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大脑的“暗能量”谜题:[F]氟代脱氧葡萄糖摄取、传递与磷酸化,以及它们与静息态脑活动的耦合

The brain's "dark energy" puzzle : [F]FDG uptake, delivery and phosphorylation, and their coupling with resting-state brain activity.

作者信息

Volpi Tommaso, Lee John J, Vlassenko Andrei G, Goyal Manu S, Corbetta Maurizio, Bertoldo Alessandra

机构信息

Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.

Padova Neuroscience Center, University of Padova, Padova, Italy.

出版信息

J Cereb Blood Flow Metab. 2025 May 15:271678X251329707. doi: 10.1177/0271678X251329707.

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 [F]FDG SUVR as a proxy of glucose metabolism. Here, we expanded on our effort by estimating [F]FDG kinetic parameters (irreversible uptake), (delivery), (phosphorylation) in a large healthy control group (n = 47). Describing the parameters' spatial distribution at high resolution (216 regions), we showed that is the least redundant (strong posteromedial pattern), and and have relevant differences (occipital cortices, cerebellum, thalamus). Using multilevel modeling, we investigated how much spatial variance of [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) from O PET. Rs-fMRI-only models explained part of the individual variance in (35%), (14%), (21%), while combining rs-fMRI and CMRO led to satisfactory description of (46%) especially. was sensitive to both local rs-fMRI variables () and CMRO, to , to CMRO. 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.

摘要

大脑的静息态能量消耗预计由自发活动驱动。我们之前使用50个静息态功能磁共振成像(rs-fMRI)特征来预测[F]氟代脱氧葡萄糖标准化摄取值(SUVR),作为葡萄糖代谢的指标。在此,我们通过在一个大型健康对照组(n = 47)中估计[F]氟代脱氧葡萄糖动力学参数(不可逆摄取)、(输送)、(磷酸化),扩展了我们的研究。在高分辨率(216个区域)描述参数的空间分布时,我们发现是冗余度最小的(强烈的后内侧模式),并且和存在相关差异(枕叶皮质、小脑、丘脑)。使用多级建模,我们研究了[F]氟代脱氧葡萄糖参数的多少空间方差可以由以下因素的组合来解释:a)rs-fMRI变量,b)来自正电子发射断层扫描(PET)的脑血流量(CBF)和氧代谢率(CMRO)。仅rs-fMRI模型解释了个体方差的一部分(35%)、(14%)、(21%),而将rs-fMRI和CMRO结合尤其能令人满意地描述(46%)。对局部rs-fMRI变量()和CMRO都敏感,对敏感,对CMRO敏感。这项工作代表了对大脑葡萄糖消耗复杂基础的全面评估,并突出了1)葡萄糖磷酸化与局部脑活动之间、2)葡萄糖输送与氧消耗之间的联系。

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