The brain’s resting-state energy consumption is expected to be driven by spontaneous activity. We previously used 50 resting-state fMRI (rs-fMRI) features to predict [18F]FDG SUVR as a proxy of glucose metabolism. Here, we expanded on our effort by estimating [18F]FDG kinetic parameters Ki(irreversible uptake), K1(delivery), k3(phosphorylation) in a large healthy control group (n = 47). Describing the parameters’ spatial distribution at high resolution (216 regions), we showed that K1is the least redundant (strong posteromedial pattern), and Kiand k3have relevant differences (occipital cortices, cerebellum, thalamus). Using multilevel modeling, we investigated how much spatial variance of [18F]FDG parameters could be explained by a combination of a) rs-fMRI variables, b) cerebral blood flow (CBF) and metabolic rate of oxygen (CMRO2) from15O PET. Rs-fMRI-only models explained part of the individual variance in Ki(35%), K1(14%), k3(21%), while combining rs-fMRI and CMRO2led to satisfactory description of Ki(46%) especially. Kiwas sensitive to both local rs-fMRI variables (ReHo) and CMRO2, k3to ReHo, K1to CMRO2. This work represents a comprehensive assessment of the complex underpinnings of brain glucose consumption, and highlights links between 1) glucose phosphorylation and local brain activity, 2) glucose delivery and oxygen consumption.

The brain’s “dark energy” puzzle upgraded: [18F]FDG uptake, delivery and phosphorylation, and their coupling with resting-state brain activity

Volpi, Tommaso;Corbetta, Maurizio;Bertoldo, Alessandra
2025

Abstract

The brain’s resting-state energy consumption is expected to be driven by spontaneous activity. We previously used 50 resting-state fMRI (rs-fMRI) features to predict [18F]FDG SUVR as a proxy of glucose metabolism. Here, we expanded on our effort by estimating [18F]FDG kinetic parameters Ki(irreversible uptake), K1(delivery), k3(phosphorylation) in a large healthy control group (n = 47). Describing the parameters’ spatial distribution at high resolution (216 regions), we showed that K1is the least redundant (strong posteromedial pattern), and Kiand k3have relevant differences (occipital cortices, cerebellum, thalamus). Using multilevel modeling, we investigated how much spatial variance of [18F]FDG parameters could be explained by a combination of a) rs-fMRI variables, b) cerebral blood flow (CBF) and metabolic rate of oxygen (CMRO2) from15O PET. Rs-fMRI-only models explained part of the individual variance in Ki(35%), K1(14%), k3(21%), while combining rs-fMRI and CMRO2led to satisfactory description of Ki(46%) especially. Kiwas sensitive to both local rs-fMRI variables (ReHo) and CMRO2, k3to ReHo, K1to CMRO2. This work represents a comprehensive assessment of the complex underpinnings of brain glucose consumption, and highlights links between 1) glucose phosphorylation and local brain activity, 2) glucose delivery and oxygen consumption.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3571976
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