Connectivity based on glucose dynamics reveals exaggerated sensorimotor network coupling on subject-level in Parkinson's disease.

Autor: Ruppert-Junck, Marina C., Heinecke, Vanessa, Librizzi, Damiano, Steidel, Kenan, Beckersjürgen, Maya, Verburg, Frederik A., Schurrat, Tino, Luster, Markus, Müller, Hans-Helge, Timmermann, Lars, Eggers, Carsten, Pedrosa, David
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Zdroj: European Journal of Nuclear Medicine & Molecular Imaging; Oct2024, Vol. 51 Issue 12, p3630-3642, 13p
Abstrakt: Purpose: While fMRI provides information on the temporal changes in blood oxygenation, 2- [18F]fluoro-2-deoxy-D-glucose ([18F]FDG)-PET has traditionally offered a static snapshot of brain glucose consumption. As a result, studies investigating metabolic brain networks as potential biomarkers for neurodegeneration have primarily been conducted at the group level. However, recent pioneering studies introduced time-resolved [18F]FDG-PET with constant infusion, which enables metabolic connectivity studies at the individual level. Methods: In the current study, this technique was employed to explore Parkinson's disease (PD)-related alterations in individual metabolic connectivity, in comparison to inter-subject measures and hemodynamic connectivity. Fifteen PD patients and 14 healthy controls with comparable cognition underwent sequential resting-state dynamic PET with constant infusion and functional MRI. Intrinsic networks were identified by independent component analysis and interregional connectivity calculated for summed static PET images, PET time series and functional MRI. Results: Our findings revealed an intrinsic sensorimotor network in PD patients that has not been previously observed to this extent. In PD, a significantly higher number of connections in cortical motor areas was observed compared to elderly control subjects, as indicated by both static PET and functional MRI (pBonferroni−Holm = 0.027), as well as constant infusion PET and functional MRI connectomes (pBonferroni−Holm = 0.012). This intensified coupling was associated with disease severity (ρ = 0.56, p = 0.036). Conclusion: Metabolic connectivity, as revealed by both static and dynamic PET, provides unique information on metabolic network activity. Subject-level metabolic connectivity based on constant infusion PET may serve as a potential marker for the metabolic network signature in neurodegeneration. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index