Purpose <p>This study aims to construct an individualized glucose metabolism network using total-body ¹⁸F-FDG PET imaging, which provides a comprehensive view of glucose metabolism across various organs, to explore the role of inter-organ interactions in Diabetes Mellitus (DM).</p> Methods <p>In this study, we constructed covariance metabolic networks using static total-body PET images, normalized by lean body mass, from 36 patients with DM (DM group) and 36 age- and sex-matched healthy controls (HC group). Differences in network properties between the DM and HC groups were evaluated at both group and individual levels. In addition, correlation analysis was performed to explore the relationship between network properties and baseline clinical data in the DM subjects.</p> Results <p>We observed that the same edges in the first three edges with the largest values were brain-subcutaneous adipose tissue (SAT) and brain-visceral adipose tissue (VAT) at both group and individual levels. There was a positive correlation between the brain-VAT and BMI and there was a negative correlation between the brain-SAT and age. The most perturbed organ was the brain at both group and individual levels, and there was a positive correlation between the strength of abnormality of brain and age.</p> Conclusion <p>This study successfully used static total-body PET imaging to construct individualized glucose metabolism networks for patients with DM, identifying the brain-VAT and brain-SAT as the most significantly altered edge and the brain as the most affected organ. These findings provide novel insights into the role of the brain-white adipose tissue axis in glucose metabolism in DM.</p>