Quantification of brown and white adipose tissue based on Gaussian mixture model using water-fat and T2* MRI in adolescents
Publication in refereed journal



To develop a technique for the separation and quantification of brown adipose tissue (BAT) and white adipose tissue (WAT) using fat fraction and math formula intensity based on the Gaussian mixture model (GMM).

Materials and Methods

Chemical-shift water–fat and math formula 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. math formula 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]), math formula (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), math formula (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 math formula 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.
著者Hui SC, Ko JK, Zhang T, Shi L, Yeung DK, Wang D, Chan Q, Chu WC
期刊名稱Journal of Magnetic Resonance Imaging
頁次758 - 768
關鍵詞T2* imaging, Gaussian mixture model, MRI, brown adipose tissue, chemical shift water-fat separation, white adipose tissue

上次更新時間 2020-18-10 於 02:24