BackgroundSystemic inflammation impairs brain function and is increasingly implicated in the etiology of common mental illnesses, particularly depression and Alzheimer’s disease. Immunotherapies selectively targeting proinflammatory cytokines demonstrate efficacy in a subset of patients with depression. However, efforts to identify patients most vulnerable to the central effects of inflammation are hindered by insensitivity of conventional structural magnetic resonance imaging.MethodsWe used quantitative magnetization transfer (qMT) imaging, a magnetic resonance imaging technique that enables quantification of changes in brain macromolecular density, together with experimentally induced inflammation to investigate effects of systemic inflammatory challenge on human brain microstructure. Imaging with qMT was performed in 20 healthy participants after typhoid vaccination and saline control injection. An additional 20 participants underwent fluorodeoxyglucose positron emission tomography following the same inflammatory challenge.ResultsThe qMT data demonstrated that inflammation induced a rapid change in brain microstructure, reflected in increased magnetization exchange from free (water) to macromolecular-bound protons, within a discrete region of insular cortex implicated in representing internal physiologic states including inflammation. The functional significance of this change in insular microstructure was demonstrated by correlation with inflammation-induced fatigue and fluorodeoxyglucose positron emission tomography imaging, which revealed increased resting glucose metabolism within this region following the same inflammatory challenge.ConclusionsTogether these observations highlight a novel structural biomarker of the central physiologic and behavioral effects of mild systemic inflammation. The widespread clinical availability of magnetic resonance imaging supports the viability of qMT imaging as a clinical biomarker in trials of immunotherapeutics, both to identify patients vulnerable to the effects of systemic inflammation and to monitor neurobiological responses.

Objectives To evaluate the effect of pre-scan blood glucose levels (BGL) on standardized uptake value (SUV) in 18 F-FDG-PET scan. Methods A literature review was performed in the MEDLINE, Embase, and Cochrane library databases. Multivariate regression analysis was performed on individual datum to investigate the correlation of BGL with SUV max and SUV mean adjusting for sex, age, body mass index (BMI), diabetes mellitus diagnosis, 18 F-FDG injected dose, and time interval. The ANOVA test was done to evaluate differences in SUV max or SUV mean among five different BGL groups (< 110, 110-125, 125-150, 150-200, and > 200 mg/dl). Results Individual data for a total of 20,807 SUV max and SUV mean measurements from 29 studies with 8380 patients was included in the analysis. Increased BGL is significantly correlated with decreased SUV max and SUV mean in brain (p < 0.001, p < 0.001,) and muscle (p < 0.001, p < 0.001) and increased SUV max and SUV mean in liver (p = 0.001, p = 0004) and blood pool (p = 0.008, p < 0.001). No significant correlation was found between BGL and SUV max or SUV mean in tumors. In the ANOVA test, all hyperglycemic groups had significantly lower SUVs compared with the euglycemic group in brain and muscle, and significantly higher SUVs in liver and blood pool. However, in tumors only the hyperglycemic group with BGL of > 200 mg/dl had significantly lower SUV max. Conclusion If BGL is lower than 200 mg/dl no interventions are needed for lowering BGL, unless the liver is the organ of interest. Future studies are needed to evaluate sensitivity and specificity of FDG-PET scan in diagnosis of malignant lesions in hyperglycemia.

FDG uptake is increased in hepatic steatosis, probably resulting from irreversible uptake in inflammatory cells superimposed on reversible hepatocyte uptake.

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• FDG standard uptake value in tumours helps clinicians assess response to treatment. • SUV is influenced by blood glucose; normalisation to blood glucose is recommended. • An alternative approach is to scale tumour SUV to liver SUV. • The brain used as a tumour surrogate shows that neither approach is valid. • Applying both approaches, however, appropriately corrects for blood glucose.

Hepatic steatosis is associated with obesity and insulin resistance. Whether hepatic glucose utilization rate (glucose phosphorylation rate; MRglu) is increased in steatosis and/or obesity is uncertain. Our aim was to determine the separate relationships of steatosis and obesity with MRglu. Sixty patients referred for routine PET/CT had dynamic PET imaging over the abdomen for 30 min post-injection of F-18-fluorodeoxyglucose (FDG), followed by Patlak–Rutland graphical analysis of the liver using abdominal aorta for arterial input signal. The plot gradient was divided by the intercept to give hepatic FDG clearance normalized to hepatic FDG distribution volume (ml/min per 100 ml) and multiplied by blood glucose to give hepatic MRglu (μmol/min per 100 ml). Hepatic steatosis was defined as CT density of ≤40 HU measured from the 60 min whole body routine PET/CT and obesity as body mass index of ≥30 kg/m2. Hepatic MRglu was higher in patients with steatosis (3.3±1.3 μmol/min per 100 ml) than those without (1.7±1.2 μmol/min per 100 ml; P<0.001) but there was no significant difference between obese (2.5±1.6 μmol/min per 100 ml) and non-obese patients (2.1±1.3 μmol/min per 100 ml). MRglu was increased in obese patients only if they had steatosis. Non-obese patients with steatosis still had increased MRglu. There was no association between MRglu and chemotherapy history. We conclude that MRglu is increased in hepatic steatosis probably through insulin resistance, hyperinsulinaemia and up-regulation of hepatic hexokinase, irrespective of obesity.

Because of obesity, non‐alcoholic fatty liver disease (NAFLD) is becoming increasingly important. 10% of NAFLD patients develop non‐alcoholic steatohepatitis (NASH), which may progress to cirrhosis and is now the leading indication for liver transplantation in the Western world. Prefibrotic NASH can only be reliably diagnosed by biopsy. However, given its success in other inflammatory diseases, PET/CT with 18F‐fluorodeoxyglucose (FDG), although non‐specific, may offer a promising approach to diagnosing not only NASH but also other inflammatory liver conditions. In addition, FDG PET has generated pathophysiological information on hepatic glucose metabolism and, diagnostically, used liver for quantification of tumour FDG accumulation (e.g. Deauville scoring). A review of hepatic FDG PET is therefore timely. There are two general approaches to the quantification of hepatic FDG accumulation: firstly, standard uptake value (SUV) and secondly dynamic PET. SUV is a poor index of hepatic metabolic function because most hepatic FDG (~75%) is un‐phosphorylated 60‐min postinjection. Hepatic fat is increased in NAFLD but accumulates negligible FDG. Because fat distribution is heterogeneous, maximum pixel SUV is therefore preferred to mean pixel SUV. Computer modelling of dynamic PET dissects the transport constants governing hepatic FDG kinetics but is challenged by the liver's dual blood supply. Graphical analysis is less informative but more robust and will be the preferred clinical approach to measurement of hepatic FDG phosphorylation. Previous dynamic PET studies have ignored hepatic fat and therefore potentially underestimated glucose accumulation in patients with hepatic steatosis. Future work should use graphical analysis of dynamic PET and correction for hepatic fat.

IIQ is strongly recommended. Isolated delay at 45 min is abnormal. However, 45 min imaging is not necessary if IIQ is performed.