title: Quantification of hepatic macrosteatosis in living, related liver donors using T1-independent, T2*-corrected chemical shift MRI.
abstract: OBJECTIVE
  To evaluate the diagnostic implications of the iterative decomposition of water and fat using echo-asymmetry and the least-squares estimation (IDEAL) technique to detect hepatic steatosis (HS) in potential liver donors using histopathology as the reference standard.
  
  
  METHODS
  Forty-nine potential liver donors (32 male, 17 female; mean age, 31.7 years) were included. All patients were imaged using the in- and out-of-phase (IOP) gradient-echo (GRE) and IDEAL techniques on a 1.5 T MR scanner. To estimate the hepatic fat fraction (FF), two reviewers performed regions-of-interest measurement in 15 areas of the liver seen on the IOP images and on the IDEAL-FF images. The magnetic resonance imaging (MRI) and pathology values of macrosteatosis were correlated using the Pearson correlation coefficient. We analyzed the diagnostic performance of IOP imaging and IDEAL for detecting HS.
  
  
  RESULTS
  The results of the hepatic-FF estimated on IDEAL were well correlated with the histologic degree of macrosteatosis (γ = 0.902, P < 0.001). IDEAL showed 100% sensitivity and 91% specificity for detecting HS, and IOP imaging showed 87.5% sensitivity and 97% specificity, respectively.
  
  
  CONCLUSIONS
  IDEAL is a useful tool for the preoperative diagnosis of HS in potential living liver donors; it can also help to avoid unnecessary biopsies in these patients.
authors: Department of Radiology, Seoul National University Hospital, Seoul, Korea.
authors: Eugene
authors: E
authors: Joe
authors: Jeong Min
authors: JM
authors: Lee
authors: Kyung Won
authors: KW
authors: Kim
authors: Kyung Bun
authors: KB
authors: Lee
authors: Soo Jin
authors: SJ
authors: Kim
authors: Jee Hyun
authors: JH
authors: Baek
authors: Cheong Il
authors: CI
authors: Shin
authors: Kyung Suk
authors: KS
authors: Suh
authors: Nam Joon
authors: NJ
authors: Yi
authors: Joon Koo
authors: JK
authors: Han
authors: Byung Ihn
authors: BI
authors: Choi
mesh_terms: D000328:Adult; D000465:Algorithms; D005234:Fatty Liver / Q000473:pathology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016031:Liver Transplantation / Q000473:pathology*; D019520:Living Donors; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D018579:Patient Selection; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity