Sarli Giuseppe, De Marco Matteo, Hallikainen Merja, Soininen Hilkka, Bruno Giuseppe, Venneri Annalena
Department of Neuroscience, University of Sheffield, Sheffield, United Kingdom.
Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy.
Brain Connect. 2021 Apr;11(3):201-212. doi: 10.1089/brain.2020.0899. Epub 2021 Jan 28.
The association between regional volumes and resting-state functional networks was tested within the default-mode network (DMN), influenced by Alzheimer pathology, salience network (SalN), not under similar pathological influence, and sensorimotor network (SMN), usually spared by pathology. A total of 148 participants, with Alzheimer's disease (AD) dementia, mild cognitive impairment (MCI), and healthy controls underwent multimodal brain magnetic resonance imaging (MRI). Functional network identification was achieved with group-level independent-component analysis of functional MRI (fMRI) scans. T1 weighted images were also analyzed. Ten regions of interest (ROI) were defined in core hubs of the three networks. Gray-matter volume/functional network strength association was tested within-ROI and cross-ROI in each group by using partial-correlation models and ROI-to-ROI, ROI-to-voxel, and voxel-to-voxel correlations. In controls, a negative association was found between right inferior-parietal volumes and SMN expression in the left precentral gyrus, as revealed by ROI-to-ROI models. In AD, DMN expression was positively associated with the volume of the left insula and the right inferior parietal lobule, and SalN expression was positively associated with volume of the left inferior parietal lobule. ROI-to-voxel models revealed significant associations between the volume of the posterior cingulate cortex and SMN expression in sensorimotor and premotor regions. No significant findings emerged in the MCI nor from voxel-to-voxel analyses. Regional volumes of main network hubs are significantly associated with hemodynamic network expression, although patterns are intricate and dependent on diagnostic status. Since distinct networks are differentially influenced by Alzheimer pathology, it appears that pathology plays a significant role in influencing the association between regional volumes and regional functional network strength.
在默认模式网络（DMN）（受阿尔茨海默病病理影响）、突显网络（SalN）（不受类似病理影响）和感觉运动网络（SMN）（通常不受病理影响）中，测试了区域体积与静息态功能网络之间的关联。共有148名患有阿尔茨海默病（AD）痴呆、轻度认知障碍（MCI）的参与者以及健康对照者接受了多模态脑磁共振成像（MRI）检查。通过对功能磁共振成像（fMRI）扫描进行组水平独立成分分析来实现功能网络识别。还对T1加权图像进行了分析。在这三个网络的核心枢纽中定义了10个感兴趣区域（ROI）。通过使用偏相关模型以及ROI到ROI、ROI到体素和体素到体素的相关性，在每组的ROI内和跨ROI测试灰质体积/功能网络强度的关联。在对照组中，ROI到ROI模型显示，右侧下顶叶体积与左侧中央前回的SMN表达之间存在负相关。在AD组中，DMN表达与左侧岛叶和右侧下顶叶小叶的体积呈正相关，而SalN表达与左侧下顶叶小叶的体积呈正相关。ROI到体素模型显示，后扣带回皮质的体积与感觉运动和运动前区的SMN表达之间存在显著关联。在MCI组中未发现显著结果，体素到体素分析也未得出显著结果。主要网络枢纽的区域体积与血流动力学网络表达显著相关，尽管模式复杂且取决于诊断状态。由于不同网络受阿尔茨海默病病理的影响不同，看来病理在影响区域体积与区域功能网络强度之间的关联中起着重要作用。
