# Enabling accurate identification and quantification of brown adipose tissue mass by xenon enhanced computed tomography > **NIH NIH R01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2021 · $372,580 ## Abstract PROJECT SUMMARY / ABSTRACT In the US, more than 36% of the population is obese and 9.4% has diabetes, most of which is type-2 diabetes driven by obesity-associated insulin resistance. Current anti-obesity strategies have been proven to be largely inadequate, and new-targeted therapies are desperately needed to stop this epidemic. At the fundamental level, obesity results from the imbalance between energy intake and energy expenditure. The latter can be regulated by the activity of brown adipose tissue (BAT), a tissue that plays a regulatory role not only in energy balance, but also in glucose homeostasis. As a result, new therapeutic approaches are now being devised to target BAT for the treatment of obesity and diabetes. However, a major roadblock to the development of such therapies is the ability to detect and quantify BAT mass accurately. Current techniques are either too insensitive, or lack the necessary specificity to differentiate this tissue from white adipose tissue. This is especially true in overweight/obese subjects - the target population for interventional therapies targeting BAT. The goal of the proposed research project is to develop a new imaging approach based on low-dose, xenon- enhanced CT (XECT) that can detect BAT and yield accurate measurements of its mass, independently of its activity. This proposal builds upon our preliminary results, in which we had shown that the inert and lipophilic gas xenon can be used as a CT contrast agent to detect and quantify BAT mass. Regardless of the tissue's thermogenic capacity, hydration status, and glucose uptake capacity, upon stimulation of thermogenic activity, xenon accumulates into BAT at a concentration high enough to significantly change the radiodensity of this tissue, making BAT visible in CT images. Our objectives in this application are: a) to characterize xenon uptake dynamics in BAT as a function of tissue hydration and thermogenic potency in lean and obese non human primates animal models; b) to characterize and optimize low-dose XECT protocols for use in longitudinal studies in humans; and c) to establish that low- dose XECT can correctly identify BAT with greater sensitivity and specificity than 18F-FDG-PET/CT, the most widely used technique for measurement of BAT volume, using biopsy as ground truth. XECT will enable accurate quantification of BAT mass in the general adult human population, while providing new insights into the morphological changes that occur in this tissue during the onset of obesity. This project is expected to have a high impact; this novel approach can be easily implemented on standard PET/CT platforms and combined with other functional measures of BAT to increase their accuracy by reducing partial volume effects. Accurate quantification of BAT mass and activity is expected to lead to a better understanding of the growth, evolution, and remodeling of this tissue resulting from various stimuli and conditions. ## Key facts - **NIH application ID:** 10227219 - **Project number:** 5R01DK123206-02 - **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL - **Principal Investigator:** Rosa Tamara Branca - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $372,580 - **Award type:** 5 - **Project period:** 2020-09-01 → 2024-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10227219 ## Citation > US National Institutes of Health, RePORTER application 10227219, Enabling accurate identification and quantification of brown adipose tissue mass by xenon enhanced computed tomography (5R01DK123206-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10227219. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*