Characterisation and identification of brown adipose tissue on positron-emission tomography and magnetic resonance imaging Since the first published description of brown adipose tissue (BAT) in 1551 its reputation has changed from that of a mere curiosity of little physiological significance in adult humans, to meriting reclassification as a metabolic organ in its own right. Obesity is a major global public health problem. Modulation of non-shivering thermogenesis through BAT manipulation presents an attractive therapeutic target for inducing weight loss. Testing the efficacy of such pharmacological agents requires the development of a reliable imaging biomarker to enable BAT quantification. In this thesis we have evaluated the effectiveness of positron-emission tomography (PET) and magnetic resonance (MR) imaging in quantifying BAT. Retrospective analysis of 3,295 consecutive PET scans performed at University Hospitals Coventry & Warwickshire NHS Trust (Coventry, UK) in 2007-2012 showed 18F-FDG uptake consistent with BAT in 5.3% of scans. Gender (female), age (younger), BMI (lower), serum glucose (lower), time of day (earlier), and temperature (lower) were all significant predictors of BAT prevalence. Regression analysis showed patients’ age and preceding day’s minimum temperature to correlate most strongly with BAT volume, while the impact of other factors is less clear. We also showed the pattern of BAT uptake within individuals to be consistent across serial PET scans. Quantitative colocalisation techniques showed this degree of colocalisation to be significant in 14/15 patients, implying fixed BAT deposits in adult humans. Concerns over the high ionising radiation dose of PET scans has stimulated research into MR as an alternative means of detecting BAT, with the potential to identify BAT irrespective of its activation state. Using IDEAL FSE sequences acquired on a 3 Tesla clinical MR scanner, we found BAT to have a significantly lower fat fraction than white adipose tissue in rats post mortem and adult humans in vivo. Our efforts to identify BAT prospectively using fat fraction yielded inconsistent results.