Endocrine Abstracts

Energy homeostasis is a major focus of biomedical research due to the prevalence of obesity affecting over 890 million adults globally. The brain plays a central role in energy homeostasis through key neural circuits and endocrine signalling governing appetite regulation and satiety. Modern pharmacotherapeutics targeting gut hormone receptors, such as glucagon-like peptide-1 receptor agonists (GLP-1RAs), have emerged as effective adjunctive therapies in obesity management. However, the precise neural mechanisms underlying GLP-1RAs remain unclear, in part due to the relatively low spatial and temporal resolution of the current non-invasive neuroimaging methods. Contrast-enhanced ultrasound (CEUS) enables non-invasive assessment of the cerebral haemodynamics. Super-resolution ultrasound (SRUS) is an ultrasound imaging technique that localises and tracks the microbubbles (MBs), used as contrast agents, to achieve structural vascular maps with high spatial resolution and allows for quantitative blood flow analysis. We describe studies investigating SRUS as an imaging platform to investigate the effects of GLP-1RAs on the brain during the progression of metabolic disease. Images of satiety regulating brain regions are acquired using a high-frequency ultrasound scanner following an intravenous injection of MBs. The MB signals are extracted using singular value decomposition and localised using a cross-correlation algorithm. The localised MBs are used to construct a super-resolution map of the vasculature. Subsequently, the MBs are tracked across time to extract blood flow parameters. GLP-1RAs activate specific brain regions in wild type mice and the polygenic Tally Ho (TH) mouse model in which males develop diabetes and females develop obesity. Super-resolved neuronal activation maps of control and TH mice before and after peripheral administration of GLP-1RAs, can be used to assess the effects of GLP-1RAs as obesity develops. These studies suggest the potential utility of CEUS and SRUS to longitudinally and non-invasively assess dynamic changes in blood flow parameters which putatively map to neuronal activation patterns.