OBJECTIVES: The objective of this study was to explore the use of magnetic resonance imaging (MRI) to identify and quantify active brown adipose tissue (BAT) in adult humans. 2-Deoxy-2-[F]fluoro-D-glucose (FDG) positron emission tomography (PET) combined with computed tomography was used as a reference method to identify active BAT depots and to guide the MRI data analysis. MATERIALS AND METHODS: The ethics committee of the institute approved the protocol, and all participants provided written informed consent before participation. Both PET combined with computed tomography and MRI of BAT were performed in 11 healthy volunteers. Brown adipose tissue was activated by cooling the participants using a dedicated water-perfused suit. For the MRI examination of BAT, water-fat imaging and dynamic T2* imaging were performed at an effective temporal resolution of 2 minutes per volume. Water-fat images were derived from a multiecho MRI sequence using the Dixon technique. RESULTS: 2-Deoxy-2-[F]fluoro-D-glucose-PET identified active BAT in 8 of the 11 participants. Water-fat MRI showed that BAT depots had a fat fraction of 65.2% (7.0%) compared with 81.5% (5.4%) for the subcutaneous white adipose tissue (paired difference of 16.3% [4.9%]; P < 0.05). Dynamic T2* imaging during cold stimulation revealed signal fluctuations that were sensitive to BAT activation. The presence of these components correlated with BAT activation quantified from FDG-PET (r = 0.63; P < 0.05). CONCLUSIONS: Although FDG-PET has superior contrast for identifying active BAT, the MRI temporal resolution provides insight in activation dynamics. In addition, the flexibility of MRI allows for simultaneous mapping of tissue fat content and functional responses. The results indicate that MRI is a promising addition to PET for the identification of BAT and its activity responses to stimulation. An MRI-based methodology to quantify BAT activity is a highly desirable step in addressing the role of BAT in obesity disorders.
OBJECTIVES: The objective of this study was to explore the use of magnetic resonance imaging (MRI) to identify and quantify active brown adipose tissue (BAT) in adult humans. 2-Deoxy-2-[F]fluoro-D-glucose (FDG) positron emission tomography (PET) combined with computed tomography was used as a reference method to identify active BAT depots and to guide the MRI data analysis. MATERIALS AND METHODS: The ethics committee of the institute approved the protocol, and all participants provided written informed consent before participation. Both PET combined with computed tomography and MRI of BAT were performed in 11 healthy volunteers. Brown adipose tissue was activated by cooling the participants using a dedicated water-perfused suit. For the MRI examination of BAT, water-fat imaging and dynamic T2* imaging were performed at an effective temporal resolution of 2 minutes per volume. Water-fat images were derived from a multiecho MRI sequence using the Dixon technique. RESULTS:2-Deoxy-2-[F]fluoro-D-glucose-PET identified active BAT in 8 of the 11 participants. Water-fat MRI showed that BAT depots had a fat fraction of 65.2% (7.0%) compared with 81.5% (5.4%) for the subcutaneous white adipose tissue (paired difference of 16.3% [4.9%]; P < 0.05). Dynamic T2* imaging during cold stimulation revealed signal fluctuations that were sensitive to BAT activation. The presence of these components correlated with BAT activation quantified from FDG-PET (r = 0.63; P < 0.05). CONCLUSIONS: Although FDG-PET has superior contrast for identifying active BAT, the MRI temporal resolution provides insight in activation dynamics. In addition, the flexibility of MRI allows for simultaneous mapping of tissue fat content and functional responses. The results indicate that MRI is a promising addition to PET for the identification of BAT and its activity responses to stimulation. An MRI-based methodology to quantify BAT activity is a highly desirable step in addressing the role of BAT in obesity disorders.
Authors: Jie Deng; Lisa M Neff; Nicholas C Rubert; Bin Zhang; Richard M Shore; Jonathan D Samet; Paige C Nelson; Lewis Landsberg Journal: J Magn Reson Imaging Date: 2017-08-11 Impact factor: 4.813
Authors: Aliya Gifford; Theodore F Towse; Ronald C Walker; Malcolm J Avison; E Brian Welch Journal: Am J Physiol Endocrinol Metab Date: 2016-05-10 Impact factor: 4.310
Authors: Rosa T Branca; Andrew McCallister; Hong Yuan; Amir Aghajanian; James E Faber; Nicholas Weimer; Riley Buchanan; Carlos S Floyd; Michael Antonacci; Le Zhang; Alex Burant Journal: Proc Natl Acad Sci U S A Date: 2017-12-18 Impact factor: 11.205