title: Liver in the analysis of body composition by dual-energy X-ray absorptiometry.
abstract: OBJECTIVE
  To investigate the predictive value for hepatic steatosis of a new software for the quantification of visceral fat by dual-energy X-ray absorptiometry (DXA) and to design new regions of interest (ROIs).
  
  
  METHODS
  Adult volunteers were prospectively screened for hepatic steatosis by ultrasonography to obtain a well-balanced population according to the presence/absence of the disease. 90 adult patients without steatosis and 90 with steatosis (mild, 53.3%; moderate, 37.7%; and severe, 10.0%) were recruited. On the same day, all subjects were submitted to blood testing and to anthropometric and whole-body DXA for body composition evaluation. A new software for android visceral fat assessment was employed, and six new "liver-suited" ROIs as well as two modified android ROIs were designed. Their association with steatosis grade was tested by correlation analysis.
  
  
  RESULTS
  Fat mass (FM) of the new ROIs showed the highest correlation coefficients with steatosis grade (ρ = 0.610-0.619; p < 0.001), which was also confirmed by multivariate analysis. On the whole population, the new ROIs maintained the highest predictive role for liver steatosis, with areas under the receiver operating characteristic curve up to 0.820 ± 0.032. Inter- and intra-operator agreement for the new ROIs was excellent (k = 0.915-1.000 and k = 0.927-1.000).
  
  
  CONCLUSIONS
  New ROIs could be designed, standardized and implemented in DXA whole-body scan to provide more specific and predictive values of hepatic lipid content.
  
  
  CONCLUSIONS
  This is the first study to investigate the predictive value for hepatic steatosis of visceral and regional FM assessed on the hepatic site by DXA in comparison with ultrasonography, anthropometry and surrogate markers derived by previously validated algorithms (fatty liver index).
authors.affiliation: Department of Specialized, Diagnostic, and Experimental Medicine, University of Bologna, Sant'Orsola Malpighi Hospital, Bologna, Italy.
authors.forename: A
authors.initials: A
authors.lastname: Bazzocchi
authors.forename: D
authors.initials: D
authors.lastname: Diano
authors.forename: U
authors.initials: U
authors.lastname: Albisinni
authors.forename: G
authors.initials: G
authors.lastname: Marchesini
authors.forename: G
authors.initials: G
authors.lastname: Battista
authors.forename: G
authors.initials: G
authors.lastname: Guglielmi
mesh_terms: D015502:Absorptiometry, Photon / Q000592:standards; D000328:Adult; D000368:Aged; D000465:Algorithms; D000886:Anthropometry; D001823:Body Composition; D003430:Cross-Sectional Studies; D005234:Fatty Liver / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D050152:Intra-Abdominal Fat / Q000000981:diagnostic imaging; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012984:Software; D055815:Young Adult