Interest in brown adipose tissue remains high a decade after it was determined to be present outside of the neonatal period. In vivo imaging, however, has remained a challenge due to the lack of a imaging modality suitable for large healthy-volunteer studies, post-prandial investigations and vulnerable groups, such as children. Infrared thermography is increasingly accepted as a valid, non-invasive and flexible alternative but there is a wide approach to analysis between different groups. Defining the region of interest with anatomical borders rather than using a simple polygon may have advantages in terms of consistency but makes image analysis slower, limiting some applications. Our novel semi-automated method, using a custom-built graphical user interface, allows an 86% improvement in speed of image analysis (54.9 (38.3-71.4) seconds/image) without increases in variation between analysers or with repeated analysis. The improved efficiency demonstrated makes feasible larger studies, longer imaging periods or increased image acquisition frequency, providing an opportunity to study novel features of brown adipose tissue function.
Keywords: BAT, Brown adipose tissue; GUI, Graphical user interface; M, Manual; ROI, Region of interest; SA, Semi-automated; UCP, Uncoupling protein; automation; brown adipose tissue; human; infrared thermography; matlab; method comparison.
© 2021 Published by Elsevier B.V.