title: Calibration of a semi-automated segmenting method for quantification of adipose tissue compartments from magnetic resonance images of mice.
abstract: OBJECTIVE
  To use an automated water-suppressed magnetic resonance imaging (MRI) method to objectively assess adipose tissue (AT) volumes in whole body and specific regional body components (subcutaneous, thoracic and peritoneal) of obese and lean mice.
  
  
  METHODS
  Water-suppressed MR images were obtained on a 7T, horizontal-bore MRI system in whole bodies (excluding head) of 26 week old male C57BL6J mice fed a control (10% kcal fat) or high-fat diet (60% kcal fat) for 20 weeks. Manual (outlined regions) versus automated (Gaussian fitting applied to threshold-weighted images) segmentation procedures were compared for whole body AT and regional AT volumes (i.e., subcutaneous, thoracic, and peritoneal). The AT automated segmentation method was compared to dual-energy X-ray (DXA) analysis.
  
  
  RESULTS
  The average AT volumes for whole body and individual compartments correlated well between the manual outlining and the automated methods (R2>0.77, p<0.05). Subcutaneous, peritoneal, and total body AT volumes were increased 2-3 fold and thoracic AT volume increased more than 5-fold in diet-induced obese mice versus controls (p<0.05). MRI and DXA-based method comparisons were highly correlative (R2=0.94, p<0.0001).
  
  
  CONCLUSIONS
  Automated AT segmentation of water-suppressed MRI data using a global Gaussian filtering algorithm resulted in a fairly accurate assessment of total and regional AT volumes in a pre-clinical mouse model of obesity.
authors.affiliation: Advanced Magnetic Resonance Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104.
authors.forename: Philippe
authors.initials: P
authors.lastname: Garteiser
authors.forename: Sabrina
authors.initials: S
authors.lastname: Doblas
authors.forename: Rheal A
authors.initials: RA
authors.lastname: Towner
authors.forename: Timothy M
authors.initials: TM
authors.lastname: Griffin
mesh_terms: D015502:Absorptiometry, Photon; D000273:Adipose Tissue / Q000473:pathology*; D000465:Algorithms; D000818:Animals; D050218:Body Fat Distribution; D059305:Diet, High-Fat; D004195:Disease Models, Animal; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D016011:Normal Distribution; D009765:Obesity / Q000209:etiology / Q000473:pathology*
keywords: AT; Adipose tissue; Adiposity; Body fat distribution analysis; DXA; Diet-induced obesity; Dual-energy X-ray absorptiometry; Fat-weighted MRI; MRI; Magnetic resonance imaging; ROI; Region of interest; T; Tesla
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