title: Low-Tube Voltage Computed Tomography During Hepatic Arterial Phase: The Effect of Body Habitus on Image Quality.
abstract: OBJECTIVE
  This study aimed to evaluate the impact of body habitus factors on image quality of low-tube voltage computed tomography (CT) during the hepatic arterial phase.
  
  
  METHODS
  Ninety-seven patients (66 men, 31 women; age range, 26-78 years) who underwent clinically indicated liver dynamic CT examination were enrolled in the study. Analysis with 80-kVp CT and intermediate tube current (277-337 mA) was performed in the late hepatic arterial phase using a 320-detector row scanner with adaptive iterative dose reduction 3-dimensional reconstruction. Patient body habitus was measured using body weight (BW), body mass index (BMI), lateral width (LW) of the abdomen, and muscle volume (MV) of the abdominal wall. On hepatic arterial phase, the mean image noise and contrast-to-noise ratio (CNR) for the aorta and liver were assessed. The correlations between body habitus factors and image quality parameters were evaluated.
  
  
  RESULTS
  In all patients, MV showed the strongest correlation with image noise, followed by BW and LW (r = 0.684, 0.570, and 0.555, respectively). The BMI showed the fourth strongest correlation with image noise among all body habitus factors (r = 0.377). With respect to CNR of the aorta, MV and BW showed the strongest inverse correlation (r = -0.590 and -0.600, respectively), followed by LW and BMI (r = -0.557 and -0.423, respectively). Regarding the CNR of the liver, MV showed the strongest inverse correlation (r = -0.279), although the correlation efficiency was weak compared with other correlations.
  
  
  CONCLUSIONS
  Among various body habitus factors, MV showed the strongest association with image noise and CNR in the hepatic arterial phase using 80-kVp CT.
authors.affiliation: From the Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea.
authors.forename: Yang Shin
authors.initials: YS
authors.lastname: Park
authors.forename: Chang Hee
authors.initials: CH
authors.lastname: Lee
authors.forename: Jongmee
authors.initials: J
authors.lastname: Lee
authors.forename: Jae Woong
authors.initials: JW
authors.lastname: Choi
authors.forename: Kyeong Ah
authors.initials: KA
authors.lastname: Kim
authors.forename: Cheol Min
authors.initials: CM
authors.lastname: Park
mesh_terms: D000328:Adult; D000368:Aged; D001837:Body Weights and Measures / Q000379:methods* / Q000706:statistics & numerical data; D005260:Female; D006499:Hepatic Artery / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000098:blood supply / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed / Q000379:methods*