Tommaso Volpi, John J Lee, Andrei G Vlassenko, Manu S Goyal, Maurizio Corbetta, Alessandra Bertoldo
{"title":"大脑的“暗能量”谜题升级了:[18F]FDG的摄取、传递和磷酸化,以及它们与静息状态大脑活动的耦合。","authors":"Tommaso Volpi, John J Lee, Andrei G Vlassenko, Manu S Goyal, Maurizio Corbetta, Alessandra Bertoldo","doi":"10.1177/0271678X251329707","DOIUrl":null,"url":null,"abstract":"<p><p>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 [<sup>18</sup>F]FDG SUVR as a proxy of glucose metabolism. Here, we expanded on our effort by estimating [<sup>18</sup>F]FDG kinetic parameters <i>K</i><sub>i</sub> (irreversible uptake), <i>K</i><sub>1</sub> (delivery), <i>k</i><sub>3</sub> (phosphorylation) in a large healthy control group (n = 47). Describing the parameters' spatial distribution at high resolution (216 regions), we showed that <i>K</i><sub>1</sub> is the least redundant (strong posteromedial pattern), and <i>K</i><sub>i</sub> and <i>k</i><sub>3</sub> have relevant differences (occipital cortices, cerebellum, thalamus). Using multilevel modeling, we investigated how much spatial variance of [<sup>18</sup>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<sub>2</sub>) from <sup>15</sup>O PET. Rs-fMRI-only models explained part of the individual variance in <i>K</i><sub>i</sub> (35%), <i>K</i><sub>1</sub> (14%), <i>k</i><sub>3</sub> (21%), while combining rs-fMRI and CMRO<sub>2</sub> led to satisfactory description of <i>K</i><sub>i</sub> (46%) especially. <i>K</i><sub>i</sub> was sensitive to both local rs-fMRI variables (<i>ReHo</i>) and CMRO<sub>2</sub>, <i>k</i><sub>3</sub> to <i>ReHo</i>, <i>K</i><sub>1</sub> to CMRO<sub>2</sub>. 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.</p>","PeriodicalId":15325,"journal":{"name":"Journal of Cerebral Blood Flow and Metabolism","volume":" ","pages":"1799-1815"},"PeriodicalIF":4.5000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12081390/pdf/","citationCount":"0","resultStr":"{\"title\":\"The brain's \\\"dark energy\\\" puzzle <i>upgraded</i>: [<sup>18</sup>F]FDG uptake, delivery and phosphorylation, and their coupling with resting-state brain activity.\",\"authors\":\"Tommaso Volpi, John J Lee, Andrei G Vlassenko, Manu S Goyal, Maurizio Corbetta, Alessandra Bertoldo\",\"doi\":\"10.1177/0271678X251329707\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 [<sup>18</sup>F]FDG SUVR as a proxy of glucose metabolism. Here, we expanded on our effort by estimating [<sup>18</sup>F]FDG kinetic parameters <i>K</i><sub>i</sub> (irreversible uptake), <i>K</i><sub>1</sub> (delivery), <i>k</i><sub>3</sub> (phosphorylation) in a large healthy control group (n = 47). Describing the parameters' spatial distribution at high resolution (216 regions), we showed that <i>K</i><sub>1</sub> is the least redundant (strong posteromedial pattern), and <i>K</i><sub>i</sub> and <i>k</i><sub>3</sub> have relevant differences (occipital cortices, cerebellum, thalamus). Using multilevel modeling, we investigated how much spatial variance of [<sup>18</sup>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<sub>2</sub>) from <sup>15</sup>O PET. Rs-fMRI-only models explained part of the individual variance in <i>K</i><sub>i</sub> (35%), <i>K</i><sub>1</sub> (14%), <i>k</i><sub>3</sub> (21%), while combining rs-fMRI and CMRO<sub>2</sub> led to satisfactory description of <i>K</i><sub>i</sub> (46%) especially. <i>K</i><sub>i</sub> was sensitive to both local rs-fMRI variables (<i>ReHo</i>) and CMRO<sub>2</sub>, <i>k</i><sub>3</sub> to <i>ReHo</i>, <i>K</i><sub>1</sub> to CMRO<sub>2</sub>. 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.</p>\",\"PeriodicalId\":15325,\"journal\":{\"name\":\"Journal of Cerebral Blood Flow and Metabolism\",\"volume\":\" \",\"pages\":\"1799-1815\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12081390/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cerebral Blood Flow and Metabolism\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/0271678X251329707\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/5/15 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cerebral Blood Flow and Metabolism","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/0271678X251329707","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/15 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
The brain's "dark energy" puzzle upgraded: [18F]FDG uptake, delivery and phosphorylation, and their coupling with resting-state brain activity.
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 K1 is the least redundant (strong posteromedial pattern), and Ki and k3 have 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) from 15O PET. Rs-fMRI-only models explained part of the individual variance in Ki (35%), K1 (14%), k3 (21%), while combining rs-fMRI and CMRO2 led to satisfactory description of Ki (46%) especially. Ki was sensitive to both local rs-fMRI variables (ReHo) and CMRO2, k3 to ReHo, K1 to 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.
期刊介绍:
JCBFM is the official journal of the International Society for Cerebral Blood Flow & Metabolism, which is committed to publishing high quality, independently peer-reviewed research and review material. JCBFM stands at the interface between basic and clinical neurovascular research, and features timely and relevant research highlighting experimental, theoretical, and clinical aspects of brain circulation, metabolism and imaging. The journal is relevant to any physician or scientist with an interest in brain function, cerebrovascular disease, cerebral vascular regulation and brain metabolism, including neurologists, neurochemists, physiologists, pharmacologists, anesthesiologists, neuroradiologists, neurosurgeons, neuropathologists and neuroscientists.