title: Comparison of clinical semi-quantitative assessment of muscle fat infiltration with quantitative assessment using chemical shift-based water/fat separation in MR studies of the calf of post-menopausal women.
abstract: OBJECTIVE
  The goal of this study was to compare the semi-quantitative Goutallier classification for fat infiltration with quantitative fat-fraction derived from a magnetic resonance imaging (MRI) chemical shift-based water/fat separation technique.
  
  
  METHODS
  Sixty-two women (age 61 ± 6 years), 27 of whom had diabetes, underwent MRI of the calf using a T1-weighted fast spin-echo sequence and a six-echo spoiled gradient-echo sequence at 3 T. Water/fat images and fat fraction maps were reconstructed using the IDEAL algorithm with T2* correction and a multi-peak model for the fat spectrum. Two radiologists scored fat infiltration on the T1-weighted images using the Goutallier classification in six muscle compartments. Spearman correlations between the Goutallier grades and the fat fraction were calculated; in addition, intra-observer and inter-observer agreement were calculated.
  
  
  RESULTS
  A significant correlation between the clinical grading and the fat fraction values was found for all muscle compartments (P < 0.0001, R values ranging from 0.79 to 0.88). Goutallier grades 0-4 had a fat fraction ranging from 3.5 to 19%. Intra-observer and inter-observer agreement values of 0.83 and 0.81 were calculated for the semi-quantitative grading.
  
  
  CONCLUSIONS
  Semi-quantitative grading of intramuscular fat and quantitative fat fraction were significantly correlated and both techniques had excellent reproducibility. However, the clinical grading was found to overestimate muscle fat.
  
  
  CONCLUSIONS
  Fat infiltration of muscle commonly occurs in many metabolic and neuromuscular diseases. • Image-based semi-quantitative classifications for assessing fat infiltration are not well validated. • Quantitative MRI techniques provide an accurate assessment of muscle fat.
authors.affiliation: Musculoskeletal and Quantitative Imaging Research Group, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry Street, Suite 350, San Francisco, CA 94107, USA. Hamza.Alizai@ucsf.edu
authors.forename: Hamza
authors.initials: H
authors.lastname: Alizai
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Nardo
authors.forename: Dimitrios C
authors.initials: DC
authors.lastname: Karampinos
authors.forename: Gabby B
authors.initials: GB
authors.lastname: Joseph
authors.forename: Samuel P
authors.initials: SP
authors.lastname: Yap
authors.forename: Thomas
authors.initials: T
authors.lastname: Baum
authors.forename: Roland
authors.initials: R
authors.lastname: Krug
authors.forename: Sharmila
authors.initials: S
authors.lastname: Majumdar
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Link
mesh_terms: D000273:Adipose Tissue / Q000473:pathology*; D050154:Adiposity; D003924:Diabetes Mellitus, Type 2 / Q000473:pathology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007866:Leg; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D018482:Muscle, Skeletal / Q000473:pathology*; D017698:Postmenopause; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014867:Water / Q000032:analysis
chemical_list: D014867:Water