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Background: The cardiovascular committee of the European Association of Nuclear Medicine (EANM) recently published recommendations on imaging conditions to be observed during 18F-FDG PET imaging of vascular inflammation. This study aimed to evaluate the impact of applying these optimized imaging conditions on PET quantification of arterial 18F-FDG uptake.Methods and Results: Fifty-seven patients were prospectively recruited to undergo an early 18F-FDG PET/CT imaging at 60 minutes and repeat delayed imaging at ≥ 120 minutes post tracer injection. Routine oncologic 18F-FDG PET protocol was observed for early imaging, while delayed imaging parameters were optimized for vascular inflammation imaging as recommended by the EANM. Aortic SUVmax of the ascending aorta and SUVmean from the lumen of the superior vena cava (SVC SUVmean) were obtained on early and delayed imaging. Target-to-background ratio (TBR) was obtained for the early and delayed imaging. Aortic SUVmax increased by a mean of 70%, while SVC SUVmean decreased by a mean of 52% between early and delayed imaging (P < 0.001). TBR increased by 122% following delayed imaging. TBR increased, while SVC SUVmean declined across all time-points from 120 to > 180 minutes. Aortic SUVmax significantly increased at imaging time-points between 120 and 180 minutes. No significant improvement in aortic SUVmax was seen at imaging time-points beyond 180 minutes.Conclusions: 18F-FDG PET imaging conditions optimized for vascular inflammation imaging lead to an improved quantification through an increase in the quantified vascular tracer uptake and decrease in blood-pool background activity. [ABSTRACT FROM AUTHOR]

A detailed mathematical modeling framework for the risk of airborne infectious disease transmission in indoor spaces was developed to enable mathematical analysis of experiments conducted at the Airborne Infections Research (AIR) facility, eMalahleni, South Africa. A model was built using this framework to explore possible causes of why an experiment at the AIR facility did not produce expected results. The experiment was conducted at the AIR facility from August 31, 2015 to December 4, 2015, in which the efficacy of upper room germicidal ultraviolet (GUV) irradiation as an environmental control was tested. However, the experiment did not produce the expected outcome of having fewer infections in the test animal room than the control room. The simulation results indicate that dynamic effects, caused by switching the GUV lights, power outages, or introduction of new patients, did not result in the unexpected outcomes. However, a sensitivity analysis highlights that significant uncertainty exists with risk of transmission predictions based on current measurement practices, due to the reliance on large viable literature ranges for parameters. [ABSTRACT FROM AUTHOR]

A detailed mathematical modeling framework for the risk of airborne infectious disease transmission in indoor spaces was developed to enable mathematical analysis of experiments conducted at the Airborne Infections Research (AIR) facility, eMalahleni, South Africa. A model was built using this framework to explore possible causes of why an experiment at the AIR facility did not produce expected results. The experiment was conducted at the AIR facility from August 31, 2015 to December 4, 2015, in which the efficacy of upper room germicidal ultraviolet (GUV) irradiation as an environmental control was tested. However, the experiment did not produce the expected outcome of having fewer infections in the test animal room than the control room. The simulation results indicate that dynamic effects, caused by switching the GUV lights, power outages, or introduction of new patients, did not result in the unexpected outcomes. However, a sensitivity analysis highlights that significant uncertainty exists with risk of transmission predictions based on current measurement practices, due to the reliance on large viable literature ranges for parameters., (© 2018 Society for Risk Analysis.)