title: MR quantification of hepatic iron concentration.
abstract: OBJECTIVE
  To evaluate the accuracy of magnetic resonance (MR) imaging in the quantification of hepatic iron concentration.
  
  
  METHODS
  Between April 1999 and June 2001, 112 patients were recruited prospectively. All had undergone liver biopsy and hepatic iron concentration quantification with spectrophotometry, followed by MR imaging. MR imaging involved use of four gradient-echo sequences and one spin-echo sequence. Signal intensity (SI) was measured on images obtained with each sequence by means of regions of interest placed in the liver and paraspinal muscle to obtain the liver-to-muscle SI ratio. The relationship between hepatic iron concentration and SI ratio for each sequence was analyzed with multiple linear regression. Receiver operating characteristic analysis was performed to find the diagnostic thresholds.
  
  
  RESULTS
  Sixty-eight patients had normal hepatic iron levels (<36 micromol/g), 23 had hemosiderosis (36-80 micromol/g), and 21 had hemochromatosis (>80 micromol/g). With all sequences, an inverse linear relationship between iron concentration and SI ratio was apparent. The authors generated a mathematic model to estimate the iron concentrations from MR imaging data (r = 0.937). For estimated concentrations of more than 85 micromol/g, the positive predictive value for hemochromatosis was 100%; for those less than 40 micromol/g, the negative predictive value for hemochromatosis was 100%. For estimated concentrations of more than 58 micromol/g, the positive predictive value for iron overload was 100%; for those less than 20 micromol/g, the negative predictive value for iron overload was 100%.
  
  
  CONCLUSIONS
  MR imaging is a useful and noninvasive diagnostic tool for quantification of hepatic iron concentration.
authors.affiliation: OSATEK, Alta Tecnología Sanitaria S.A., Paseo Dr Beguiristain 109, 20014 San Sebastián, Basque Country, Spain. rm.donostia@osatek.es
authors.forename: José M
authors.initials: JM
authors.lastname: Alústiza
authors.forename: José
authors.initials: J
authors.lastname: Artetxe
authors.forename: Agustín
authors.initials: A
authors.lastname: Castiella
authors.forename: Cristina
authors.initials: C
authors.lastname: Agirre
authors.forename: José I
authors.initials: JI
authors.lastname: Emparanza
authors.forename: Pedro
authors.initials: P
authors.lastname: Otazua
authors.forename: Manuel
authors.initials: M
authors.lastname: García-Bengoechea
authors.forename: Jesús
authors.initials: J
authors.lastname: Barrio
authors.forename: Fernando
authors.initials: F
authors.lastname: Mújica
authors.forename: José A
authors.initials: JA
authors.lastname: Recondo
mesh_terms: D000328:Adult; D000368:Aged; D001706:Biopsy; D005260:Female; D006432:Hemochromatosis / Q000097:blood / Q000175:diagnosis*; D006486:Hemosiderosis / Q000097:blood / Q000175:diagnosis*; D006801:Humans; D007089:Image Enhancement; D007090:Image Interpretation, Computer-Assisted; D007501:Iron / Q000097:blood*; D008099:Liver / Q000378:metabolism* / Q000473:pathology; D008111:Liver Function Tests; D008279:Magnetic Resonance Imaging; D008297:Male; D008432:Mathematical Computing; D008875:Middle Aged; D018482:Muscle, Skeletal / Q000378:metabolism / Q000473:pathology; D012372:ROC Curve; D012016:Reference Values; D012044:Regression Analysis; D012680:Sensitivity and Specificity
chemical_list: D007501:Iron