Objective：This study aims to establish individual cerebral metabolic networks in Parkinson’s disease（PD）using integrated 18F - FDG - PET/MR imaging and Jensen - Shannon similarity estimation（JSSE）and investigate topological alterations in metabolic networks and their associations with functional networks. Methods：Twenty-eight patients with clinically confirmed PD（16 males and 12 females）who underwent 18F-FDG-PET/MR imaging at the Affiliated Nanjing Hospital of Nanjing Medical University from August 2022 to May 2024 were retrospectively analyzed，and 20 age-and sex-matched normal controls（NC）were included（10 males and 10 females）. Individual brain metabolic networks were constructed using the JSSE method，and Matlab2013b was used to analyze changes between network topological properties and metabolic connectivity in brain regions using Gretna. Data were analyzed using two independent samples t-test and Mann -Whitney U-test，and the Mantel test analyzed correlations between metabolic and functional network matrices in the PD group and the NC group. Results：Compared with the NC group，the PD group showed higher assortativity in terms of global attributes（t=-2.06，P=0.045）；in terms of nodal attributes，the centrality of nodal degree in the right fusiform gyrus was significantly reduced（t=3.32，P ＜ 0.001）；15 key metabolic connectivity parameters were reduced（P ＜ 0.001），with the reduction in metabolic connectivity between the left caudate nucleus and the left inferotemporal gyrus being the most pronounced. There was a significant positive correlation between the PD metabolic and functional network matrices（r=0.242，P ＜ 0.05），and the correlation was greater than that in the NC group（r=0.197，P ＜ 0.05）. Conclusion：The integrated PET/MR and JSSE framework demonstrates clinical efficacy in detecting cerebral topological reorganization and metabolic connectivity aberrations in PD. 18F - FDG - PET/MR imaging is useful for the early diagnosis of PD and for exploring changes in the mechanisms of intrinsic remodeling of the brain in PD patients from the perspective of brain metabolism and function.