Image fat metabolism.

Metabolism is a fundamental process of life. However, non-invasive measurement of local tissue metabolism is limited today by a deficiency in adequate tools for in vivo observations. Reber et al. employed label-free multispectral optoacoustic tomography (MSOT) to non-invasively image brown adipose tissue (BAT) and white adipose tissue (WAT) in mice and humans and resolve BAT activation based on hemoglobin gradients. The 700–970 nm spectral range further enabled identification of BAT composition using lipid and water signatures. Importantly, MSOT readouts of BAT activation correlate with indirect calorimetry, demonstrating the utility of this approach to yield information on metabolism. Clinical MSOT using a handheld detector in humans allows the visualization of BAT based on spectral absorption signatures.

MSOT images at 800 nm exhibit areas with strong absorption (A) that are congruent with inter-scapular BAT (iBAT) in the corresponding cryoslice (C). MSOT images at 800 nm show iBAT and Sulzer vein (SV) in healthy mouse (A) and diabetic mouse (B) in vivo. iBAT in diabetic mice (DM) exhibited significantly weaker MSOT signal at 800nm (D) than healthy mice (HM).

(A) Anatomical image at 800 nm showing the iBAT profile and the Sulzer vein (SV). (C and D) unmixed oxygenated (HbO2) and deoxygenated (Hb) hemoglobin signal. After norepinephrine (NE) stimulation, both oxy- and deoxygenated hemoglobin signal in the iBAT increased significantly (B).

A: MRI-PET coronal co-registered image as well as MSOT imaging plane indicated by the yellow dotted line
B: Pseudo color in MRI/PET shows 18F-FDG uptake in activated BAT
C: MSOT handheld image from the same region shows BAT (white arrow) and muscle (green arrow)
D: Before and after cold activation, MSOT was used to image BAT (red arrows) and muscle.
E: In BAT the HbO2 intensity increased significantly with cold activation whereas no significant change was captured from muscle.

A: Pixels at the expected depths of BAT in the supraclavicular region were categorized according to there total blood volume (Hb+HbO2) and fat signal.
B: The pixels with high fat and low blood signal were characterized as WAT cluster, whereas pixels with low fat and high blood signal were characterized as BAT cluster. BAT and WAT clusters shown in (B) can be spectrally differentiated (C).

  • Chan XHD et al.,
    Multimodal Imaging Approach to Monitor Browning of Adipose Tissue In Vivo,
    JLR, April 13, 2018. DOI: 10.1194/jlr.D083410.
  • Reber J et al.,
    Non-invasive Measurement of Brown Fat Metabolism Based on Optoacoustic Imaging of Hemoglobin Gradients,
    Cell Metab. 2018 Mar 6;27(3):689-701.e4. DOI: 10.1016/j.cmet.2018.02.002.
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