Functional resting-state brain connectivity is accompanied by dynamic correlations of application-dependent [ 18 F]FDG PET-tracer fluctuations

Mario Amend, Tudor M. Ionescu, Xin Di, Bernd J. Pichler, Bharat B. Biswal, Hans F. Wehrl

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


Brain function is characterized by a convolution of various biochemical and physiological processes, raising the interest whether resting-state functional connectivity derived from hemodynamic scales shows underlying metabolic synchronies. Increasing evidence suggests that metabolic connectivity based on glucose consumption associated PET recordings may serve as a marker of cognitive functions and neuropathologies. However, to what extent fMRI-derived resting-state brain connectivity can also be characterized based on dynamic fluctuations of glucose metabolism and how metabolic connectivity is influenced by [ 18 F]FDG pharmacokinetics remains unsolved. Simultaneous PET/MRI measurements were performed in a total of 26 healthy male Lewis rats. Simultaneously to resting-state fMRI scans, one cohort (n = 15) received classical bolus [ 18 F]FDG injections and dynamic PET images were recorded. In a second cohort (n = 11) [ 18 F]FDG was constantly infused over the entire functional PET/MRI scans. Resting-state fMRI and [ 18 F]FDG-PET connectivity was evaluated using a graph-theory based correlation approach and compared on whole-brain level and for a default-mode network-like structure. Further, pharmacokinetic and tracer uptake influences on [ 18 F]FDG-PET connectivity results were investigated based on the different PET protocols. By integrating simultaneous resting-state fMRI and dynamic [ 18 F]FDG-PET measurements in the rat brain, we identified homotopic correlations between both modalities, suggesting an underlying synchrony between hemodynamic processes and glucose consumption. Furthermore, the presence of the prominent resting-state default-mode network-like structure was not only depicted on a functional scale but also from dynamic fluctuations of [ 18 F]FDG. In addition, the present findings demonstrated strong pharmacokinetic and tracer uptake dependencies of [ 18 F]FDG-PET connectivity outcomes. This study highlights the application of dynamic [ 18 F]FDG-PET to study cognitive brain functions and to decode underlying brain networks in the resting-state. Thereby, PET-derived connectivity outcomes indicated strong dependencies on tracer application regimens and subsequent time-varying tracer pharmacokinetics.

Original languageEnglish (US)
Pages (from-to)161-172
Number of pages12
StatePublished - Aug 1 2019

All Science Journal Classification (ASJC) codes

  • Neurology
  • Cognitive Neuroscience


  • Connectomics
  • Resting-state brain networks
  • Simultaneous PET/fMRI
  • fPET


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