title: Assessment of hepatic steatosis: comparison of quantitative and semiquantitative methods in 108 liver biopsies.
abstract: BACKGROUND
  There is growing interest in the role of hepatic steatosis in liver injury. The current standard for steatosis assessment is histological grading, although there is variability in the scoring systems used.
  
  
  OBJECTIVE
  The aim of this study was to compare steatosis assessment by image analysis and histological grading.
  
  
  METHODS
  Three methods were used to measure steatosis: histological grading (from 0 to 4); estimation of the percentage of hepatocytes (to nearest 5%) with steatosis; and computer-assisted image analysis. Image analysis was performed on multiple fields for each biopsy with image pro plus 4.5, with steatotic droplets identified on the basis of shape, colour and size. Computer-selected objects were reviewed to ensure that these were steatotic droplets. The predictive accuracy of the three techniques was assessed using measures of obesity and insulin resistance (homeostasis model assessment) as the outcome variables.
  
  
  RESULTS
  There was a strong correlation between the results of image analysis and histological grade (r(s)=0.89, P<0.01), and estimated per cent steatosis (r(s)=0.93, P<0.01). The variability in the area of steatosis calculated by image analysis in different fields of a biopsy correlated with the total steatosis area (r(s)=0.93, P<0.01).
  
  
  CONCLUSIONS
  Image analysis did not offer any additional predictive value when the association between degree of obesity or insulin resistance was correlated with the different methods of assessing steatosis. Image analysis allows measurement of area of steatosis in liver biopsy material and generates a continuous variable that facilitates statistical analysis. These aspects may prove beneficial in research settings.
authors.affiliation: Départment of Pathology and INSERM U522, Centre Hospitalier Universitaire, Rennes Cedex, France.
authors.forename: Bruno
authors.initials: B
authors.lastname: Turlin
authors.forename: Grant A
authors.initials: GA
authors.lastname: Ramm
authors.forename: David M
authors.initials: DM
authors.lastname: Purdie
authors.forename: Fabrice
authors.initials: F
authors.lastname: Lainé
authors.forename: Michelle
authors.initials: M
authors.lastname: Perrin
authors.forename: Yves
authors.initials: Y
authors.lastname: Deugnier
authors.forename: Graeme A
authors.initials: GA
authors.lastname: Macdonald
mesh_terms: D000328:Adult; D000368:Aged; D001706:Biopsy; D005234:Fatty Liver / Q000473:pathology*; D005260:Female; D022781:Hepatocytes / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008099:Liver / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D015203:Reproducibility of Results