title: Quantification of brown and white adipose tissue based on Gaussian mixture model using water-fat and T2* MRI in adolescents.
abstract: To develop a technique for the separation and quantification of brown adipose tissue (BAT) and white adipose tissue (WAT) using fat fraction and T2* intensity based on the Gaussian mixture model (GMM).
  
  
  
  Chemical-shift water-fat and T2* images were acquired at the neck, supraclavicular, interscapular, and paravertebral regions in 24 volunteers (Obese: n = 12, female/male = 6/6, body mass index [BMI] = 31.3 ± 2.3 kg/m2, age = 16.1 ± 0.6; Normal weight: n = 12, female/male = 6/6, BMI = 21.2 ± 2.4 kg/m2, age = 12.9 ± 2.4) using a 3T scanner with the chemical-shift water-fat mDixon sequence. BAT and WAT were clustered based on the Gaussian mixture model using the expectation-maximization algorithm. Results and reproducibility were compared and assessed using independent t-tests and intraclass correlation coefficient.
  
  
  
  BAT in obese participants was predominately found at the supraclavicular region and in normal-weight participants it was more scattered and distributed in interscapular-supraclavicular, axillary, and spine regions. Absolute volume of BAT was higher in the obese group (Obese: 315.2 mL [±89.1], Normal weight: 248.5 mL [±86.4]), but BAT/WAT ratios were significantly higher (P = 0.029) in the normal group. T2* of BAT (P = 0.04) and volume of WAT (P < 0.001) were significantly lower in the normals. Within-group comparison between male and female indicated no significant differences were found in volume (P = 0.776 (normal), 0.501 [obese]), T2* (P = 0.908 [normal], 0.249 [obese]) and fat-fraction of BAT (P = 0.985 [normal], 0.108 [obese]). The intraclass correlation coefficient showed a good reproducibility in volume (BAT: 0.997, WAT: 0.948), T2* (BAT: 0.969, WAT: 0.983), and fat-fraction (BAT: 0.952, WAT: 0.517).
  
  
  
  BAT identified by this method was in agreement with other studies in terms of location, fat-fraction value, and T2* intensity. The proposed GMM-based segmentation could be a useful nonradiation imaging method for assessment of adipose tissue, in particular for serial follow-up of volume changes after drug or lifestyle interventions for obesity.
  
  
  
  2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:758-768.
authors.affiliation: Department of Imaging and Interventional Radiology, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR.
authors.forename: Steve C N
authors.initials: SCN
authors.lastname: Hui
authors.affiliation: Department of Imaging and Interventional Radiology, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR.
authors.forename: Jacky K L
authors.initials: JKL
authors.lastname: Ko
authors.affiliation: Department of Imaging and Interventional Radiology, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR.
authors.forename: Teng
authors.initials: T
authors.lastname: Zhang
authors.affiliation: Department of Medicine and Therapeutics, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR.|Chow Yuk Ho Technology Centre for Innovative Medicine, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR.
authors.forename: Lin
authors.initials: L
authors.lastname: Shi
authors.affiliation: Department of Imaging and Interventional Radiology, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR.
authors.forename: David K W
authors.initials: DKW
authors.lastname: Yeung
authors.affiliation: Department of Imaging and Interventional Radiology, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR.|Research Center for Medical Image Computing, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR.
authors.forename: Defeng
authors.initials: D
authors.lastname: Wang
authors.affiliation: Philips Healthcare, Sha Tin, New Territories, Hong Kong SAR.
authors.forename: Queenie
authors.initials: Q
authors.lastname: Chan
authors.affiliation: Department of Imaging and Interventional Radiology, Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR.
authors.forename: Winnie C W
authors.initials: WCW
authors.lastname: Chu
mesh_terms: D002001:Adipose Tissue, Brown / Q000000981:diagnostic imaging*; D052436:Adipose Tissue, White / Q000000981:diagnostic imaging*; D000293:Adolescent; D002648:Child; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009765:Obesity / Q000000981:diagnostic imaging*; D015203:Reproducibility of Results
keywords: 
  T2* imaging; Gaussian mixture model; MRI; brown adipose tissue; chemical shift water-fat separation; white adipose tissue