title: MR fat fraction mapping: a simple biomarker for liver steatosis quantification in nonalcoholic fatty liver disease patients.
abstract: OBJECTIVE
  To assess the performance, postprocessing time, and intra- and interobserver agreement of a simple magnetic resonance-based mapping technique to quantify liver fat.
  
  
  METHODS
  This prospective, single-center study included 26 patients who were overweight with type 2 diabetes and at risk for nonalcoholic fatty liver disease. Mapping of the liver was based on a triple echo gradient-echo sequence, and (1)H magnetic resonance spectroscopy was used as the reference standard. The nonparametric Spearman correlation coefficient and the Wilcoxon test were used for comparisons between mapping and spectroscopy. The mapping was assessed for its predictive performance using the area under the curve of a receiver operating characteristic curve. Intraclass correlation coefficients were used to calculate intra- and interobserver's agreement for mapping measurements.
  
  
  RESULTS
  Patients had a mean fat percentage of 11.7% (range, 2-35.4%). A strong correlation was seen between mapping and spectroscopy (r = 0.89, P < .0001). A cutoff of 6.9% for fat fraction mapping was found to diagnose steatosis with 93% sensitivity and 100% specificity with an area under the curve of 0.99. Mapping of the liver had shorter acquisition and post-processing times than spectroscopy (5 min vs. 38 min; P < .0001). Mapping measurements had an intra- and interobserver agreement of 0.98 and 0.99, respectively.
  
  
  CONCLUSIONS
  The magnetic resonance-based liver mapping can accurately quantify liver fat with a cutoff value of 6.9% and excellent intra- and interobserver agreement. This mapping technique, with its simple methodology and short postprocessing time, has the potential to be included in routine abdominal protocols.
authors.affiliation: Center for Neuroscience and Cell Biology, PhD Program in Experimental Biology and Biomedicine, University of Coimbra, Coimbra, Portugal. helenasleitao@zonmail.pt
authors.forename: Helena S
authors.initials: HS
authors.lastname: Leitão
authors.forename: Cláudia
authors.initials: C
authors.lastname: Paulino
authors.forename: Dírcea
authors.initials: D
authors.lastname: Rodrigues
authors.forename: Sónia I
authors.initials: SI
authors.lastname: Gonçalves
authors.forename: Cristina
authors.initials: C
authors.lastname: Marques
authors.forename: Manuela
authors.initials: M
authors.lastname: Carvalheiro
authors.forename: Carlos F G C
authors.initials: CF
authors.lastname: Geraldes
authors.forename: Filipe
authors.initials: F
authors.lastname: Caseiro-Alves
mesh_terms: D000273:Adipose Tissue / Q000473:pathology* / Q000503:physiopathology; D050154:Adiposity; D000328:Adult; D000368:Aged; D015415:Biomarkers; D003924:Diabetes Mellitus, Type 2 / Q000150:complications / Q000473:pathology* / Q000503:physiopathology*; D005234:Fatty Liver / Q000209:etiology / Q000473:pathology* / Q000503:physiopathology*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D065626:Non-alcoholic Fatty Liver Disease; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D015415:Biomarkers
keywords: Magnetic resonance imaging; fat quantification; fatty liver disease; magnetic resonance spectroscopy; mapping