Spectral Unmixing Imaging for Differentiating Brown Adipose Tissue Mass and Its Activation

Abstract

Recent large-scale clinical analysis indicates that brown adipose tissue (BAT) mass levels inversely correlate with body-mass index (BMI), suggesting that BAT is associated with metabolic disorders such as obesity and diabetes. PET imaging with 18F-FDG is the most commonly used method for visualizing BAT. However, this method is not able to differentiate between BAT mass and BAT activation. This task, in fact, presents a tremendous challenge with no currently existing methods to separate BAT mass and BAT activation. Our previous results indicated that BAT could be successfully imaged in mice with near infrared fluorescent (NIRF) curcumin analogues. However, the results from conventional NIRF imaging could not reflect what portion of the NIRF signal from BAT activation contributed to the signal observed. To solve this problem, we used spectral unmixing to separate/unmix NIRF signal from oil droplets in BAT, which represents its mass and NIRF signal from blood, which represents BAT activation. In this report, results from our proof-of-concept investigation demonstrated that spectral unmixing could be used to separate NIRF signal from BAT mass and BAT activation.