从区域到结缔水平的人脑皮质厚度与葡萄糖代谢之间的耦合:PET/MRI 研究。

IF 2.4 3区 医学 Q3 NEUROSCIENCES
Brain connectivity Pub Date : 2024-03-01 Epub Date: 2024-03-06 DOI:10.1089/brain.2023.0070
Qi Huang, Yihong Yang, Na Qi, Yihui Guan, Jun Zhao, Fengchun Hua, Shuhua Ren, Fang Xie
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引用次数: 0

摘要

背景:大脑结构和功能之间的平衡与衰老和许多脑部疾病有关。本研究旨在使用 18F-FDG PET/MRI 研究大脑结构与功能之间的耦合。通过计算每个受试者整个皮层的 GluM(葡萄糖代谢)和皮层厚度(CTh)之间的受试者内 Spearman 相关性,探讨区域水平的结构和功能耦合,然后将其与年龄相关联,以探讨其生理效应。然后将受试者分为中青年组(MYA)和老年人组(OA)。分别构建了基于 CTh 的结构连通性(SC)和基于 GluM 的功能连通性(FC)矩阵。此外,还对大脑 SC 和 FC 的整体和局部效率进行了评估:结果:97.83%的受试者的区域 CTh 与 GluM 呈显著负相关(r = -0.24 至 -0.71,p):本研究发现 CTh 和 GluM 在区域和结缔水平上都存在耦合,这反映了衰老的进程,并可能为脑部疾病提供新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coupling Between Human Brain Cortical Thickness and Glucose Metabolism from Regional to Connective Level: A Positron Emission Tomography/Magnetic Resonance Imaging Study.

Background: Balance between brain structure and function is implicated in aging and many brain disorders. This study aimed to investigate the coupling between brain structure and function using 18F-fludeoxyglucose positron emission tomography (PET)/magnetic resonance imaging (MRI). Methods: One hundred thirty-eight subjects who underwent brain 18F-FDG PET/MRI were recruited. The structural and functional coupling at the regional level was explored by calculating within-subject Spearman's correlation between glucose metabolism (GluM) and cortical thickness (CTh) across the cortex for each subject, which was then correlated with age to explore its physiological effects. Then, subjects were divided into groups of middle-aged and young adults and older adults (OAs); structural connectivity (SC) based on CTh and functional connectivity (FC) based on GluM were constructed for the two groups, respectively, followed by exploring the connective-level structural and functional coupling on SC and FC matrices. The global and local efficiency values of the brain SC and FC were also evaluated. Results: Of the subjects, 97.83% exhibited a significant negative correlation between regional CTh and GluM (r = -0.24 to -0.71, p < 0.05, FDR correction), and this CTh-GluM correlation was negatively correlated with age (R = -0.35, p < 0.001). For connectivity matrices, many regions showed positive correlation between SC and FC, especially in the OA group. Besides, FC exhibited denser connections than SC, resulting in both higher global and local efficiency, but lower global efficiency when the network size was corrected. Conclusions: This study found couplings between CTh and GluM at both regional and connective levels, which reflected the aging progress, and might provide new insight into brain disorders. Impact statement The intricate interplay between brain structures and functions plays a pivotal role in unraveling the complexities inherent in the aging process and the pathogenesis of neurological disorders. This study revealed that 97.83% subjects showed negative correlation between the brain's regional cortical thickness and glucose metabolism, while at the connective level, many regions showed positive correlations between structural and functional connectivity. The observed coupling at the regional and connective levels reflected physiological progress, such as aging, and provides insights into the brain mechanisms and potential implications for the diagnosis and treatment of brain disorders.

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来源期刊
Brain connectivity
Brain connectivity Neuroscience-General Neuroscience
CiteScore
4.80
自引率
0.00%
发文量
80
期刊介绍: Brain Connectivity provides groundbreaking findings in the rapidly advancing field of connectivity research at the systems and network levels. The Journal disseminates information on brain mapping, modeling, novel research techniques, new imaging modalities, preclinical animal studies, and the translation of research discoveries from the laboratory to the clinic. This essential journal fosters the application of basic biological discoveries and contributes to the development of novel diagnostic and therapeutic interventions to recognize and treat a broad range of neurodegenerative and psychiatric disorders such as: Alzheimer’s disease, attention-deficit hyperactivity disorder, posttraumatic stress disorder, epilepsy, traumatic brain injury, stroke, dementia, and depression.
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