Tumor delineation using noninvasive medical imaging modalities is important to determine the target volume in radiation treatment planning and to evaluate treatment response. It is expected that combined use of CT and functional information from 18 F-FDG PET will improve tumor delineation. However, until now, tumor delineation using PET has been based on static images of 18 F-FDG standardized uptake values (SUVs). 18 F-FDG uptake depends not only on tumor physiology but also on blood supply, distribution volume, and competitive uptake processes in other tissues. Moreover, 18 F-FDG uptake in tumor tissue and in surrounding healthy tissue depends on the time after injection. Therefore, it is expected that the glucose metabolic rate (MR glu ) derived from dynamic PET scans gives a better representation of the tumor activity than does SUV. The aim of this study was to determine tumor volumes in MR glu maps and to compare them with the values from SUV maps. Methods: Twenty-nine lesions in 16 dynamic 18 F-FDG PET scans in 13 patients with non-small cell lung carcinoma were analyzed. MR glu values were calculated on a voxel-by-voxel basis using the standard 2-compartment 18 F-FDG model with trapping in the linear approximation (Patlak analysis). The blood input function was obtained by arterial sampling. Tumor volumes were determined in SUV maps of the last time frame and in MR glu maps using 3-dimensional isocontours at 50% of the maximum SUV and the maximum MR glu , respectively. Results: Tumor volumes based on SUV contouring ranged from 1.31 to 52.16 cm 3 , with a median of 8.57 cm 3 . Volumes based on MR glu ranged from 0.95 to 37.29 cm 3 , with a median of 3.14 cm 3 . For all lesions, the MR glu volumes were significantly smaller than the SUV volumes. The percentage differences (defined as 100% · (V MR glu 2 V SUV )/V SUV , where V is volume) ranged from 212.8% to 284.8%, with a median of 232.8%. Conclusion: Tumor volumes from MR glu maps were significantly smaller than SUV-based volumes. These findings can be of importance for PET-based radiotherapy planning and therapy response monitoring.

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Objective. The frequent association of gout with metabolic syndrome and cardiovascular disease (CVD) suggests that it has a systemic component. Our objective was to study whether circulating proinflammatory cytokines are associated with comorbidities in gout patients.Methods. We studied 330 gout patients from 3 independent cohorts and compared them with 144 healthy individuals and 276 disease controls. We measured circulating levels of interleukin-8 (IL-8)/CXCL8, IL-1b, IL-6, IL-10, IL-12, and tumor necrosis factor, after which we performed proteome-wide analysis in a selection of samples to identify proteins that were possibly prognostic for the development of comorbidities. Replication analysis was performed specifically for myeloidrelated protein 8 (MRP-8)/MRP-14 complex.Results. Compared to healthy controls and disease control patients, patients with gouty arthritis (n 5 48) had significantly higher mean levels of CXCL8 (P < 0.001), while other cytokines were almost undetectable. Similarly, patients with intercritical gout showed high levels of CXCL8. CXCL8 was independently associated with diabetes mellitus in patients with intercritical gout (P < 0.0001). Proteome-wide analysis in gouty arthritis (n 5 18) and intercritical gout (n 5 39) revealed MRP-8 and MRP-14 as the proteins with the greatest differential expression between low and high levels of CXCL8 and also showed a positive correlation of MRP8/MRP14 complex with CXCL8 levels (R 2 5 0.49, P < 0.001). These findings were replicated in an independent cohort. The proteome of gout patients with high levels of CXCL8 was associated with diabetes mellitus (odds ratio 16.5 [95% confiDrs. Broen and Radstake

Crystal-proven gout was strongly associated with an increased prevalence of CVD. In patients with gout, characteristic gout severity factors were associated with CVD.

An easy-to-use diagnostic rule for gout developed in primary care shows good performance in secondary care and improves the predictive value of the clinical diagnosis of gout when joint fluid analysis is not available.