a newly developed adaptive noise reduction filter in hepatic multidetector computed tomography (MDCT) scans by using a computer-simulated liver phantom.
  
  
  METHODS
  Simulated CT images, including liver and intrahepatic tumors, were mathematically constructed using a computer workstation to evaluate low-contrast detectability by the observer performance test. Milliampere second for construction of simulated images were 60, 80, 100, and 120 mAs (low dose) and 160 mAs (standard dose) at 120 kVp. Images with 60, 80, 100, and 120 mAs were postprocessed with the adaptive noise reduction filter. A total of 432 images were prepared and receiver operating characteristic (ROC) analysis was performed by 5 radiologists. The detectability of simulated tumor by radiologists was estimated with the area under the ROC curves (Az values). In addition, we visually evaluated CT images of 15 patients with chronic liver damage for graininess of the liver parenchyma, sharpness of the liver contour, conspicuity and marginal sharpness of the liver tumors, and overall image quality.
  
  
  RESULTS
  The mean Az value at 0.777 (60 mAs), 0.828 (80 mAs), and 0.844 (100 mAs) without filter was significantly lower than that of 160 mAs without filter (P < 0.001, 60 mAs; P = 0.010, 80 mAs; P = 0.040, 100 mAs). There was no statistical difference between the mean Az value at 80 mAs with and 160 mAs without the adaptive noise reduction filter (P = 0.220) and 100 mAs with and 160 mAs without the adaptive noise reduction filter (P = 0.979). In the visual evaluation of patient livers, there was no statistical difference in the graininess and sharpness of the liver, the conspicuity and marginal sharpness of the tumor, and the overall image quality between standard-dose and filtered low-dose images (Wilcoxon signed rank test, P > 0.05).
  
  
  CONCLUSIONS
  The radiation dose can be reduced by 50% without loss of nodule detectability by applying the adaptive noise reduction filter to simulated and patient liver images obtained at MDCT.
authors.affiliation: Department of Medical Information Systems, School of Health Sciences, Kumamoto University, Japan. yfunama@hs.kumamoto-u.ac.jp
authors.forename: Yoshinori
authors.initials: Y
authors.lastname: Funama
authors.forename: Kazuo
authors.initials: K
authors.lastname: Awai
authors.forename: Osamu
authors.initials: O
authors.lastname: Miyazaki
authors.forename: Yoshiharu
authors.initials: Y
authors.lastname: Nakayama
authors.forename: Taiga
authors.initials: T
authors.lastname: Goto
authors.forename: Yasuo
authors.initials: Y
authors.lastname: Omi
authors.forename: Toshiaki
authors.initials: T
authors.lastname: Shimonobo
authors.forename: Duo
authors.initials: D
authors.lastname: Liu
authors.forename: Yasuyuki
authors.initials: Y
authors.lastname: Yamashita
authors.forename: Shinichi
authors.initials: S
authors.lastname: Hori
mesh_terms: D000368:Aged; D000704:Analysis of Variance; D006528:Carcinoma, Hepatocellular / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008113:Liver Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D019047:Phantoms, Imaging; D012372:ROC Curve; D011829:Radiation Dosage; D011857:Radiographic Image Interpretation, Computer-Assisted; D018709:Statistics, Nonparametric; D014057:Tomography, X-Ray Computed / Q000379:methods*