2025/05/15 by Tommaso Volpi, John J. Lee, Andrei G. Vlassenko +3 · 1 voice
Neuroscience · Medicine · #Functional Brain Connectivity Studies #Advanced MRI Techniques and Applications #Optical Imaging and Spectroscopy Techniques
paper · doi:10.1177/0271678x251329707
openalex publication_date 2025/05/15 · openalex created_date 2025/05/16 · openalex updated_date 2026/08/01
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 [ 18 F]FDG SUVR as a proxy of glucose metabolism. Here, we expanded on our effort by estimating [ 18 F]FDG kinetic parameters K i (irreversible uptake), K 1 (delivery), k 3 (phosphorylation) in a large healthy control group (n = 47). Describing the parameters’ spatial distribution at high resolution (216 regions), we showed that K 1 is the least redundant (strong posteromedial pattern), and K i and k 3 have relevant differences (occipital cortices, cerebellum, thalamus). Using multilevel modeling, we investigated how much spatial variance of [ 18 F]FDG parameters could be explained by a combination of a) rs-fMRI variables, b) cerebral blood flow (CBF) and metabolic rate of oxygen (CMRO 2 ) from 15 O PET. Rs-fMRI-only models explained part of the individual variance in K i (35%), K 1 (14%), k 3 (21%), while combining rs-fMRI and CMRO 2 led to satisfactory description of K i (46%) especially. K i was sensitive to both local rs-fMRI variables ( ReHo ) and CMRO 2 , k 3 to ReHo , K 1 to CMRO 2 . 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.