Summary

Metabolic syndrome and its individual components lead to wideranging consequences, many of which affect the central nervous system. In this study, we compared the [18F]FDG regional brain metabolic pattern of participants with type 2 diabetes mellitus (T2DM) and non-DM obese individuals.

In our prospective study, 51 patients with controlled T2DM (ages 50.6 ± 8.0 years) and 45 non-DM obese participants (ages 52.0 ± 9.6 years) were enrolled. Glucose levels measured before PET/CT examination (pre-PET glucose) as well as laboratory parameters assessing glucose and lipid status were determined. NeuroQ application (NeuroQTM 3.6, Syntermed, Philips) was used to evaluate regional brain metabolic differences. [18F]FDG PET/CT (AnyScan PC, Mediso) scans, estimating brain metabolism, were transformed to MNI152 brain map after T1 registration and used for SPM-based group comparison of brain metabolism corrected for pre-PET glucose, and correlation analysis with laboratory parameters.

NeuroQ analysis did not reveal significant regional metabolic defects in either group. Voxel-based group comparison revealed significantly (P_FWE<0.05) decreased metabolism in the region of the precuneus and in the right superior frontal gyrus (rSFG) in the diabetic group as compared to the obese patients. Data analysis corrected for pre-PET glucose level showed a hypometabolic difference only in the rSFG in T2DM. Voxel-based correlation analysis showed significant negative correlation of the metabolism in the following brain regions with pre-PET glucose in diabetes: precuneus, left posterior orbital gyrus, right calcarine cortex and right orbital part of inferior frontal gyrus; whilst in the obese group only the right rolandic (pericentral) operculum proved to be sensitive to pre-PET glucose level.

To our knowledge, this is the first study to perform pre-PET glucose level corrected comparative analysis of brain metabolism in T2DM and obesity. We also examined the pre-PET glucose level dependency of regional cerebral metabolism in the two groups separately. Large-scale future studies are warranted to perform further correlation analysis with the aim of determining the effects of metabolic disturbances on brain metabolism.

Keywords: [ 18F]FDG, Metabolism, Brain, Type 2 diabetes mellitus, Obesity

Results from AnyScan® PET/CT

To investigate cerebral metabolism, all participants underwent brain [18F]FDG-PET/CT examinations applying AnyScan® PET/CT (Mediso, Hungary). PET acquisition was initiated 45 min (+/− 5 min) after injecting 3.5 MBq/Bw [18F]FDG intravenously using an automated infusion system (MEDRAD Intego, Bayer). A low-dose CT was also performed for attenuation correction. The parameters of static PET acquisition were the following: 10 min/FOV, with voxel size of 2×2×2 mm and matrix size of 160×160×76, whilst low-dose CT parameters were as follows: 120 kVp and 100 mAs.

Fig. 2 The left side show the thresholded voxel-wise SPM{t} maps overlaid on the population-averaged T1- weighted images, representing the lower [18F]FDG uptake in diabetes group relative to the obese group. The colour scales demonstrate the t values above the applied PFWE<0.05 statistical threshold. In this analysis, we did not apply correction for pre-PET blood glucose level. In the right side, the boxplots demonstrate the group difference in globally normalised FDG uptake at the highest local Student t maxima> <0,05 statistical threshold. In this analysis, we did not apply correction for pre-PET blood glucose level. In the right side, the boxplots demonstrate the group difference in globally normalized FDG uptake at the highest local Student t maxima

Table 6 Results of statistical parametric mapping (SPM) analyses

Conclusion

Pre-PET glucose level dependent hypometabolism was detected in the precuneus in type 2 diabetic individuals compared to non-DM obese participants. To our knowledge, this is the first study to perform pre-PET glucose level corrected comparative analysis of brain metabolism in T2DM and obesity. Pre-PET glucose sensitive brain regions were also revealed in the two study groups separately. Our findings highlight the importance of future correlative studies in the search for mechanistic explanations of the effect of dysmetabolic states on brain glucose metabolism. Since individuals with T2DM/obesity face impairments in daily living activities, imposing a considerable burden of care on both society and family, sensitive diagnostic methods showing alterations in cerebral metabolism have clinical significance as biological markers derived from brain imaging may be effective early indicators of the appearance of cerebrovascular diseases.

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